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SponSored and organized by

Division of Neurosciences, Pablo de Olavide UniversityCeslatiC Foundation (Centro de Estudios Latinoamericanos para la Ciencia y la Cultura)

Co-SponSored by

Carmona City HallCibertec S.A.Olavide en CarmonaPablo de Olavide UniversityUniverlab S.L.

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CommitteeS

international Committee

José María Delgado García (Pablo de Olavide University, Spain)Rubin Wang (Hangzhou Dianzi University and East China University of Science and Technology, China)Jan Lauwereyns (Kyushu University, Japan)Minoru Tsukada (Tamagawa University, Japan)IchiroTsuda (Hokkaido University, Japan)Hans Liljenström, Hans (SLU and Agora for Biosystems, Sweden)

loCal organizing Committee

José María Delgado García (Chairman)Agnès GruartMiguel MerchánJuan Carlos López-RamosRocío Leal-CampanarioRaudel Sánchez-Campusano

young loCal organizing Committee

Ana Rocío Conde MoroFlorbela Da Rocha AlmeidaMar Reus GarcíaJosé Antonio García Moreno

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Paper Acceptance and Book Edition

Raudel Sánchez Campusano (E-mail: [email protected])Xiaochuan Pan (E-mail: [email protected])

Secretariat

Antonio Quetglas (E-mail: [email protected])

Travel Agency

Antonio Vázquez (Viajes Pacífico, E-mail: [email protected])José M. Ávila (Viajes Pacífico, E-mail: [email protected])

mailto:[email protected]





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TABLE OF CONTENTSi. program at a glanCe 9

ii. Full program 11

iii. abStraCtS 23

plenary leCtureS 251st Plenary conference: Quantification of human sensorimotor behavior in the field and resulting databases. (Invited Speaker: Prof. Dr. Pierre-Paul Vidal, France) 26

2nd Plenary conference. Mild cortical dysplasia as a model of mental disorder.(Invited Speaker: Prof. Dr. Salvador Martínez, Spain) 27

3rd Plenary conference: It takes two to tango: cerebellar modules and learning rules.(Invited Speaker: Prof. Dr. Chris De Zeeuw, Netherlands) 28

4th Plenary conference: Cortical, hippocampal and striatal activations during reward-seeking behaviors. (Invited Speaker: Prof. Dr. Yoshikazu Isomura, Japan) 29

5th Plenary conference: Learning in a dish: from timing-dependent synaptic plasticity toemergent network dynamics. (Invited Speaker: Prof. Dr. Guo-Qiang Bi, China) 30

6th Plenary conference: Dynamic visual processing through top-down influences andperceptual learning. (Invited Speaker: Prof. Dr. Wu Li, China) 31

SympoSia 33Symposium S1: Neurodynamics of coincidence detection: from synapses to behavior 34Symposium S2: Comprehensive neurophilosophy – a Tribute to W.J. Freeman 39Symposium S3: Neural engineering 44Symposium S4: Learning about learning: different scientific edges 49Symposium S5: Cerebelar markers of vulnerable aging: from structure to function 54Symposium S6: Data analysis & mathematical modeling for dynamic brain 59Symposium S7: The states of the brain: a dynamic puzzle to create daily behaviors 66Symposium S8: Tamagawa dynamic brain forum - beyond neural representation 71Symposium S9: Metastability and phase-transitions in neural, mental and social systems 77Symposium S10: Analysis of electrophysiological signals in brain dynamics 85Symposium S11: Cognitive dynamics of large-scale brain circuits 95Symposium S12: Dynamic modelling of EEG and fMRI 101

poSter SeSSion 107

iV. general inFormation 147

I. PROGRAM AT A GLANCE

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program at a glanCe

day morning SeSSion lunCh time aFternoon SeSSion eVening

August 1 9:00 – 13:00Registration open

16:00-20:30Registration open

A visit to Carmona monuments will be provided to interested people (19:00-20:45)

21:00Reception party at the hotel Alcázar de la Reina

August 2 8:30-8:45Opening Ceremony9:00-10:00Plenary Lecture 110:00-10:30Coffee Break10:30-12:30Symposia 1 and 212:30-14:00Poster session 1

14:00-15:30Buffet lunch at the hotel Alcázar de la Reina

16:00-17:00Plenary Lecture 217:00-17:30Coffee break17:30-19:30Symposia 3 and 419:30-20:30Poster session 2

21:00-23:00Dinner at the hotel Alcázar de la Reina

August 3 8:30-9:30Plenary Lecture 39:30-10:00Coffee Break10:00-12:00Symposia (5 and 6)12:00-14:00Poster session 3


16:00-17:00Plenary Lecture 417:00-17:30Coffee break17:30-19:30Editorial Board Meeting of Cognitive Neurodynamics17:30-19:30Symposia 7 and 819:30-20:30Poster session 4

21:00-23:00Dinner at the hotel Alcázar de la Reina

August 4 8:30-9:30Plenary Lecture 59:30-10:00Coffee Break10:00-12:00Symposia 9 and 1012:00-14:00Poster session 5


16:00-17:00Plenary Lecture 617:00-17:30Coffee break17:30-19:30Symposia (11 and 12)19:30-20:30Poster session 6

21:00-24:00Gala Dinner and Flamenco concert at the Casa de Córdoba (Curro Montoya Restaurant)

August 5 9:00- Tourist visit to Seville monuments

II. FULL PROGRAM

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auguSt 1 (tueSday)9:00-13:00Reception is open. The reception desk will be located at the hotel main hall

16:00-20:30Reception is open

19:00-20:45A free guided visit to the main Carmona monuments. Departure will be from the hotel main hall. Two English-speaking guides will be in charge of the visit.

21:00-23:00Reception party (Swimming pool area of the hotel)

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auguSt 2 (WedneSday)

8:30-8:45Opening Ceremony (Salón Puerta de Sevilla)José M. Delgado-García and Rubin Wang

9:00-10:00Plenary Lecture 1 (Salón Puerta de Sevilla)Speaker: Pierre-Paul Vidal (COGNAC-G Université Paris Descartes-CNRS, Paris, France)Title: Quantification of human sensorimotor behavior in the field and resulting databasesChairperson: José M. Delgado-García (Pablo de Olavide University, Sevilla, Spain)

10:00-10:30Coffee Break (Salón Puerta de Sevilla)

10:30-12:30Symposium 1 (Salón Puerta de Sevilla)Organizer: Miguel A. Merchán (INCYL, Salamanca University, Salamanca, Spain)Title: Neurodynamics of coincidence detection: From synapses to behavior

Speakers:1. Alberto Ferrús, Instituto Cajal, CSIC, Madrid, Spain.Electric and coincident synapses in fast neural processes2. Carlos Acuña, Universidad de Santiago, Santiago de Compostela, Spain.Neuronal encoding of errors and successful decisions improve future behavioral performance3. Philip X. Joris, Laboratory of Auditory Neurophysiology, University of Leuven, Belgium.Monaural and binaural coincidence detection in the auditory system4. Ray Meddis, Essex Hearing Research Laboratory, University of Essex, Colchester, U.K.Coincidence detection and absolute threshold in the auditory system

10:30-12:30Symposium 2 (Salón de la Reina)Organizer: Jan Lauwereyns (Kyushu University, Nishi-ku, Fukuoka, Japan)

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Title: Comprehensive Neurophilosophy -- a Tribute to Walter J. Freeman

Speakers: 1. Ichiro Tsuda, Hokkaido University, Hokkaido, Japan. Self-organization with constraints: The significance of invariant manifolds 2. Nobuo Kazashi, Kobe University, Kobe, Japan. On the “Discontinuous continuity” of the self: memory, attention, and mindful breathing (Freeman along with William James)3. Anton Luis Sevilla, Kyushu University, Nishi-ku, Fukuoka, Japan.Mindful education and the Kyoto School: contemplative pedagogy, enactivism, and the philosophy of nothingness4. Jan Lauwereyns, Kyushu University, Nishi-ku, Fukuoka, Japan.Beyond Prediction: Self-Organization of Meaning with the World as a Constraint

12:30-14:00Poster session 1 (Salón Puerta de Sevilla)

14:00-15:30Buffet Lunch (Salón Cueva de la Batida)

16:00-17:00Plenary Lecture 2 (Salón Puerta de Sevilla)Speaker: Salvador Martínez (INA, CSIC and Miguel Hernández University, Alicante, Spain)Title: Mild cortical dysplasia as a model of mental disorderChairperson: Agnès Gruart (Pablo de Olavide University, Sevilla, Spain)


17:30-19:30Symposium 3 (Salón Puerta de Sevilla)Organizer: Laura Roa (Biomedical Engineering, Engineering School, Seville, Spain)Title: Neural Engineering

Speakers:1. José Luis Pons Rovira, Biomedical Engineering Group, CSIC, Madrid, Spain.Technology-driven neuromodulation and neural plasticity: stroke and iSCI2. Roberto Hornero Sánchez, Grupo de Ingeniería Biomédica, Valladolid University, Valladolid, Spain. Neurocognitive training by means of a motor imagery-based Brain Computer Interface in the elderly3. Javier Reina Tosina, Biomedical Engineering, Engineering School, University of Seville, Seville, Spain.Intra-body Communications as an Emerging Approach to Neuromodulation4. Christopher James, University of Warwick, Warwick, UK.Independent Component Analysis in brain signals

17:30-19:30Symposium 4 (Salón de la Reina)Organizer: Agnès Gruart (Division of Neurosciences, Pablo de Olavide University, Seville, Spain)Title: Learning about learning: different scientific edges

Speakers:

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1. Agnès Gruart, Division of Neurosciences, Pablo de Olavide University, Seville, Spain. When and where learning is taking place during instrumental learning2. Cyril Herry, Neurocentre Magendie, INSERM U862, Université Bordeaux Segalen, Bordeaux, France.Neuronal circuits and mechanisms of fear behavior3. Victoria Puig, Hospital del Mar Medical Research Institute, Barcelona Biomedical Research Park (PRBB), Barcelona, Spain.Serotonin modulation of the neuronal activity and brain waves in the prefrontal cortex4. Miguel Remondes, Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal.Brain maps for choice behaviors


21:00-23:00Dinner (Salón Cueva de la Batida)

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auguSt 3 (thurSday)

8:30-9:30Plenary Lecture 3 (Salón Puerta de Sevilla)Speaker: Chris De Zeeuw, Netherlands Institute for Neuroscience, Amsterdam, The NetherlandsTitle: It takes two to tango: Cerebellar modules and learning rulesChairperson: Rocío Leal-Campanario (Pablo de Olavide University, Sevilla, Spain)


10:00-12:00Symposium 5 (Salón Puerta de Sevilla)Organizer: José L. Cantero (Pablo de Olavide University, Sevilla, Spain)Title: Cerebral markers of vulnerable aging: from structure to function

Speakers:1. Heidi I.L. Jacobs, School for Mental Health & Neuroscience, Alzheimer Centre Limburg, Faculty of Health Medicine & Life Sciences, Maastricht University, The Netherlands.Locus coeruleus resting-state functional connectivity trajectories over the adult lifespan2. Mercedes Atienza, Laboratory of Functional Neuroscience, CIBERNED, Pablo de Olavide University, Seville, Spain.APOE4 status determines the impact of temporal lobe degeneration on memory in patients with mild cognitive impairment3. Julio Acosta Cabronero, Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London WC1N 3BG, United Kingdom.Microstructural and biochemical change measured with MRI: a neurodegenerative disease perspective4. José L. Cantero, Laboratory of Functional Neuroscience, CIBERNED, Pablo de Olavide University, Seville, Spain.

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Relationship between changes in sleep structure and peripheral blood markers in mild cognitive impairment

10:00-12:00Symposium 6 (Salón de la Reina)Organizers: Yutaka Yamaguti (Fukuoka Institute for Technology, Japan),Akihiro Yamaguchi (Fukuoka Institute for Technology, Japan), andIchiro Tsuda (Hokkaido University, Japan)Title: Data analysis and mathematical modeling for dynamic brain ― Dedicated to Walter J. Freeman

Speakers: 1. Shozo Tobimatsu, Kyushu University, JapanFunctional significance of neural oscillations in humans2. Rubin Wang, East China University of Science and Technology, P.R. ChinaTBA3. Yuichi Katori, School of Systems Information Science, Future University Hakodate, JapanNetwork model for dynamics of perception with reservoir computing and predictive coding4. Hiromichi Tsukada, Okinawa Institute for Science and Technology, JapanAnalysis of structure-function relationship using a whole-brain dynamic model based on MRI images of the common marmoset5. Jan Lauwereyns, Kyushu University, JapanBias versus Sensitivity in Cognitive Processing: A Critical, but Often Overlooked, Issue for Data Analysis6. Shigetoshi Nara, Hokkaido University, JapanA pseudo-neuron device and firing dynamics of their networks similar to neural synchronizing phenomena between far distant fields in brain



16:00-17:00Plenary Lecture 4 (Salón Puerta de Sevilla)Speaker: Yoshikazu Isomura, Brain Science Institute, Tamagawa University, Tokyo, JapanTitle: Cortical, hippocampal and striatal activations during reward-seeking behaviorsChairperson: Minoru Tsukada (Tamagawa University, Japan)


17:30-19:30Editorial Board Meeting of Cognitive NeurodynamicsChairpersons: Xiaochuan Pan (East China University of Science and Technology, P.R. China) andRaudel Sánchez-Campusano (Pablo de Olavide University, Sevilla, Spain)

17:30-19:30Symposium 7 (Salón Puerta de Sevilla)Organizer: Juan de los Reyes Aguilar (Hospital Nacional de Parapléjicos, Toledo, Spain)Title: The states of the brain: a dynamic puzzle to create daily behaviors

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Speakers:1. María Victoria Sánchez-Vives, ICREA and IDIBAPS, Barcelona, Spain.Cortical dynamics in different consciousness states2. Oscar Herreras, Instituto Cajal, CSIC, Madrid, Spain.Using pathway-specific LPFs to disclose the neuron populations and networks involved in brain state changes3. Jaime Gómez-Ramírez, Fundación CIEN, CTB-UPM, Madrid, Spain.Causality in brain dynamics: pitfalls and hope4. Juan de los Reyes Aguilar, Hospital Nacional de Parapléjicos, Toledo, Spain.Neural plasticity is temporally and spatially heterogeneous in the somatosensory cortex after a spinal cord injury

17:30-19:30Symposium 8 (Salón de la Reina)Organizer: Yoshikazu Isomura (Brain Science Institute, Tamagawa University, Tokyo, Japan)Title: Tamagawa Dynamic Brain Forum - Beyond neural representation

Speakers:1. Hiromichi Tsukada, Okinawa Institute of Science and Technology, Kunigami, Japan.A structure and function of hippocampal memory networks in consolidating spatiotemporal contexts2. Makoto Ito and Kenji Doya, Neural Computation Unit, Okinawa Institute of Science and Technology, Okinawa, Japan and Progress Technologies, Inc., Koto-ku, Tokyo, Japan.Information coded in the striatum during decision making3. Taro Toyoizumi, RIKEN Brain Science Institute Saitama, Japan.Efficient signal processing in random networks that generate variability: A comparison of internally generated and externally induced variability4. Yoshikazu Isomura, Brain Science Institute, Tamagawa University, Tokyo, Japan.The Multi-Linc method reveals spike dynamics in cortical projection neurons5. Xiaochuan Pan, Institute for Cognitive Neurodynamics, East China University of Science and Technology, P.R. China.Injection of muscimol into prefrontal cortex impairs monkey’s reward transitive inference


21:00-23:00Dinner (Salón Cueva de la Batida)

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auguSt 4 (Friday)

8:30-9:30Plenary Lecture 5 (Salón Puerta de Sevilla)Speaker: Guo-Qiang Bi (School of Life Sciences, University of Science and Technology of China, Hefei, P.R. China).Title: Learning in a dish: From timing-dependent synaptic plasticity to emergent network dynamics.Chairperson: Rubin Wang, East China University of Science and Technology, P.R. China.

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10:00-12:00Symposium 9 (Salón Puerta de Sevilla)Organizer: Hans Liljeström (Dept. of Energy and Technology, SLU, Uppsala, Sweden)Title: Metastability and Phase-Transitions in Neural, Mental and Social Systems

Speakers:1. Hans A. Braun, Department for Neuroendocrinology and Neurodynamics, Institute of Physiology, Philipps University of Marburg, Marburg, Germany.Noise as a source of flexible decision making2. Hans Liljeström and Azadeh Hassannejad Nazir, Biometry and Systems Analysis, Department of Energy and Technology, SLU, Uppsala, Sweden.A neuro-cognitive model for social decision making3. Paul Rapp, Department of Defense, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.Psychoanalysis, cognitive neuroscience and dynamical systems theory4. Emmanuelle Tognoli, Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, USA. On the nature of coordination in nature5. Alessandro E.P. Villa, Laboratory of Neuroheuristics, University of Lausanne, Lausanne, Switzerland.An ERP study reveals how training with dual n-back task affects risky decision making in a gambling task in ADHD patients6. James J. Wright, Department of Psychological Medicine, School of Medicine, University of Auckland, Auckland, New Zealand. Cortical synaptic development and consequences for information processing

10:00-12:00Symposium 10 (Salón de la Reina)Organizers: Toshishisa Tanaka (Tokyo University of Agriculture and Technology) andJianting Cao (Saitama Institute of Technology, Japan)Title: Analysis of electrophysiological signals in brain dynamics

Speakers: 1. Daqing Guo, University of Electronic Science and Technology of China, China. Functional connectivity of the rat default mode network2. Jing Jin, East China University of Science and Technology, Shanghai, China. A new paradigm based on dynamic visual stimulation in BCI3. Tao Zhang, Nankai University, P.R.China. Alpha phase is regulated by gamma power in mouse hippocampus4. Zhuo Yang, Nankai University, P.R.China. Notch1 signaling pathway is involved in the voluntary running-induced hippocampal neurogenesis and antidepressant effects of c57bl/6j mice5. Hongyan Cui, Department of Orthopedics and Traumatology, The University of Hong Kong, Hong Kong. P.R.China.Trial-to-trial latency variability of somatosensory evoked potential as an indication of spinal cord demyelination6. Arao Funase, Nagoya Institute of Technology, RIKEN, Japan.Movement-related cortical potential in saccadic eye movements with cued-movement task7. Atsuhiro Ichidi, Tokyo University of Agriculture and Technology, Tokyo, Japan.

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Motor imagery EEG during movement observation: A comparison between stroke and healthy subjects8. Natsuki Morita and Yoshikazu Washizawa. University of Electro-Communication, Japan. Asynchronous stimulation method for N100-P300 Speller9. Jianting Cao, Saitama Institute of Technology, Japan.The influence of sodium current on spontaneous spiking in up and down activities



16:00-17:00Plenary Lecture 6 (Salón Puerta de Sevilla)Speaker: Wu Li (State Key laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University in China, Beijing, P.R. China)Title: Dynamic visual processing through top-down influences and perceptual learningChairperson: Barry J. Richmond, NIMH/NIH/DHHS, USA


17:30-19:30Symposium 11 (Salón Puerta de Sevilla)Organizers: Steven L. Bressler (Department of Psychology, Florida Atlantic University, Boca Ratón, USA) and Raudel Sánchez-Campusano (Division of Neurosciences, Pablo de Olavide University, Seville, Spain)Title: Cognitive dynamics of large-scale brain circuits - a Tribute to Walter J. Freeman

Speakers:

1. Gustavo Deco, Center for Brain and Cognition. Theoretical and Computational Group. Universitat Pompeu Fabra (UPF) / ICREA and Department of Information and Technologies, UPF, Barcelona, Spain.Whole-brain models: Identifying brain states2. Steven L. Bressler, Center for Complex Systems and Brain Sciences and Department of Psychology, Florida Atlantic University, Boca Raton, USA.Anticipatory top-down inter-areal cortical coupling3. Ernesto Pereda, Department of Industrial Engineering, University of La Laguna. Spain.Dynamical patterns of brain networks as neuronal correlates of aesthetic appreciation4. Julien Vezoli, Ernst Strügmann Institute for Neuroscience in Cooperation with Max Planck Society, Frankfort, Germany.Large-scale dynamics of frequency-specific cortical interaction maps5. Raudel Sánchez-Campusano, Division of Neurosciences, Pablo de Olavide University, Seville, Spain.Functional states of cortical-subcortical network nodes

17:30-19:30Symposium 12 (Salón de la Reina)Organizer: Xu Lei (Sleep and neuroimaging Center, Faculty of Psychology, Southwest University in China, Chongqing, China)

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Title: Dynamic modelling of EEG and fMRI

Speakers:1. Xu Lei, Faculty of Psychology, Southwest University, Chongqing, China.Spontaneous theta rhythm predicts insomnia duration: a resting-state EEG study2. Daqing Guo, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.Biophysical models of absence seizures3. Yin Tian, Bio-information College, Chongqing University of Posts and Telecommunications, Chongqing, China.Electrical cortex time-varying network based on the inverse operation: a study on N170 for emotional face recognition4. Quanying Liu, Neural Control of Movement Laboratory, ETH Zurich, 8057 Zurich, Switzerland. High-density EEG permits the detection of resting state networks5. Zhihui Wang and Quingyun Wang, Department of Dynamics and Control, Beihand University, Beijing, China.Seizures dynamics in a mean-field model with bursting dynamics


21:00-24:00Gala Dinner and Flamenco concert (Curro Montoya Restaurant at the Casa de Córdoba)

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poSter SeSSionS (1-6)Posters will be displayed during the whole Meeting at the Salon Puerta de Sevilla. Please, hang your poster at the indicated number. Poster presenters should be available at the indicated time for the six poster sessions.

P1. An electrophysiological approach to the study of the claustrum: Recording claustral neurons in alert behaving rabbits. M. Mar Reus-García*, A. Gruart, J.M. Delgado-García.

P2. Structure and dynamics of self-organized neuronal network with an improved STDP rule. Rong Wang, Ying Wu, Mengmeng Du, Jiajia Li.

P3. A pseudo-neuron device and firing dynamics of their networks similar to neural synchronizing phenomena between far distant field in brain. T. Yano, Y. Goto, T. Nagaya, I. Tsuda, S. Nara.

P4. Effect of spike-timing-dependent plasticity on stochastic spike synchronization in an excitatory neuronal population. Sang-Yoon Kim, Woochang Lim.

P5. Study of dynamic mechanism for rhythmic transition of glial-neuronal network. Mengmeng Du, Ying Wu*.

P6. Changes in phase synchronization of EEG during development of symbolic communication systems. M. Fujiwara, T. Hashimoto, G. Li, J. Okuda, T. Konno, K. Samejima, J. Morita.

P7. Ratbutton: a user-friendly touchscreen presentation software. C. Andreu-Sánchez*, M. A. Martín-Pascual, A. Gruart, J.M. Delgado-García.

P8. Differences in perceiving narratives through screens or reality. M.A. Martín-Pascual*, C. Andreu-Sánchez, J. M. Delgado-García, A. Gruart.

P9. Behavioural and brain activity modulation through neurofeedback training using electroencephalography. T. Kimura, J. Okuda.

P10. Complexity of heart rate as a value of behavioral complexity. A.V. Bakhchina*.

P11. Changes in brain activity during instrumental behaviour after additional learning in rats. Vladimir Gavrilov.

P12. Cortical and subcortical activities for food and social interactions with rats. F. Rocha-Almeida*, A.R. Conde-Moro, J.M. Delgado-García, A. Gruart.

P13. Role of inhibitory control processes in decision-making procedures. J. A. García-Moreno*, C. Andreu-Sánchez, M. Á. Martín-Pascual, J. M. Delgado-García, A. Gruart.

P14. Spectral power and maturational frequency-coupling differences between attention deficit and controls children and adolescents. Elena I. Rodríguez-Martínez, Brenda Y. Angulo-Ruiz, Antonio Arjona-Valladares, Francisco J. Ruiz-Martínez, Jaime Gómez-González, Carlos M. Gómez*.

P15. Behavioral working memory development in attention deficit children and adolescents. Classification by linear discrimination analysis. Elena I. Rodríguez-Martínez*, Antonio Arjona-Valladares, Francisco J. Ruíz-Martínez1, Manuel Morales, Jaime Gómez-González, Carlos M. Gómez.

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P16. Event related potentials during a delayed match-to-sample test to evaluate working memory development in control and attention deficit children and adolescents. Antonio Arjona-Valladares*, Elena I. Rodríguez-Martínez, Francisco J. Ruíz-Martínez, Jaime Gómez-González, Carlos M. Gómez.

P17. Stochastic multi-resonance induced by noise in a neuronal networks of subnetworks. Xiaojuan Sun, Zhaofan Liu, Huiyan Li.

P18. A model of plasticity-dependent network activity in rodent hippocampus during exploration of novel environments. P. Theodoni, B. Rovira, A. Roxin.

P19. High-density simultaneous recordings from visual cortex and superior colliculus in a rat: a pilot study in retinal prosthesis. A. Barriga-Rivera*, T. Guo, N. H. Lovell, J. W. Morley, G. J. Suaning.

P20. Decomposition of superimposed chaotic spike sequences by using the bifurcating neuron. Akihiro Yamaguchi, Yutaka Yamaguti, Masao Kubo.

P21. Hippocampal and prefrontal cortex network dynamics are modulated by serotonin receptors and antipsychotic drugs. T. Gener*, M. Alemany, M.V. Puig.

P22. Connecting mathematical modeling with electrophysiological experiments: the virtual laboratories SIMNERV and SIMNEURON. A. Tchaptchet*, H.A. Braun.

P23. Medial prefrontal cortex involvement in interactive behaviors between rats. A.R. Conde-Moro*, F. Rocha-Almeida, R. Sánchez-Campusano, J. M. Delgado-García, A. Gruart.

P24. Computer simulation of noise effects in the neighbour of stimulus threshold for a mathematical model of homeostatic regulation of sleep wake cycles. Wuyin Jin, Qian Lin, An Wang, Chunni Wang.

P25. Effects of temporal integration on computational performance of spiking neural network. Fangzheng Xue, Yang Zhang, Hongjun Zhou, Xiumin Li*.

P26. Abnormal firing rate of deep cerebellar nuclei neurons in Lurcher mice is related with a poor performance of the classical eyeblink conditioning. J.C. López-Ramos*, Z. Houdek, J. Cendelín, F. Vožeh, J.M. Delgado-García.

P27. Cortical slow wave propagation patterns and network memory in different brain states in the mouse. M. Dasilva*, A. Pazienti, M. Mattia, M.V. Sanchez-Vives.

P28. Behavioral, electrical and morphological effects of chronic growth hormone/IGF-I hypersecretion in adult rats. R. Leal-Campanario*, J.F. Martin-Rodriguez, V.D. Ramos-Herrero, G. Gutiérrez-Parra, Á. Flores, A. Madrazo-Atutxa, D.A. Cano, A. Gruart, J.M. Delgado-Garcia, A. Leal-Cerro.

P29. Behavioral and cognitive impairments induced by low doses of MK-801 and ketamine. M. Lovera-Ulecía*, L. Moreno-Lama*, M.Á. Gómez-Climent, J.M. Delgado-García, A. Gruart.

P30. VISSOR: An algorithm for the detection, identification, and classification of the action potentials distributed across electrophysiological recordings. C.R. Caro-Martín, J.M. Delgado-García, A. Gruart, R. Sánchez-Campusano*.

P31. ERFo, an algorithm for extracting a range of optimal frequencies of an electrophysiological recording. C.R. Caro-Martín*, A. Gruart, J. M. Delgado-García, A.E.P. Villa.

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P32. Postnatal development of sleep-wake cycle in noradrenalin deficient mice: involvement in learning. E. Domínguez-del-Toro* and A. Prados-Pardo.

P33. Synchrony and rhythm in a small world cortical neural network. Xia Shi, Zhiheng Liu.

P34. Precision Control of Biological Reaction-Diffussion Network by using Synchronization. Jianwei Shen, Lingli Zhou, Linan Guan.

P35. Multiple epileptogenic foci can promote seizure discharge onset and propagation. Denggui Fan and Qingyun Wang.

P36. Coherence-based coding in spiking neural network with global inhibitory feedback. Jinli Xie, Qinjun Zhao, and Jianyu Zhao

P37. Neural generator of the N2 component for abstinent heroin addicts in a dot-probe task. Hongqian Li, Qinglin Zhao, Bin Hu, Yu Zhou and Quanying Liu.

P38. Self-assembly of cortical networks and the resulting cognitive framework. James J. Wright.

III. ABSTRACTS

PLENARY LECTURES

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1st Plenary conference

QUANTIFICATION OF HUMAN SENSORIMOTOR BEHAVIOR IN THE FIELD AND RESULTING DATABASES

Invited Speaker: Prof. Dr. Pierre-Paul VidalCOGNAC-G Université Paris Descartes-CNRS UMR-MD-SSA, Paris, France

Abstract: “COGNAC G” is a cooperative projects that investigate the long-term follow up of Human groups, which have in common to be engaged during long stretch of time in very complex behavior and therefore, which are at risk. These populations require to be followed in order to evaluate their training, to check the maintenance of their high skilled capabilities and to avoid to put them under excessive pressures, leading to chronic syndromes such as the burn out syndrome, overtraining and PTSD. We propose to name these groups “High maintenance cohorts” or HMC. They are very diverse and, being evolution of society, their number will inevitably rise. To quote few examples, HMC include military the groups in active duties, sportsmen at high level of competition, patients with neurological diseases under reeducation, psychiatric patients, people with heavy chronic handicaps etc. The proposal is two folds: First, we intend to learn how to monitor and quantify the behavior of these high maintenance cohorts both at the sensorimotor and cognitive level. These measurements to be efficient should be in real time, continuous and non-invasive. Second, we propose to investigate how to use these measurements to build and exploit large data banks allowing the effective longitudinal follow-up of these HMC. In brief, COGNAC G goal is to explore the phenotypes or better the ethomics of human subjects. These data banks will be later enriched with other types of variables, which cannot be recorded on line such as biological, psychological and sociological variables and the genotypes. These data can include either direct measurements or data extracted from various databank not directly concerned by the COGNAC project but rendered available by the subjects, once the adequate ethical rules enforced (anonymization, confidentiality etc.). One can quote the daily activities extracted from the phone GPS, psycholinguistic analysis of the medical records etc. Logically these data banks, should then be used to establish norms on statistical bases which will be used to prevent physiological and psychological hardship as far as possible, to detect pathologies at their onset and personalize their treatments.

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2nd Plenary conference

MILD CORTICAL DYSPLASIA AS A MODEL OF MENTAL DISORDER

Invited Speaker: Prof. Dr. Salvador MartínezSalvador Martinez and Emilio Geijo Barrientos

Instituto de Neurociencies-CSIC; and Miguel Hernández University (UMH), Alicante, Spain

Abstract: LIS1 plays a major role in the development of the cerebral cortex, and haploinsufficient mutations cause human lissencephaly type 1. We have studied some structural and functional properties of the cerebral cortex of Lis1/sLis1 mutant mice, which present a deletion in the first exon similar to that observed in a mild form of lissencephaly in human. In Mouse model and human cortex there is and altered distribution of cortical interneurons mainly accumulating in the deep neocortical layers. In the mouse model, fast spiking (FS) inhibitory interneurons (parvalbumin+) exhibited significant electrophysiological alterations. Furthermore, the whole electrical activity of the cortex recorded in anesthetized animals was modified, with increased power of the alpha, beta and gamma bands as well as more coherent and synchronized activity between layers 2/3 and 5 and between layers 5 and 6. Lis1/sLis1 embryos also exhibited a delay of cortical innervation by the thalamocortical fibers. We have explored in Lis1/sLis1 mice anomalies in forebrain cholinergic neuron development, which migrate from pallium to subpallium, and functionally represent the main cholinergic input to the cerebral cortex, modulating cortical activity and facilitating attention, learning, and memory. We studied basal forebrain neurons in Lis1/sLis1 mice during development, and described structural and hodological differences between wild-type and Lis1/sLis1 embryos. In addition, septohippocampal projections showed altered development in mutant embryos. Basal forebrain abnormalities could contribute to hippocampal excitability anomalies secondary to Lis1 mutations and may explain the cognitive symptoms associated to cortical displasia-related mental diseases and epileptogenic syndromes. Moreover, the study of general cortical activity by early gene expression (c-fos) showed an increasing of neuronal activity in the auditory cortex and hippocampus, in basal conditions of stimuli. Overall, these observations indicate that the alterations in the interneurons distribution in Lis1/sLis1 mouse cortex may not only be a lissencephaly animal model, but also of mental diseases where cortical development is altered.

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3rd Plenary conference

IT TAKES TWO TO TANGO: CEREBELLAR MODULESAND LEARNING RULES

Invited Speaker: Prof. Dr. Chris I. De Zeeuw1,2

1 Department of Neuroscience, Erasmus MC, Rotterdam, The Netherlands2 Netherlands Institute for Neuroscience, Amsterdam, The Netherlands

Abstract: Whereas our ability to store semantic declarative information can nowadays be readily surpassed by that of simple personal computers, our ability to learn and express procedural memories still outperforms that of supercomputers controlling the most advanced robots. To a large extent our procedural memories are formed in the cerebellum, which embodies more than two thirds of all neurons in our brain. In this lecture I will focus on the emerging view that different modules of the cerebellum employ different encoding schemes to form and express their respective memories. More specifically, zebrin-positive zones in the cerebellum, such as those controlling adaptation of the vestibulo-ocular reflex or whisker movements, appear to predominantly form their memories by potentiation mechanisms and express their memories via rate coding, whereas zebrin-negative zones, such as those controlling eyeblink conditioning, appear to predominantly form their memories by suppression mechanisms and express their memories in part by temporal coding employing rebound bursting. Together, the different types of modules offer a rich repertoire to acquire and control sensorimotor processes with specific challenges in the spatiotemporal domain.

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4th Plenary conference

CORTICAL, HIPPOCAMPAL AND STRIATAL ACTIVATIONS DURING REWARD-SEEKING BEHAVIORS

Invited Speaker: Prof. Dr. Yoshikazu IsomuraBrain Science Institute, Tamagawa University, Tamagawagakuen, Machida, Tokyo 194-8610, Japan

Abstract: What happens in the brain when an animal performs a reward-seeking behavior? To address this issue at a single-cell level, we established several behavioral tasks requiring rats to manipulate (push, hold, and pull) a lever correctly with their forelimb to acquire a drop of reward water in a head-fixed condition (e.g., Kimura, 2012). In a series of our experiments, we have examined functional (behavioral task-related) spike activity in the motor cortex, striatum, and hippocampus, by using our juxtacellular recording as well as multi-neuronal recording. In the motor cortex, we showed that excitatory pyramidal cells were activated diversely whereas inhibitory fast-spiking interneurons were activated uniformly across cortical layers in relation with their task performance (Isomura, 2009; Saiki, 2014). Their spiking activity was phase-locked to slow/fast gamma and theta oscillations of local field potentials in a layer-specific manner (Igarashi, 2013), and often synchronous among nearby neurons (Kimura, 2017). Both intra- and extra-telencephalic-type pyramidal cells displayed the functional spike activity (Saiki, 2017). In the striatum, we analyzed functional spike activity of striatal projection neurons, which were identified juxtacellularly with in situ hybridization for dopamine D1 receptors, during their reward-seeking behaviors in a reward-expectable condition, and suggested that striatal projection neurons for the direct (D1-positive) and indirect (D1-negative) pathways may work cooperatively to integrate motor and reward information (Isomura, 2013; Nonomura, unpublished). In the hippocampus, we found two distinct types of sharp-wave ripples differently occurring depending on the reward expectation during their task performance. The first type (with larger amplitude) occurred in the reward-seeking period, in which reward expectation enhanced their occurrence prior to a motor response. The other (with smaller amplitude) occurred in response to reward delivery in the reward-consuming period (Samura, unpublished). These functionally active neurons in the cortex, striatum, and hippocampus may participate in movement controls in the reward-seeking behavior.

Support: Brain/MINDS from AMED, Grants-in-Aid for Scientific Research on Innovative Areas (JP26112005; JP15K21715), and Supported Program for the Strategic Research Foundation at Private Universities from MEXT.

ICCN 2017

30


LEARNING IN A DISH: FROM TIMING-DEPENDENT SYNAPTIC PLASTICITY TO EMERGENT NETWORK DYNAMICS

Invited Speaker: Prof. Dr. Guo-Qiang BiSchool of Life Sciences, University of Science and Technology of China, Hefei, China

Abstract: Being able to learn and to adapt to a changing environment through learning is fundamental for the survival of living organisms. Furthermore, the capacity of learning, to a large extent, defines the successfulness of both biological and artificial intelligence. In the brain, synaptic plasticity, by virtue of its capability of altering the connectivity and thus dynamics of neuronal circuits based on neuronal activity, serves as a cellular substrate of learning and memory. In this talk, I will describe several observations of learning and plasticity made with hippocampal neurons in culture, including the properties of spike-timing-dependent synaptic plasticity, the features of quasi-rhythmic network dynamics with conserved temporal patterns, and the intricate interactions between the two that is reminiscent of Hebb’s cell assembly theory. I propose that what we learn from learning neurons in culture dishes could help us understand learning in brains and design learning devices on chips.

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DYNAMIC VISUAL PROCESSING THROUGH TOP-DOWN INFLUENCES AND PERCEPTUAL LEARNING

Invited Speaker: Prof. Dr. Wu LiState Key laboratory of Cognitive Neuroscience and Learning and IDG/McGovern

Institute For Brain Research, Beijing Normal University, Beijing, China

Abstract: Parsing visual scenes to form coherent percepts involves proper grouping and segmentation of image components. The traditional point of view of image processing in the brain emphasizes a hierarchical order: information about local simple image components such as short line segments is first extracted in early visual cortex, whereas more complex visual features such as global forms are subsequently assembled in higher-order cortical areas by integrating primitive elements. In the primary visual cortex (area V1), response properties of neurons are generally thought to be rather simple and stereotyped, mainly determined by hardwired neural circuitry. In contrast to this simplified bottom-up viewpoint, recent studies in awake behaving monkeys have shown that analyses of visual images depend on complex interactions between V1 and higher-order cortical areas and between stimulus-driven and goal-directed processes. Such interactions dynamically modify neural computations in the cortical loop according to different stimulus context and perceptual tasks. Moreover, repeatedly performing the same perceptual task, and therefore, repetitively invoking top-down influence specific to the task can potentiate the adaptive changes in V1, allowing V1 neurons to convey more task-relevant information for a more efficient readout by higher cortical areas. These findings indicate that even V1, the earliest cortical stage along the hierarchically organized visual pathway, is capable of running different computation algorithms, which are tailored to different perceptual tasks and can be further refined by perceptual training. This could reflect a general adaptive mechanism underlying processing of sensory information.

Support: National Natural Science Foundation of China (31671079, 91432102) and National Basic Research Program of China (973 Program 2014CB846101).

SYMPOSIA

ICCN 2017

34

Symposium S1

NEURODYNAMICS OF COINCIDENCE DETECTION:FROM SYNAPSES TO BEHAVIOR

Organizer: Dr. Miguel A. MerchánINCYL, Salamanca University, Salamanca, Spain

Abstract: The dynamic integration of separate stimuli within a short time window has been referred to as coincident detection. This property of the nervous system is involved in Hebbian learning, binaural localization, amplitude modulated sound coding or visual attention among other neural associative processes. Due to its temporal resolution in the range of milliseconds as well as the proposed mechanisms which underlie detection, it can be considered as one of the most dynamic and intriguing properties of the neurons. In this symposium we will address the state of the art of coincidence detection under molecular, physiological, structural and behavioural points of view.

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35

S1-1

ELECTRIC AND COINCIDENT SYNAPSES IN FASTNEURAL PROCESSES

A. Acebes and A. Ferrús*Cajal Institute, CSIC, Madrid, Spain

Abstract: Time resolution is a remarkable feature of most nervous systems. In some vertebrate auditory systems, binaural sound discrimination can occur below the millisecond range, and in bees associative learning may be established by the association of two stimuli during 1 millisecond exposure. Subcellular structures that could sustain fast integration are poorly known, if at all. Neurons in the Drosophila antennal lobe establish chemical (excitatory and inhibitory) synapses that interconnect sensory, local and projection neurons which are thought to underlie the loosely defined integrative functions during odorant perception. In addition to chemical synapses, however, electrical and peptidergic terminals are well documented in the antennal lobe whose role in olfaction is becoming recognized in recent studies. We have addressed electrical synapses in olfactory perception through the behavioral analysis of the shakingB (shakB) gene of Drosophila which encodes essential components of electrical synapses. Perception profiles have been determined for Ethyl Butirate, Isoamyl acetate and 1-Hexanol in shakB animals. The data show concentration-dependent changes in olfactory indexes which are characteristic for each odorant. Thus, animals deficient in electrical synapses are not anosmic but perception is modified. Ongoing studies aim to dissect the relative contribution of electrical versus chemical synapses in olfaction. In addition, we have analyzed the ultrastructure of the antennal lobe neuropile searching for synapse types in the wild type. From the currently available data, we noted a type of chemical synapse array which we named “coincident synapses or agora”. The array is compatible with a role in the detection of coincident events. Agoras are also found in the ellipsoid body, another integrative center, of Drosophila and Apis which controls decision making for locomotion. We aim to identify the cell types contributing to this particular synapse type in the antennal lobe following the same strategy already in use for the ellipsoid body.

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S1-2

NEURONAL ENCODING OF ERRORS AND SUCCESSFUL DECISIONS IMPROVE FUTURE BEHAVIORAL PERFORMANCE

Carlos Acuña1* and José Luis Pardo-Vázquez2

1Laboratorios de Neurociencia, Facultad de Medicina, Universidad de Santiago de Compostela,15705-Santiago de Compostela, Spain. 2Champalimaud Neuroscience Programme,

Champalimaud Centre for the Unknown, Lisbon, Portugal.

Abstract: It has been shown that neurons from the ventral premotor cortex (PMv) represent in their firing rates different elements of perceptual decisions (Romo et al., 2004; Pardo-Vazquez et al., 2008, 2009; Acuña and Pardo-Vazquez, 2011). One of the most striking findings was that after monkeys have reported a perceptual decision and once the outcome is known, single neurons from the premotor ventral cortex encode the choices, outcomes, and the sensory information on which the choice was based (Pardo-Vazquez et al., 2008, 2009). These results prompted us to suggest that this information is necessary for the evaluation of the decision-making process and that this cortical area could be involved in shaping future behavior. If this indeed is the case, it is expected that the outcomes of previous decisions will modify the activity of these neurons in a following trial. In this work, we have tested this prediction by recording the activity of single neurons from PMv during a visual discrimination task in one monkey and comparing the behavioral and neuronal responses as a function of the correctness of the preceding trial. Behavioral performance was significantly better after incorrect trials; there was an increase in the percentage of correct responses at the expense of the percentage of abortions. Receiver Operating Characteristic (ROC) analysis revealed significant differences between the single neuronal activity in trials preceded by correct and incorrect decisions. These results give strong support to our suggestion that PMv neurons evaluate the decision process and use this information to modify future behavior.

ICCN 2017

37

S1-3

MONAURAL AND BINAURAL COINCIDENCE DETECTIONIN THE AUDITORY SYSTEM

Philip X. JorisLaboratory of Auditory Neurophysiology, University of Leuven, Herestraat 49 box 1021, Leuven, Belgium

Abstract: Being the sense with the fastest receptors, the auditory system is a model system to investigate mechanisms and limits of coincidence detection. The temporal waveform of sounds is encoded in various ways in spike patterns of the auditory nerve. Dimensions that can be distinguished in the sound waveform and its encoding in the nerve, are 1) fine-structure, 2) envelope, and 3) transients. By changing the sound characteristics, these various components are under experimental control, allowing investigation whether and how these temporal aspects influence the output of neurons in the CNS. I will discuss four examples of brainstem neurons whose output is clearly dependent on the temporal patterns set up in the cochlea and auditory nerve. Bushy cells are monaural neurons in the cochlear nucleus that detect coincident patterns in spikes locked to sound fine-structure in the auditory nerve. Octopus cells also reside in the cochlear nucleus and detect coincidences in envelopes and transients across their inputs. Neurons of the medial superior olive (MSO) are binaural neurons that are exquisitely sensitive to coincidences of spike patterns relayed from the left and right sides, which make these cells sensitive to time delays and correlation of the sound waveforms to the two ears. Neurons of the lateral superior olive (LSO) are also binaural but receive excitatory ipsilateral input and inhibitory contralateral input: they behave as anti-coincidence detectors. In all four cases, these neurons and circuits are endowed with membrane, synaptic, and other adaptations to optimize the coincidence process. I will present intracellular data, recently obtained with in vivo patch recordings, which clarify the coincidence process, but also present some puzzles.

ICCN 2017

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S1-4

COINCIDENCE DETECTION AND ABSOLUTE THRESHOLD IN THE AUDITORY BRAINSTEM

Ray MeddisDepartment of Psychology, Essex University, Colchester, U.K. CO4 3SQ

Abstract: In psychophysics, absolute threshold is explained using the concept of a ‘leaky integrator’. However, this is difficult to reconcile with our knowledge of the physiology of the auditory periphery. A computer model is used to explore the potential of coincidence detection neurons to emulate absolute threshold phenomena when two layers of coincidence detection neurons are used. This arrangement is able to distinguish acoustically-driven auditory nerve action potentials from spontaneous activity and identify absolute threshold with a dependence of threshold on signal duration as found in psychophysics.

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Symposium S2

COMPREHENSIVE NEUROPHILOSOPHY – A TRIBUTE TOWALTER J. FREEMAN

Organizer: Dr. Jan LauwereynsKyushu University, Nishi-ku, Fukuoka, Japan

Abstract: The field of cognitive neurodynamics was shaped in large part thanks to the groundbreaking contributions by Walter J. Freeman, rethinking the entire field of neuroscience through emphasis on dynamics, complex systems, and non-representational approaches to the interaction between brain, mind, and the world. In this symposium we honor his legacy by revisiting the core concepts from Freeman’s work, and their enduring validity in developing a critique of neuroscience and philosophy of mind. Themes addressed in this symposium include the mathematics of chaos and self-organization, the framework of predictive coding, the rationalist and intuitive facets of moral development, and the experience of self.

ICCN 2017

40

S2-1

SELF-ORGANIZATION WITH CONSTRAINTS: THE SIGNIFICANCEOF INVARIANT MANIFOLDS

Ichiro TsudaDepartment of Mathematics, School of Science, Hokkaido University,

Kita-10, Nishi-8, Kita-ku, Sapporo, Hokkaido 060-0810, Japan

Abstract: Manifold self-organization phenomena have been found in scientific fields such as physics, chemistry, biology, and even social sciences. These phenomena have attracted attention as typical phenomena emerging in nonlinear and far-from-equilibrium systems. Furthermore, the mechanism for the appearance of self-organization phenomena have been clarified. One finds the development of theory for self-organization, typically in slaving principle by H. Haken and dissipative structures by G. Nicolis and I. Prigogine. Walter Freeman developed a theory for self-organization of neural systems with his outstanding findings about chaotic behaviors in animals brain, based on Haken’s slaving principle. Classifying self-organization phenomena into two categories, one category may consist of order formation at macroscopic scales, which stems from cooperative or competitive interactions of elements of a system concerned. Here, elementary interactions are supposed to occur at microscopic levels such as atomic or molecular levels. On the other hand, the other category may consist of the formation of elementary units at microscopic or mesoscopic levels as subsystems of a total system, which occurs via constraints acting on the system. The latter relates to differentiation such as cell differentiation in embryos and functional differentiation in cortical modules. In this talk, we discuss about the significance of invariant manifolds in the appearance of function in brain activity.

Support: Grant-in-Aid for Scientific Research on Innovative Areas (Nonlinear Neuro-oscillology: Towards Integrative Understanding of Human Nature, KAKENHI Grant Number 15H05878) from the Ministry of Education, Culture, Sports, Science and Technology, Japan.

ICCN 2017

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S2-2

ON THE “DISCONTINUOUS CONTINUITY” OF THE SELF:MEMORY, ATTENTION, AND MINDFUL BREATHING

(FREEMAN ALONG WITH WILLIAM JAMES)

Nobuo KazashiGraduate School of Humanities, Kobe University, Kobe University, Japan

Abstract: In How Brains Make Up Their Minds (2000), Freeman writes: “My conclusion comes to rest on a premise proposed by the psychologist William James in 1879 [in “Are We Automata?”], that consciousness is interactive with brain processes and is neither epiphenomenal nor identical with those processes.” This fundamental premise shared by James and Freeman did not simply mean an agreement in overall scheme, but entailed significant convergence of their orientations in approaching the most central questions such as choice, attention, emotion, and the self, equipped with the clear realization of the importance of “fringe” or “penumbra” of consciousness and the pragmatic nature of “intentionality.” Most emblematically, Freeman states at the outset of the book: “I hope to turn the biology around so that a proper understanding of brain dynamics supports and explains the biological capacity to choose.” As for James, he wrote in his magnum opus, The Principles of Psychology (1890): “Will you or won’t you have it so?” is the most probing question we are ever asked: we are asked it every hour of the day, and about the largest as well as the smallest, the most theoretical as well as the most practical, things. We answer by consents or non-consents and not by words. What wonder that these dumb responses should seem our deepest organs of communication with the nature of things!” The experience of choosing pervades and accentuates human reality. Seen in this light, our sense of genuine reality consists in the sense of “or.” (Cf. Linda. Simon, Genuine Reality: A Life of William James, 1998, and John. J. McDermott, The Drama of Possibility, 2007) And this sense of “or” marks the “continuity of discontinuity” of the human self”; at stake here is what Merleau-Ponty called “synthesis in transition, or the emergent re-formation of experience in the face of competing objects and uncertain possibilities. This paper attempts to reconsider and unfold the significance of the thoughts of Freeman, along with James, on the question of “choosing” especially in relation to the attentive experience of “mindful breathing” as a mode of “discontinuous continuity” involving “unlearning.”

ICCN 2017

42

S2-3

MINDFUL EDUCATION AND THE KYOTO SCHOOL:CONTEMPLATIVE PEDAGOGY, ENACTIVISM,

AND THE PHILOSOPHY OF NOTHINGNESS

Anton Luis SevillaFaculty of Arts and Sciences and Graduate School of Education, Kyushu University, Japan

Abstract: This presentation is a dialogue between eastern philosophy (the Kyoto School of Philosophy) and western cognitive science (particularly psychology and neuroscience) on the topic of education. As a discussion point, I take up contemplative pedagogy/mindful education, which is a movement that attempts to integrate contemplative practices into the process of education. I will examine four points of connection between this movement and the ideas of the Kyoto School. The four points concern the idea of mindfulness itself, the subject-object relationship, well-being, and creativity. To represent the Kyoto School, I will focus on Nishida Kitarô’s idea of pure experience and Nishitani Keiji’s idea of the standpoint of emptiness. Additionally, I will try to bring these ideas into dialogue with the enactivist view of Francisco Varela (who directly cites Nishitani’s philosophy in The Embodied Mind).

Support: Funding from Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research (Project Number: 17K13988).

ICCN 2017

43

S2-4

BEYOND PREDICTION: SELF-ORGANIZATION OF MEANINGWITH THE WORLD AS A CONSTRAINT

Jan LauwereynsKyushu University, Nishi-ku, Fukuoka, Japan

Abstract: In recent years, predictive coding has gained considerable popularity in neuroscience and philosophy of mind as a powerful theoretical approach (e.g., Hohwy, 2013; Clark, 2016). The basic concept of “predictive coding” is that the brain endeavors to minimize prediction errors: it tries to anticipate the current situation so as to reduce the loss of energy required to deal with the unexpected. However, one recurring problem with predictive-coding models is that, in order to minimize prediction errors, the most efficient strategy would be to avoid unpredictable situations as much as possible. Yet, as pointed out several decades ago in a critique of behaviorist models (Berlyne, 1966), curiosity is a very typical and basic characteristic of many animals, particularly also humans: we tend to seek a certain level of new stimulation even if there is no guaranteed material or immediate benefit, sometimes even if there is a considerable risk of adverse outcomes. Moreover, much brain activity is devoted to a type of coding in which the relevant information is fully known and requires no analysis in terms of prediction (e.g., savoring the taste of wine, or ruminating on a negative experience). Humans often spend large amounts of time in such “postdictive” information processing. How can these phenomena be reconciled with the framework of predictive coding? I propose to use the concept of “intrinsic reward” as a key addition to predictive-coding models, where the ultimate goal of prediction is not to minimize error, but to maximize reward. A new model based on predictive coding with intrinsic rewards would explain not only how the typical utilitarian behaviors work, but also how seemingly spurious activities such as reprocessing can be tied to the mechanisms of predictive coding. Essentially, the reprocessing would lead to the self-organization of a richer, intrinsically rewarding experience of meaning, with real-world information as a constraint. This “intensive approach” to information processing would tend toward the expansion of meaning and predictive power by continually trying to “fail better”.

Support: Grant-in-Aid 16H03751 from JSPS.

ICCN 2017

44

Symposium S3

NEURAL ENGINEERING

Organizer: Dr. Laura RoaBiomedical Engineering, Engineering School, Seville, Spain

Abstract: The last years have seen a renewed interest for the advances on neural science and engineering. While the main focus is still based on the diagnosis and treatment of diverse neural disorders including cognitive impairments, the emergence of novel brain-stimulation technologies provides promising pathways to improve cognitive performance. This symposium brings together different experts that can provide a comparative analysis of methods and techniques in the area of neural engineering. The topics range from neuromodulation and neural plasticity to brain-computer interfaces, including advances on neural signal processing and novel approaches to neural stimulation.

ICCN 2017

45

S3-1

TECHNOLOGY-DRIVEN NEUROMODULATION AND NEURAL PLASTICITY: STROKE AND iSCI

José Luis Pons RoviraBiomedical Engineering Group, CSIC, Madrid, Spain

Abstract: Abstract not received

ICCN 2017

46

S3-2

NEUROCOGNITIVE TRAINING BY MEANS OF A MOTOR IMAGERY-BASED BRAIN COMPUTER INTERFACE IN THE ELDERLY

J. Gomez-Pilar, V. Martínez-Cagigal, and R. Hornero*Grupo de Ingeniería Biomédica, Valladolid University, E.T.S.I. Telecomunicación,

Paseo Belén, 15, 47011 - Valladolid, Spain

Abstract: Brain-computer interfaces (BCIs) have become not only a tool to provide communication and control for people with disabilities, but also a way to restore brain plasticity by inducing brain activity by means of neurofeedback training (NFT). In this regard, NFT has shown to be a suitable technique to control one’s own brain activity. We hypothesized that a well-designed NFT with a motor imagery-based BCI (MI-BCI) could enhance cognitive functions related to ageing effects. In this study, a MI-BCI application was developed, designed and assessed to study the potential benefits in elderly people to slow down the effect of ageing. To assess the effectiveness of our MI-BCI application, a total of 63 subjects were recruited by the ‘Centro de Referencia Estatal (CRE) of San Andrés del Rabanedo (León, Spain). All subjects were older than 60 years, healthy, and with similar educational level. None of them had previous BCI experience (BCI-naives). Participants was randomly divided, taking into account age and gender, into a control group (32 subjects) and a NFT group (31 subjects). Our proposed application was only used by the NFT group (31 subjects). NFT effects were studied observing changes in the electroencephalogram (EEG) spectrum during resting by means of relative power (RP) measures, and also by the study of changes in different cognitive functions using the Luria Adult Neuropsychological Diagnosis (Luria-AND) test. Three frequency bands centered on 12, 18, and 21 Hz (bandwidth of 3 Hz) were selected for the training and, then, to assess EEG changes. Significant increases (p<0.01, Wilcoxon signed-rank test) in the RP of these frequency bands were found. Moreover, after performing five NFT session, results from Luria-AND test showed significant improvements (p<0.01, Wilcoxon signed-rank test) in the NFT group in four cognitive functions: visuospatial, oral language, memory, and intellectual. These results further support the association between NFT and the enhancement of cognitive performance, as well as it opens the opportunity of designing new NFT based on motor imagery strategies. Therefore, this novel approach could lead to new means to help elderly people by slowing down the effect of ageing.

Support: Grants TEC2014-53196-R (Ministerio de Economía y Competitividad and FEDER), VA037U16 (Consejería de Educación de Castilla y León).

ICCN 2017

47

S3-3

INTRA-BODY COMMUNICATIONS AS AN EMERGINGAPPROACH TO NEUROMODULATION

J. Reina-Tosina*, L.M. Roa, and A. CallejónBiomedical Engineering, Engineering School, University of Seville, 41092-Seville, Spain

Abstract: The partial conductivity of biological tissues allows the transmission of electromagnetic signals, with the term Intra-body Communication (IBC) recently adopted to refer to the use of skin (or inner tissues) as a physical layer for the communication among on-body (or implanted) sensors. Two coupling alternatives are commonly described for IBC, galvanic and capacitive coupling, with the former involving the injection of an electric current within the tissues through proper electrodes. Current penetrates into the deep tissues and spreads across the body by following appropriate current pathways. The application of galvanic IBC to brain tissues opens new alternatives for the coupling of electromagnetic energy to target areas for brain stimulation and neuromodulation. The lack of knowledge about the electric field distribution under neural IBC stimulation can be alleviated with computational electromagnetic models. In this work, we perform a parametric study of relevant design parameters, such as frequency range or electrode configuration, which is supported by a computational model of the human head. The objective is to obtain electric field and current density distributions and levels that can be compared with other neuromodulation techniques, such as Transcranial Magnetic Stimulation or Transcranial Direct Current Stimulation. The use of realistic computational models becomes a practical tool for the design of IBC stimulators. In this regard, they can provide practical hints about the placement of electrodes to focus a target brain area and show the flexibility of IBC for neuromodulation therapies.

Support: Grants PI15/00306 and DTS15/00195, by Instituto de Salud Carlos III, and INT-2-CARE, NeuroIBC and ALBUMARK, by CIBER-BBN.

ICCN 2017

48

S3-4

INDEPENDENT COMPONENT ANALYSIS IN BRAIN SIGNALS

Christopher J. JamesWarwick Engineering in Biomedicine, University of Warwick, Coventry, CV4 7AL, U.K.

Abstract: Independent Component Analysis (ICA) is a biomedical signal processing technique that has gained in popularity over the years used as a means of extracting meaningful information from a number of measurements made across the body. In Neural Engineering in particular, ICA has provided a very useful means of extracting information about neural sources, or otherwise, from recordings of electromagnetic brain signals (i.e. the electroencephalogram and magnetoencephalogram – EEG and MEG respectively). Inherently ICA is about the separation of statistically independent sources from a set of mixed measurements or recordings – for example in extracting eye-blinks from EEG or identifying ictal activity mixed in with ongoing EEG, etc. The strong assumption of statistical independence of the underlying sources is usually well met in neural engineering cases. The “default” methods of ICA usually work with a number of simultaneously measured channels and these report on a similar number of independent sources. In previous work we have shown, however, that ‘single-channel’ ICA is possible and is in itself a very powerful technique for the extraction of multiple (independent) sources underlying a single channel measurement – a very useful technique in applications that require ambulatory brain signal recordings. Whereas ‘standard’ ICA can be termed as ensemble or ‘spatial’ ICA, single channel ICA can be termed as ‘temporal’ ICA – as there is no spatial information informing the ICA process due to the single channel arrangement. The logical progression for ICA is to perform space-time (or spatio-temporal) ICA, whereby the ICA process is informed by means of both spatial and temporal/spectral information derived from a set of neural signal recordings. We can show that this, so called, space-time ICA results in a powerful algorithm that can extract meaningful information in brain signal recordings across a number of conditions. The technique is not without its issues, and suffers from the same problems standard ICA suffers from; these include issues around the assumptions of linear, noiseless, statistically independent mixing of sources as well as the dilemma of choosing sources of relevance once the ICA process is complete. With space-time ICA the problem is compounded somewhat due to the curse of dimensionality.

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Symposium S4

LEARNING ABOUT LEARNING: DIFFERENT SCIENTIFIC EDGES

Organizer: Dr. Agnès GruartDivision of Neurosciences, Pablo de Olavide University, Seville, Spain

Abstract: Although learning and memory is often approached as a unique concept, many different functional states are probably underlying these complex processes. Multiple learning types could require different circuits activated at very precise times and modulated by changing internal (neural) and external (cues and contexts) states. In this symposium, we plan to present and to discuss about learning strategies and how different methodological and conceptual approaches can help to identify the basic mechanisms that sustain them.

ICCN 2017

50

S4-1

WHEN AND WHERE LEARNING IS TAKING PLACE DURING INSTRUMENTAL LEARNING

I. Fernández-Lamo, R. Sánchez-Campusano, J. M. Delgado-García and A. Gruart*Division of Neurosciences, Pablo de Olavide University, Seville, Spain

Abstract: Although it is generally assumed that brain circuits are modified by new experiences, the question of which changes in synaptic efficacy take place in these circuits across learning remains unanswered. Experiments were carried out in rats trained for the acquisition of an operant conditioning task in a modified Skinner box. Animals were chronically implanted with stimulating and recording electrodes in hippocampal [CA1; CA3; dentate gyrus; subiculum (SUB)], medial prefrontal (mPFC), and subcortical [basolateral amygdala (BLA); nucleus accumbens (NAc); reuniens nucleus (REU)] sites relevant to the task. The evolution in functional efficacy of 14 different synapses was followed across the acquisition of the instrumental task during the performance of seven selected behaviors related or unrelated to the learning process (going to the lever, before pressing the lever, pressing the lever, going to the feeder, eating, exploring, and grooming). Changes in synaptic strength were more noticeable in synapses corresponding to afferent (SUB-mPFC) or efferent (mPFC-NAc, mPFC-REU, and mPFC-BLA) pathways of the mPFC. Those changes were specifically related to the moment of maximum change in the slope of the learning curve, as compared with those taking place before learning and when asymptotic values were reached. Changes in synaptic strength observed in the prefrontal circuits took place not only during the performance of appetitive (going to the lever, before pressing the lever, pressing the lever) and consummatory (going to the feeder, eating) behaviors, but also during the performance of behaviors unrelated to this learning (exploring, grooming). These results indicate a rather general activation of prefrontal circuits during the whole learning sessions, meanwhile hippocampal synapses corresponding to inputs to its intrinsic circuit, and those taking part in this circuit, were not very much involved in the process, with some exceptions. Thus, for each acquired ability carried out by brain circuits, there is a corresponding neural functional map with different synaptic weights characterizing it.

Support: Grants P07-CVI-02487 to J.M.D.-G. and BFU2014-56692-R to J.M.D.-G and to A.G.

ICCN 2017

51

S4-2

NEURONAL CIRCUITS AND MECHANISMS OF FEAR BEHAVIOR

Cyril HerryNeurocentre Magendie, INSERM U1215, Université Bordeaux 146 rue léo Segalen,

33077-Bordeaux, France

Abstract: Over the past years it has become clear that the basolateral amygdala (BLA) and dorsal medial prefrontal cortex (dmPFC) play a key role in fear behavior, yet the precise neuronal circuits and cellular elements involved are still largely unknown. I will present recent data collected using a combination of single unit and local field potential recordings and targeted optogenetic approaches in behaving mice that identify important neuronal circuits involved in the expression, of conditioned fear responses. All together, these results demonstrate that the synchronization of neuronal activity occurring in dedicated BLA and dmPFC neuronal circuits stronglydetermines fear behavior in rodents.

ICCN 2017

52

S4-3

SEROTONIN MODULATION OF THE NEURONAL ACTIVITY AND BRAIN WAVES IN THE PREFRONTAL CORTEX

M. Alemany-González, T. Gener, and M.V. Puig*Hospital del Mar Medical Research Institute,

Barcelona Biomedical Research Park, 08003-Barcelona, Spain

Abstract: Our group aims at understanding the neural substrates of cognitive impairment to find new strategies for cognitive amelioration. To do so, we leverage on mouse models of schizophrenia and Down syndrome, two well-established “cognitive disorders”. We record neural activity in the prefrontal cortex (PFC) and hippocampus (HPC) of freely-moving mice performing operant and non-operant cognitive tasks and evaluate the actions of selective drugs. The main focus of the schizophrenia study is to determine the neural substrates of cognitive preservation by atypical antipsychotic drugs. Specifically, we have investigated the role of the serotonin system (5-HT1AR and 5-HT2AR) in the actions of atypical (clozapine, risperidone) vs. typical (haloperidol) antipsychotics on prefronto-hippocampal (PFC-HPC) neural dynamics. We report that spiking activity, theta (8 Hz) and high gamma (50-80 Hz) oscillations are reduced by acute antipsychotics and the 5-HT1AR agonist 8-OH-DPAT both in PFC and HPC. In addition, clozapine and haloperidol increase delta (4 Hz) and beta (18-25 Hz) oscillations. Interestingly, PFC-HPC neural communication, assessed by several measures of functional connectivity (phase-lag index, phase-locking value), is disrupted by all drugs with the exception of risperidone, that greatly enhances it. Ongoing work evaluates the impact of these compounds in the phencyclidine mouse model of schizophrenia and during memory performance. Trisomic mice (Ts65Dn line), a well-established murine model of Down syndrome and cognitive impairment, show disrupted delta (4 Hz) and theta (8 Hz) oscillations in PFC and HPC. These abnormalities are more evident in brain states with high PFC-HPC demand (e.g., during the novel object recognition task). Importantly, one month of treatment with the cognitive enhancer EGCG, the main compound of green tea, normalizes PFC delta and theta activity. Taken together, our findings suggest that alterations in neural network dynamics between PFC and HPC may underlie cognitive impairment and this can be normalized by selective cognitive enhancers.

Support: NARSAD Young Investigator Award to M.V. Puig.

ICCN 2017

53

S4-4

BRAIN MAPS FOR CHOICE BEHAVIORS

Miguel RemondesInstituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa,

Avenida Professor Egas Moniz . 1649-028 Lisboa, Portugal

Abstract: Cognitive deficits such as Alzheimer’s Disease, Anhedonia, Depression, and Schizophrenia, have been mapped to neuropathological changes in midline cortical (MC) structures, such as the anterior cingulate cortex (ACC), necessary for appropriate decision-making, the retrosplenial cortex (RSC), critically involved in visual-spatial processing, and the hippocampal formation, (entorhinal cortex (EC), subiculum (SUB), and hippocampus (HIPP)), critical for episodic memory and any mental function therein dependent. To understand, and ultimately ameliorate or cure, such disorders, it is imperative that we identify the structures and mechanisms underlying the behaviors they affect. We model such behaviors as the reward-seeking trajectory choices present when rodents learn to negotiate goal-directed tasks of variable complexity. In such tasks, we create a contingency regulating the delivery of a reward after rodents chose a given spatial trajectory, from 2+ available, at a defined point (the choice point, or CP). Current evidence shows that hippocampus (HIPP) and adjacent entorhinal cortex (EC) form a complex circuit whose neurons store a spatial memory engram. Reactivation of such memory engram would allow its use by the “executive” cingulate (ACC) and retrosplenial (RSC) regions (midline cortex, MC), whenever such information is needed for decision-making. Evidence for this model is largely correlative. We do not know the mechanisms converting sensory information to EC-HIPP spatial-maps, neither how MC retrieves and uses memory engrams to support behavior. The findings we now present are the result of joint cutting-edge techniques from multiple disciplines: a) Anatomical tracings in rodent models b) in vivo and in vitro electrophysiology, c) Fine manipulation of neural activity using genetically-encoded neural actuators, and d) Place-dependent, decision-making protocols. We have identified the neural circuitry connecting sensory areas, HIPP and MC, successfully manipulated neural activity in said circuitry, and begun to dissect the mechanisms linking primary sensory input, spatial memory, and decision-making. Ultimately we want to understand how we go from receiving primary sensory inputs, to building an enduring mental map of context, and to decide on the appropriate actions in a changing world.

Support: Foundation for Science and Technology, Portugal, IMM Directory Board

ICCN 2017

54

Symposium S5

CEREBRAL MARKERS OF VULNERABLE AGING: FROM STRUCTURE TO FUNCTION

Organizer: Dr. José L. CanteroLaboratory of Functional Neuroscience, Spanish Network of Excellence for Research onNeurodegenerative Diseases (CIBERNED). Pablo de Olavide University. Seville, Spain

Abstract: A major challenge in aging research is to establish the biological boundaries between normal aging and asymptomatic Alzheimer’s disease (AD), paving the way for therapeutic intervention decades before the neuropathological cascade give rise to irreversible damage in brain circuits. Therefore, searching for reliable biomarkers of vulnerable aging is increasingly important to anticipate accelerated cognitive decline in asymptomatic elderly individuals. In this symposium, we will present results on different aspects of the functional anatomy of the brain affected by aging and additionally related to prodromal stages of AD, using structural and functional neuroimaging techniques.

ICCN 2017

55

S5-1

LOCUS COERULEUS RESTING-STATE FUNCTIONAL CONNECTIVITY TRAJECTORIES OVER THE ADULT LIFESPAN

H.I.L. Jacobs1,2

1School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands

2Department of Radiology, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital / Harvard Medical School, Boston, USA.

Abstract: The locus coeruleus (LC), a tiny nucleus in the brainstem, provides the entire brain of noradrenergic input. Therefore, the integrity of the LC system has an important role modulating cognitive abilities. Neuropathology studies indicated that the LC might be the first location where Alzheimer’s disease pathology occurs, starting already around the age of 20-30 years old. Previously, we have shown differences in functional connectivity between the LC and medial temporal lobe between healthy older individuals and patients with preclinical Alzheimer’s disease, which was relevant for episodic memory functioning. However, it remains unknown how functional connectivity patterns between the LC and other brainstem nuclei or cerebral regions alter during the lifespan. We set out to investigate changes in functional connectivity of the LC during adult life for the first time using ultra-high-field (UHF) resting-state MRI data. Forty-nine individuals (19-74 years old, 29 females, all right-handed) underwent 7T MRI. Functional connectivity analyses were done in the con toolbox for SPM12. Data were band-pass filtered with nuisance regression following the CompCor strategy, including CSF signal surrounding the brainstem and movement outliers. Region-based correlation analyses were calculated between the LC and the target regions (AAL cerebral atlas or brainstem nuclei). Brainstem nuclei were derived from ex-vivo atlases and diffeomorphic registered using ANTs. Non-linear age trajectories of functional connectivity between the LC and other regions-of-interests were modeled using a generalized additive model approach with sex, educational level and intracranial volume (p < 0.05, FDR-corrected). Results showed negative linear functional connectivity trajectories with age between the left and right LC and Ventral tegmental area and positive linear functional connectivity trajectories during age between the left LC and bilateral postcentral gyrus. Non-linear trajectories were observed between the left LC and the left nucleus basalis of Meynert and several frontal, temporal and parietal regions. These non-linear age-trajectories are consistent with previous cerebral studies, suggesting that increases in functional connectivity at younger ages may reflect different neural mechanisms than at older ages (maturation versus compensation/over recruitment). Future work involves replication using our novel 7T LC-sequence during rest and task and including patients with neurodegenerative disorders.

Support: Grant NWO- VENI [451-14-035].

ICCN 2017

56

S5-2

APOE4 STATUS DETERMINES THE IMPACT OF TEMPORAL LOBE DEGENERATION ON MEMORY IN PATIENTS WITH MILD

COGNITIVE IMPAIRMENT

Mercedes Atienza*, Laura Prieto del Val, Daniel Baena, José L. CanteroLaboratory of Functional Neuroscience, Spanish Network of Excellence for Research onNeurodegenerative Diseases (CIBERNED). Pablo de Olavide University. Seville, Spain

Abstract: In mild cognitive impairment (MCI), APOE4 is associated with accelerated memory decline, likely because brain deterioration hampers successful compensation. This hypothesis was tested in twenty-six controls and thirty-four MCI individuals, of which sixteen were APOE4 carriers. Patients showed hippocampal atrophy and cortical thinning and dysfunctional EEG oscillations across fronto-temporal areas. But importantly, APOE4 status was the critical factor in determining the impact of temporal degeneration on memory. Specifically, path analyses revealed that hippocampal atrophy in MCI was directly responsible for memory deterioration in APOE4 carriers, a causal relationship mediated by the serial intervention of three related factors in noncarriers. Temporal cortical thickness (first mediator) accounted for activation of functional networks through synchronized theta activity across temporal regions (second mediator), which, in turn, coordinated memory reactivation through desynchronized alpha/beta activity across sensorimotor areas (third mediator). Results revealed that, contrary to APOE4-carrier patients, noncarriers are successful in compensating for memory as long as the integrity and functionality of the temporal lobe is preserved, a fact primarily dependent on hippocampal degeneration.

Support: Grants from the Spanish Ministry of Economy and Competitiveness (PSI2014-55747-R); the Regional Ministry of Innovation, Science and Enterprise, Junta de Andalucía (P12-CTS-2327), and CIBERNED (CB06/05/1111).

ICCN 2017

57

S5-3

MICROSTRUCTURAL AND BIOCHEMICAL CHANGE MEASUREDWITH MRI: A NEURODEGENERATIVE DISEASE PERSPECTIVE

Julio Acosta CabroneroWellcome Centre for Human Neuroimaging, UCL Institute of Neurology,

University College London, London WC1N 3BG, United Kingdom

Abstract: With the population aging, neurodegenerative diseases, which are exceptionally common in later life, pose an enormous challenge for diagnosis and treatment. The most prevalent neurodegenerative brain disorder is Alzheimer’s disease (AD), which accounts for over 60% of all dementia cases. During the course of the disease, there is progressive neuronal and synaptic loss with abnormal accumulation of neurofibrillary tangles and β-amyloid plaques, putatively causing gradual deterioration of cognition and function though the precise mechanisms by which this occurs remain elusive. Currently there is no cure for AD, although there are a number of therapies in development that are hoped to slow or prevent the dementing process. In this context, considerable efforts are presently being made to identify individuals that are at a high risk of developing AD to take part in clinical trials. Thus, therapeutic developments are in priority need of biomarkers that are sensitive in early disease stages, that can be used repeatedly–hence safely and relatively inexpensively–and that can detect tissue responses over short time periods to monitor treatment outcome. In this regard, magnetic resonance imaging (MRI) is potentially ideal because in contrast to positron emission tomography (PET)— the imaging “gold standard” for in vivo AD diagnosis—multiple types of data can be acquired in one session; it shows great anatomical detail; it is relatively cheap, safe and readily available; and is already standard practice for individuals with cognitive complaints. Although until now MRI’s role in clinical assessment has primarily been to exclude unexpected pathologies such as strokes or tumors, recent technical advances suggest that it is now the ideal time to develop and calibrate MRI methods that have specific diagnostic application rather than, as is the case presently, imaging that is only “consistent with” degenerative disease through group studies.

Support: Core funding from the Wellcome [203147/Z/16/Z].

ICCN 2017

58

S5-4

RELATIONSHIP BETWEEN CHANGES IN SLEEP STRUCTUREAND PERIPHERAL BLOOD MARKERS IN MILD

COGNITIVE IMPAIRMENT

José L. CanteroLaboratory of Functional Neuroscience, Spanish Network of Excellence for Research onNeurodegenerative Diseases (CIBERNED). Pablo de Olavide University. Seville, Spain

Abstract: Evidence suggests that amyloid-beta (Abeta) deposition accompanies sleep deficits in Alzheimer’s disease (AD). However, it remains unknown whether impaired sleep and changes in plasma Abeta levels parallel in amnestic mild cognitive impairment (aMCI) subjects, and whether both markers are further associated with cortical thinning in canonical AD regions. To address these issues, we first evaluated whether plasma Abeta levels are related to changes in sleep physiology and/or cortical thinning in aMCI subjects. Second, we investigated if sleep deficits and/or increased Abeta levels accounted for cortical thinning in aMCI subjects. Overnight polysomnographic (PSG) recordings, cerebral magnetic resonance imaging (MRI), and plasma Abeta levels were obtained from 21 aMCI patients and 21 healthy older (HO) subjects. Sleep stages were scored manually, and cortical thickness was measured using Freesurfer. aMCI, but not HO subjects, showed significant relationship between disrupted slow-wave sleep (SWS) and increased plasma levels of Abeta42. We also found that shortened rapid-eye movement (REM) sleep in aMCI correlated with thinning of the posterior cingulate, precuneus, and postcentral gyrus; whereas higher levels of Abeta40 and Abeta42 accounted for grey matter (GM) loss of posterior cingulate and entorhinal cortex, respectively. These results support the relationship between Abeta and altered sleep physiology previously observed in animal models of AD amyloidosis, and provide precise cortical correlates of these changes in older adults with aMCI.

Support: Spanish Ministry of Economy and Competitiveness (SAF2011-25463); the Regional Ministry of Innovation, Science and Enterprise, Junta de Andalucía (P12-CTS-2327), CIBERNED (CB06/05/1111), and the Spanish Sleep Society (2017).

ICCN 2017

59

Symposium S6

DATA ANALYSIS AND MATHEMATICAL MODELING FOR DYNAMIC BRAIN ― DEDICATED TO WALTER J. FREEMAN

Organizers: Dr. Yutaka Yamaguti1, Dr. Akihiro Yamaguchi1, and Prof. Ichiro Tsuda2

1Fukuoka Institute for Technology, Japan2Hokkaido University, Japan

Abstract: Various kinds of dynamic phenomena such as periodic, quasiperiodic and chaotic oscillations, and further complex transitory dynamics, each of which occurs in both synchronized and desynchronized phases, have been observed in the brain at some spatio-temporal scales. To clarify how such dynamics is generated and how they relate to functions and behaviors, intensive cooperation of researchers with different disciplines is needed. The symposium aims to discuss advances in the fields of mathematical modeling, neurocognitive and behavioral experiments and statistical analyses, concerning the above-mentioned dynamic behaviors in the brain, and possibly to present new perspectives for collaborative studies about the dynamic brain.

ICCN 2017

60

S6-1

FUNCTIONAL SIGNIFICANCE OF NEURAL OSCILLATIONS IN HUMANS

Shozo TobimatsuDepartment of Clinical Neurophysiology, Neurological Institute, Faculty of Medicine,

Graduate School of Medical Science, Kyushu University, Japan

Abstract: Neural oscillations (NOs) are rhythmic or repetitive neural activities in the central nervous system. Neural tissues can generate oscillatory activity in many ways, driven either by mechanisms within individual neurons or by interactions between neurons. At the level of neural ensembles, synchronized activity of large numbers of neurons can give rise to macroscopic oscillations, which can be observed in the EEG. The interaction between neurons can give rise to oscillations at a different frequency than the firing frequency of individual neurons. A well-known example of macroscopic neural oscillations is a activity. I will present several examples of NOs that arise from either feedforward or feedback connections between the neurons that result in the synchronization or desynchronization of their firing patterns. To achieve this, magnetoencephalography (MEG) and transcranial alternating current stimulation (tACS) are useful for assessing the implications of NOs in the sensori-motor systems in humans. Here, three topics are given in this symposium. First, the g-band synchrony is important for the early-stage of human somatosensory processing. The g-band NOs bind the primary (SI) and secondary (SII) somatosensory cortices, and their alterations occur in multiple sclerosis and aging. Second, a -band hypersynchrony between the left and right auditory cortices in stuttering was found. This was probably due to the compensatory mechanism for impaired left auditory processing in stuttering. Finally, online and offline effects of transcranial alternating current stimulation (tACS) on excitability of the primary motor (M1) and visual (V1) cortices were investigated. The M1 and V1 were tuned to the stimulus frequency of tACS in a frequency-dependent manner. The 20 Hz tACS increased the excitability of M1 while the 10 Hz tACS increased the excitability of V1. Taken together, the NOs are important for integrating either the nearby brain areas or the remote brain areas.

Support: Grant-in-Aid for Scientific Research on Innovative Areas MEXT KAKENHI 15H05875.

ICCN 2017

61

S6-2

TBA

Rubin WangEast China University of Science and Technology, China


ICCN 2017

62

S6-3

NETWORK MODEL FOR DYNAMICS OF PERCEPTION WITH RESERVOIR COMPUTING AND PREDICTIVE CODING

Yuichi Katori1,2

1The School of Systems Information Science, Future University Hakodate, 116-2 Kamedanakano-cho, Hakodate, Hokkaido, Japan. 2Institute of Industrial Science, The University of Tokyo, Tokyo, Japan.

Abstract: The sensory information processing in the brain is achieved by mutual interactions between externally given sensory signals and internally generated neural dynamics rather than by a one-directional bottom-up processing. However, the underlying mechanism of the dynamical properties of the sensory processing largely remains to be explored. Here, we propose a neural network model based on the predictive coding and reservoir computing as a model of the dynamical process of perception. The internal network dynamics of the proposed model is trained so that the network reproduces given multi-dimensional time courses of sensory signal and the prediction error is sent to higher order network and is triggering the internal network dynamics. The proposed model may contribute to uncover the mechanism of higher order cognitive function and can be a basis for the application of the neural dynamics for artificial intelligence.

Support: Grant-in-Aid for Scientific Research (C) Grant Number 16K00246.

ICCN 2017

63

S6-4

ANALYSIS OF STRUCTURE-FUNCTION RELATIONSHIP USING A WHOLE-BRAIN DYNAMIC MODEL BASED ON MRI IMAGES

OF THE COMMON MARMOSET

Hiromichi Tsukada1*, Hiroaki Hamada1, Ken Nakae2, Shin Ishii2, Junichi Hata3,4,Hideyuki Okano3,4 and Kenji Doya1

1Okinawa Institute of Science and Technology Graduate University, Okinawa 904-0495, Japan. 2Integrated Systems Biology Laboratory, Graduate School of Informatics, Kyoto University,

Kyoto 606-8501, Japan. 3Laboratory for Marmoset Neural Architecture, Brain ScienceInstitute RIKEN, Saitama 351-0198, Japan. 4Department of Physiology, Keio

University School of Medicine, Tokyo 160-8582, Japan.

Abstract: How brain functions emerge from anatomical networks of the brain is still an open fundamental question. One approach for understanding the structure–function relationship is computational modeling of structural and functional connectivity data from MRI and to explore the behavior of the dynamic model by computer simulation. Here we constructed a whole-brain model based on the structural connectivity between 96 anatomical areas of the marmoset brain estimated from diffusion MRI data. The activation of each area was approximated by a mean-field model, and the connection weights from diffusion MRI were scaled by a global coupling parameter. We investigated the network activity by changing the global coupling parameter and found parameter regions in which the model exhibited mono-stable and multi-stable dynamics. We compared the brain activity simulated by the model based on the diffusion MRI data and the brain activity observed by resting state functional MRI. We found that the correlation between the simulated and empirical functional connectivities had a peak in the multi-stable parameter region. The models with shuffled weights could not produce a comparable correlation, which suggests that the network estimated by diffusion MRI provides relevant information for the functional network. Exploration of how further parameters (e.g. excitation-inhibition balance, scaling of specific connections, and external inputs) impact the structure-function relationship and the analysis of the data from neurological disease model animals would contribute to understanding of the factors behind the disorders and development of new treatments.

Support: Program for Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) from Japan Agency for Medical Research and Development, AMED.

ICCN 2017

64

S6-5

BIAS VERSUS SENSITIVITY IN COGNITIVE PROCESSING:A CRITICAL, BUT OFTEN OVERLOOKED,

ISSUE FOR DATA ANALYSIS

Jan LauwereynsKyushu University, Japan

Abstract: One of the goals of cognitive neuroscience is to characterize the information-processing mechanisms by which individuals respond to sensory or mnemonic data in a variety of contexts. Many theoretical approaches, based on rates of responding and on reaction-time data, have indicated two parallel, independent, but not mutually-exclusive dimensions by which the information processing can be influenced: on the one hand, the quality of information, conceptualized as a signal-to-noise ratio, or the ability to accurately distinguish a target from among distractors, often expressed as a sensitivity measure; on the other hand, the response tendency, referring to the a-priori likelihood of a certain response, often expressed as a bias measure. Although these two dimensions can be readily distinguished in behavioral measures, they are often overlooked in the data analysis of contemporary neurophysiological studies. Through a critical reading of several recent high-profile studies, I demonstrate the pitfalls of this oversight. One recurring problem is that increased target detection in studies of selective attention is sometimes equated with improved performance, implying a superior signal-to-noise ratio, whereas in reality the effects could be due, at least partially, to a change in the a-priori likelihood of response. In worst case, this may lead to the misinterpretation of data, by which effects of selective attention are attributed to sensitivity, while they are actually due to bias. I argue that the careful distinction of bias versus sensitivity is necessary in order to gain a fuller understanding of the neural circuits that underlie cognitive processing. Particularly, bias mechanisms should be well suited for additive, prospective types of coding (e.g., through changes in baseline activity), best supported by (dis)inhibitory circuits, whereas sensitivity mechanisms should be well suited for multiplicative, synergistic types of coding (e.g., through sharpened tuning curves), best supported by synaptic gain modulation. To characterize the types of neural coding properly, it will be necessary to address the dimensions of bias versus sensitivity systematically in the study of cognitive processing.

Support: Grant-in-Aid 16H03751 from JSPS.

ICCN 2017

65

S6-6

A PSEUDO-NEURON DEVICE AND FIRING DYNAMICS OF THEIR NETWORKS SIMILAR TO NEURAL SYNCHRONIZING

PHENOMENA BETWEEN FAR DISTANT FIELDS IN BRAIN

T. Yano1, Y. Goto2, T. Nagaya3, I. Tsuda4, S. Nara1

1Graduate School of Natural Science and Technology, Okayama University. 2Junior College, Beppu University. 3Faculty of Engineering, Oita University. 4Graduate School of Science, Dept. of Mathematics, Hokkaido

University, Sapporo. Japan

Abstract: A pseudo-neuron hardware device called Dynamic Self-Electro-optic Effect Device (DSEED) is proposed and considered. First, the two kinds of neuron-like pulsed oscillations ((i) fast spiking type, (ii) threshold spiking type) are theoretically predicted and their nonlinear oscillation properties are discussed. The case (i) was partly reported in our previous papers (Fig. 1a), so this paper is the first report of the case (ii) (Fig. 1b & 2). Next, firing (pulsing) pattern dynamics of their diffusion coupled DSEED networks of the both spiking types are considered and the computer experiments indicate that there are the three kinds of firing dynamics, (a) transient chaotic firing state, (b) entirely synchronized (coherent) firing state, (c) partly synchronized firing state between far distant fields in the network. The case (a) and (b) were partly reported in ICCN2011 briefly with employing rather less neuron number (400̴900) for simplicity. The new results reported in this paper are, (1) the experiments in larger neuron number case (up to 512X512) that result in the more realistic and new phenomena (Fig. 2), (2) the discovery in the case (c) obtained by the computer experiments is discussed. It shows that the firing patterns are quite similar to neural synchronization phenomena observed in brain (Fig. 3 & 4). So, this device and their networks are, if successfully implemented by hardware, quite useful to verify and develop theories of neural (or coupled nonlinear oscillator) networks to consider or to understand the mechanisms of brain functions.

Support: MEXT KAKENHI Grant Number JP24120707, and Cooperative Research Program of “Network Joint Research Center for Materials and Devices”.

ICCN 2017

66

Symposium S7

THE STATES OF THE BRAIN: A DYNAMIC PUZZLETO CREATE DAILY BEHAVIORS

Organizer: Dr. Juan de los Reyes AguilarGrupo de Neurofisiología Experimental, Unidad de Investigación – Hospital

Nacional de Parapléjicos. SESCAM. Toledo, Spain

Abstract: The brain states are an important feature linked to daily behaviors and the key to properly understand how the brain integrates the sensory information in order to produce responses. Moreover, it has been shown that if an aberrant neural activity takes place in one or more brain structures, alterations of brain states could be produced. At the same time, alterations of brain states could be used as biomarkers for some neurological diseases. This symposium is intended to discuss the relation between neural activity, natural brain states and neurological pathologies from different perspectives: synaptic level, neural population dynamics and the strength of connections between cortical areas.

ICCN 2017

67

S7-1

CORTICAL DYNAMICS IN DIFFERENT CONSCIOUSNESS STATES

María V. Sanchez-Vives1,2

1Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS),08036 Barcelona, Spain. 2ICREA, 08010 Barcelona, Spain.

Abstract: Slow oscillations dominate the activity of the intact cerebral cortex under slow wave sleep and anesthesia, presenting similar characteristics across different cortical areas. The same activity pattern also emerges in the isolated cerebral cortex either in vivo or in vitro. These properties led us to suggest that slow oscillations are the default emergent activity of the cortical network (Sanchez-Vives et al., 2017 Neuron, 94: 993-1001; Sanchez-Vives and Mattia, 2014 Archives Italiennes de Biologie 152: 147-155). Such default activity is a low complexity state that integrates neuronal membrane, synaptic activity and connectivity properties of the cortex. It provides a gauge of the state of the underlying network, being sensitive to variations of parameters such as ionic levels (Sancristobal et al., 2016 Nature Physics, 12: 881-887), temperature (Reig et al., 2010 J Neurophysiol, 103: 1253-61) or excitatory/inhibitory balance (Sanchez-Vives et al., 2010 J Neurophysiol, 104: 1314-24). It also serves the identification of pathological changes, having been used to characterize transgenic models of neurological diseases (Castano-Prat et al., 2017 Frontiers in Aging Neuroscience 9:141; Ruiz-Mejias et al., 2016 Journal of Neuroscience 36: 3648-59). This cortical default activity pattern acts as a powerful attractor leading to a breakdown of cortical connectivity and complexity (D’Andola et al., 2017 Cerebral Cortex, 1-10). Getting out of this attractor is necessary for the brain to recover the levels of functional connectivity (Bettinardi et al., 2015 Neuroimage 114: 185-198) and complexity associated with conscious states (Casali et al., 2013 Science Translational Medicine 5: 198ra105-198ra105) which will be discussed in this talk.

Support: Grants BFU2014-52467-R MINECO and HBP SGA1 (WaveScalES) Contract 720270 by Human Brain Project.

ICCN 2017

68

S7-2

USING PATHWAY-SPECIFIC LPFs TO DISCLOSE THE NEURON POPULATIONS AND NETWORKS INVOLVED

IN BRAIN STATE CHANGES

O. Herreras*, T. Ortuño, D. Torres, and J. MakarovaCajal Institute - CSIC, 28002-Madrid, Spain

Abstract: Virtually all neuron activity flows through several brain nuclei forming functional networks. Such flow is based on sequential activation of varying groups of neurons in each relay and is essentially sparse and population-coded. The study of the local and large-scale networks involved in behavioral/cognitive tasks is severely hampered by technical limitations. Global imaging techniques are excessively static or have limited spatial resolution, while massive unitary studies present local circuit indetermination and hard access to population code. A parameter that reflects the highly dynamic fluctuations of neuron activity is the local field potential (LFP), although it is strongly subjected to several technical and theoretical constraints that have gone too often neglected and led to erroneous interpretation (Herreras, Front. Neural Circuits, 2016). Particularly, the mixture of extracellular currents from multiple co-activating sources makes raw LFPs virtually undecipherable. The only approach to disentangle the contributions by different sources is through defining the precise spatial distribution of the respective voltage shells, which can be approached by spatial discrimination techniques as the independent component analysis (ICA) of multisite LFP recordings (Herreras et al., Neuroscience 2015). While this approach is not particularly useful for recordings made at the skull, it proves highly discriminant in intracerebral recordings. In most cases, the distinct cytoarchitectonic features of anatomical connections make the separated components to faithfully reflect pathway-specific activity. In this way, a simple row of linear recordings provides time-varying activity of multiple pathways that can be readily identified by complementary techniques. Here we extend this approach to several brain regions at a time. We show in anesthetized rodents that a mild distortion imposed in a small region may affect profoundly the activity of local and long range networks in several brain structures. Specifically, moderate disinhibition of the rostral CA3 region of the hippocampus produces changes in the thalamus, cortex and other hippocampal subfields. Pharmacological blockade of different structures indicates that the changes do not follow a unique pathway, but it rather suggests they constitute a so-called brain-state. Strikingly, the changes appear dependent on the electrographic state at the moment of the intervention. We think this approach opens path to quantitative studies of ongoing activity in multiple brain populations and structures.

Support: Grants BFU2013-41533R and SAF2016-80100-R to O.H.

ICCN 2017

69

S7-3

CAUSALITY IN BRAIN DYNAMICS: PITFALLS AND HOPE

Jaime Gómez-RamírezDepartamento de Neuroimagen, Fundación CIEN, CTB-UPM, Madrid, Spain

Abstract: A mechanistic understanding of brain function and malfunction will necessary require to establish a causal theory of the brain. Candidates for global brain theories are not missing e.g. Friston’s Free Energy minimization (Friston, 2010 Nature Reviews Neuroscience 11(2): 127–138), von Malsburg’s correlation theory (Malsburg, 1994 In Models of neural networks. Springer), Abeles cortinomics (Abeles, 1991 Corticonics: Neural Circuits of the Cerebral Cortex. Cambridge University Press), Llinás thalamocortical loop (Llinás and Ribary, 1993 Proc Natl Acad Sci USA, 90(5): 2078–2081), Tononi’s integrated information theory (Marshall et al., 2016 Frontiers in Psychology, 7:926) etc., but the jury is still out on a causal explanation of cognition. Neuroimaging reveals only correlations. Causality can only be investigated through intervention, that is, stimulation or lesion. This poses a tremendous challenge in a nonlinear highly coupled system like the brain. Intervention in one area of the brain can ripple to other parts in very complex and unpredictable ways. In this talk we will make the argument that network models fall short of producing mechanistic models of normal function and disease. Graphs are built by connecting one pair of elements at a time. The limitation of having exclusively dyadic (or bivariate in statistics jargon) relationships is a crucial limitation that is often overlooked (Giusti, 2016 arXiv preprint arXiv:1601.01704). Computational topology allows us to go beyond pairwise connections within an elegant mathematical framework. In particular, the connectomics of the mammalian brain can be studied with persistent homology. Persistent homology is a method of computational topology that studies the persistent structure in data sets. This framework provides a compact encoding multi-scale relations and is agnostic to way the coupling is computed (power-based, phase-based, granger causality, dynamic time waring etc.) We will show using rs-fMRI functional connectivity data, how persistent homology provides new views to understand the interplay between strong and weak connections in the brain connectome.

ICCN 2017

70

S7-4

NEURAL PLASTICITY IS TEMPORALLY AND SPATIALLY HETEROGENEOUS IN THE SOMATOSENSORY CORTEX

AFTER A SPINAL CORD INJURY

Juan de los Reyes AguilarGrupo de Neurofisiología Experimental. Unidad de Investigación - Hospital

Nacional de Parapléjicos. SESCAM. Toledo. Spain.

Abstract: A cortical reorganization has been described in the long-term after spinal cord injury that consists in a functional invasion of neural activity from the intact cortex to the deafferented cortex. It has been proposed that axonal rewiring of cortico-cortical connection occurs in order to compensate the lack of sensory inputs in the deafferented cortex. However, there is not agreement in the field about what are the neural mechanisms that drive the cortical reorganization after a spinal lesion. Our main objective is to determine the main physiological features in neuronal population of the somatosensory cortex that explain the basis of cortical reorganization after a spinal cord injury. We have studied the cortical activity from the immediate moments after spinal cord injury to the long-term using an animal model of complete thoracic section. For that purpose simultaneous extracellular and intracellular recordings were obtained from intact somatosensory cortex (forelimb coordinates) and deafferented cortex (hindlimb coordinates) in order to study the neural dynamics in each cortical locations. We analyzed the spontaneous activity and the evoked responses to peripheral stimulation at different time windows after spinal lesion. Our results demonstrate that a spinal cord injury immediately triggers a state of slow-wave activity in the somatosensory cortex, which indicates a reduced neural excitability (Aguilar et al J. Neurosci. 2010). We found that cortical evoked responses were increased due to a state-dependency, in addition, synaptic inputs magnitude were increased in the intact cortex and deafferented cortex in a state-independent manner (Humanes-Valera et al PLoS One 2013). In the long-term, our results show a temporal heterogeneous neural plasticity that take place in Layer V of somatosensory cortex in animals with chronic spinal cord injury. We found that synaptic properties of pyramidal neurons are different depending on the time from lesion, and that intrinsic excitability of cortical network is increased (Humanes-Valera et al., Cereb Cortex 2016). Our recent data indicates that cortical neural plasticity is spatially heterogeneous because is depending on the cortical layer location. In summary our results provide a new perspective of neural dynamics involved in the somatosensory cortex reorganization after a spinal cord injury.

Support: Grants: SAF2012-40109 and BFU2016-80665-P.

ICCN 2017

71

Symposium S8

TAMAGAWA DYNAMIC BRAIN FORUM – BEYOND NEURAL REPRESENTATION

Organizer: Dr. Yoshikazu IsomuraBrain Science Institute, Tamagawa University, Tokyo, Japan

Abstract: So far, many researchers have electrophysiologically described spike activity changes that are correlated with animal’s cognition and behavior as neural representation. Such an approach was practically powerful enough to determine a specific function of each brain area. However, the neural representation alone never tells us actual dynamics of neuronal interactions in a network of the brain. In this symposium, we will show our physiological and theoretical approaches to explore the cerebrum dynamics beyond the neural representation. The Dynamic Brain Forum is co-sponsored by Tamagawa University (Japan).

ICCN 2017

72

S8-1

A STRUCTURE AND FUNCTION OF HIPPOCAMPAL MEMORY NETWORKS IN CONSOLIDATING SPATIOTEMPORAL CONTEXTS

Hiromichi Tsukada1, Minoru Tsukada2*, and Yoshikazu Isomura2

1Neural Computation Unit, Okinawa Institute of Science and Technology, Okinawa 904-0495, Japan,2Brain Science Institute, Tamagawa University, Machida, Tokyo 194-8610, Japan

Abstract: The memory neural network is organized by attractor structures. The models for associative memory have been proposed so far, which have the basic structure that excitatory neurons are reciprocally connected by recurrent connections (Amari 1972, Hopfield 1982). This structure with an appropriate balance of excitatory-inhibitory (E/I) connection strengths yields pattern completion in associative memory, and imbalance of E/I produces successive retrieval of memory (Tsukada H. 2013). For the possibility of spatiotemporal attractor, physiologically, the magnitude of LTP in hippocampal CA1 depends on spatiotemporal stimuli (Tsukada M. et al. 1994, 1996), and the spatiotemporal learning rule plays important role in the pattern separation and Hebb rule in pattern completion (Tsukada M. & Pan 2005, Pan & Tsukada M 2006). Both rules coexist in the hippocampal CA1 (Tsukada M. et al. 2007). Theoretically, the possibility of Cantor coding (Tsuda 2001, Tsuda & Kuroda 2001, 2004) and the concept of spatiotemporal attractor (Tsukada H. et al. 2015) was reported by using hippocampal CA1 network and experimentally was identified Cantor-like coding in membrane potentials of hippocampal CA1 pyramidal neurons (Fukushima et al. 2007). This study shows the structural and functional mechanisms of spatial clustering and its self-similarity (Cantor-like coding) in hippocampal CA1 networks. The dynamic neural network is defined as a quintuple [X, S, Y, {A(x): x Î X}, F]: Where X is a set of input, S is a set of state, Y is a set of output, A(x) gives the dynamics of the state transition depending on the input. F is a function from S into Y. The structural and functional mechanism require the steps that follow:

1. State space S(t) is modified by the synaptic weight change depending on input pattern X(t) and the spatiotemporal learning rule (STLR, non-Hebb).

2. The outputs of the neurons are calculated by Y(t) = F(S(t)) . The magnitude of weight changes is determined by Hebb learning rule, so that it consolidates the weights related to the output. This is to adjust the weights so that application of a set of inputs produces the subset of output.

3. Self-recurrent inhibition disbranches output space depending Step2 and initialize the weights so that the organized network is not saturated by large values of the weights for next inputs.

Support: Grants-in-Aid for Scientific Research on Innovative Areas (JP26112005; JP15K21715).

ICCN 2017

73

S8-2

INFORMATION CODED IN THE STRIATUM DURINGDECISION MAKING

Makoto Ito1 and Kenji Doya2

1Neural Computation Unit, Okinawa Institute of Science and Technology 1919-1 Tancha, Onna, Kunigami, Okinawa 904-0495. 2PROGRESS TECHNOLOGIES, Inc. 1-1-20 Aomi, Koto-ku, Tokyo 135-0064. Japan

Abstract: The basal ganglia are known to play an essential role in decision making. The striatum, the major input site of the basal ganglia, has a dorsal-ventral gradient in the input modality: the more dorsolateral part receives sensorimotor-related information and the more ventral part receives associative and motivational information. Previous lesion studies have suggested that subareas of the striatum have distinct roles: the dorsolateral striatum (DLS) functions in habitual action, the dorsomedial striatum (DMS) in goal-directed actions, and the ventral striatum (VS) in motivation. However, it is still unclear what kind of roles are assigned to these subareas in the same process of decision making. In this study, we systematically investigated information represented by phasically active neurons in DLS, DMS, and VS during two types of choice tasks: fixed- and free-choice tasks. In both tasks, rats were required to perform nose poking to either the left or right hole after cue-tone presentation. A food pellet was delivered probabilistically depending on the presented cue and the selected action. The reward probability was fixed in fixed-choice task and varied in a block-wise manner in free-choice task. We found the following: (1) When rats began the tasks, a majority of VS neurons increased their firing rates and information regarding task type and state value was most strongly represented in VS; (2) During action selection, information of action and action values was most strongly represented in DMS; and (3) action-command information was strongest in DLS, particularly when the same　choice　was repeated. To explain our results, we proposed a hierarchical-reinforcement-learning hypothesis that VS, DMS, and DLS are hierarchical learning modules in charge of actions at different physical and temporal scales. VS is the coarsest module governing actions of the whole animal, such as aiming for a goal, avoiding a danger, or just taking a rest. DMS is the middle module in charge of abstract actions, such as turn left, turn right, or go straight, by taking into account contextual information. DLS is the module in charge of the finest control of physical actions, such as the control of each limb.

Support: Ministry of Education, Culture, Sports, Science and Technology KAKENHI Grants 23120007 and 26120729, Japan Society for the Promotion of Science KAKENHI Grant 25430017, and Okinawa Institute of Science and Technology Graduate University research support to K.D.

ICCN 2017

74

S8-3

EFFICIENT SIGNAL PROCESSING IN RANDOM NETWORKS THAT GENERATE VARIABILITY: A COMPARISON OF INTERNALLY GENERATED

AND EXTERNALLY INDUCED VARIABILITY

Taro ToyoizumiRIKEN Brain Science Institute, 351-0198, Japan

Abstract: Source of cortical variability and its influence on signal processing remain an open question. We address the latter, by studying two types of balanced random networks of quadratic integrate-and-fire neurons that produce irregular spontaneous activity patterns: (a) a deterministic network with strong synaptic interactions that actively generates variability by chaotic dynamics and (b) a stochastic network that has weak synaptic interactions but receives externally generated noise. These networks of spiking neurons are analytically tractable in the limit of a large network-size and channel-time-constant. Despite the difference in their sources of variability, spontaneous activity patterns of these two models are indistinguishable unless majority of neurons are simultaneously recorded. We characterize the network behavior with dynamic mean field analysis and reveal a single-parameter family that allows interpolation between the two networks, sharing nearly identical spontaneous activity. Despite the close similarity in the spontaneous activity, the two networks exhibit remarkably different sensitivity to external stimuli. The difference between the two networks is further enhanced if input synapses undergo activity-dependent plasticity, producing significant difference in signal to noise ratio. We show that, this difference naturally leads to distinct performance while integrating spatio-temporally distinct signals from multiple sources. Unlike its stochastic counterpart, the deterministic chaotic network activity can serve as a reservoir to perform near optimal Bayesian integration and Monte-Carlo sampling from the posterior distribution. We describe implications of the differences between deterministic and stochastic neural computation on population coding and neural plasticity.

Support: RIKEN Brain Science Institute

ICCN 2017

75

S8-4

THE MULTI-LINC METHOD REVEALS SPIKE DYNAMICSIN CORTICAL PROJECTION NEURONS

Yoshikazu IsomuraBrain Science Institute, Tamagawa University, 6-1-1 Tamagawagakuen, Machida, Tokyo 194-8610, Japan

Abstract: In the motor cortex, two types of deep layer pyramidal cells send their axons to other areas: intra-telencephalic (IT)-type neurons specifically project bilaterally to the cerebral cortex and striatum (telencephalon), but never outside it, whereas the extra-telencephalic (ET)-type, termed conventionally pyramidal tract (PT)-type, neurons project ipsilaterally to the thalamus and other areas, but never to contralateral telencephalon. Although they have totally different synaptic and membrane potential properties in vitro, little is known about the differences between them in ongoing spiking dynamics in vivo. Therefore, we developed a novel multi-neuronal analysis based on optogenetically evoked spike collision along their axons in transgenic rats expressing channelrhodopsin-2 (Multi-Linc method), which enables us to identify axonal target area. Using the Multi-Linc method, we identified IT-type and ET-type neurons, as well as fast-spiking (FS)-type interneurons, in the primary and secondary motor cortices of behaving or resting rats (Saiki et al., Cereb. Cortex 2017). We observed ‘’post-spike suppression’’ (~100 ms) as a characteristic of ET-type neurons in spike auto-correlograms, and it remained constant independent of behavioral conditions (task-performing or resting) in functionally different ET-type neurons. The post-spike suppression followed even solitary spikes, and spike bursts extended its duration. Thus, the Multi-Linc method revealed spiking dynamics in IT-type and ET-type neurons that should be optimized for precise and coordinated motor control. Now we are trying to make this approach more efficient under computer control to elucidate inter-areal spike communication in behaving animals at a single-cell level and with millisecond time resolution.

Support: Brain/MINDS from AMED, Grants-in-Aid for Scientific Research on Innovative Areas (JP26112005; JP15K21715), and Supported Program for the Strategic Research Foundation at Private Universities from MEXT.

ICCN 2017

76

S8-5

INJECTION OF MUSCIMOL INTO PREFRONTAL CORTEXIMPAIRS MONKEY’S REWARD TRANSITIVE INFERENCE

X. C. Pan1, R.B. Wang1, and M. Sakagami2

1Institute for Cognitive Neurodynamics, East China University of Science and Technology, Meilong Road 130, Shanghai 200237, P.R. China. 2Brain Science Institute, Tamagawa

University, Tamagawagakuen 6-1-1, Machida, Tokyo, Japan.

Abstract: It is known that both the prefrontal cortex and striatum are involved in reward processing. In a reward inference task (Pan et al, J. Neurosci., 2014), it was found that neurons in the lateral prefrontal cortex (LPFC) could utilize transitive inference to predict reward value of a stimulus without the requirement to experience the stimulus-reward association directly. While striatal neurons didn’t have such ability, instead, they used exclusive inference or directly experienced stimulus-reward associations to predict reward. On the basis of these results, we hypothesized that inactivation of the LPFC could impair reward predictive ability based on transitive inference, but did not impair the ability based on exclusive inference or associations. To test this hypothesis, muscimol was injected in LPFCs bilaterally while a monkey was performing the reward inference task. Muscimol acts as a potent, selective agonist for the GABAA receptors, alters neuronal activity in its injected location. Two types of reward predicting stimuli were presented in the task. One type was “old stimuli” that the monkey had experienced extensively with different amounts of reward (large vs. small amount of reward). The other type was “new stimuli” that the monkey had never experienced with different amounts of reward. When the old stimuli were presented as a reward predicting cue, the monkey showed significantly higher correct rate in large than small reward trials under both muscimol and saline (control) conditions, indicating the monkey still predicted reward for old stimuli even in the condition of local inactivation of LPFC. In contrast, when the new stimuli were presented at the first time, the monkey showed similar correct rates between large and small reward trials in the muscimol condition, significantly higher correct rate in large reward trials in the saline condition. The behavioral results with muscimol indicated that local inactivation in the LPFC impaired only the reward predictive ability that requires transitive inference, suggesting that the LPFC is an important region to make inference.

Support: Grants National Natural Science Foundation of China (No. 11232005, No. 11472104) and Shanghai Pujiang Program (No. 13PJ1402000).

ICCN 2017

77

Symposium S9

METASTABILITY AND PHASE-TRANSITIONS INNEURAL, MENTAL AND SOCIAL SYSTEMS

Organizer: Dr. Hans Liljeström1,2

1Agora for Biosystems. 2Division of Biometry and Systems Analysis,Department of Energy and Technology, ET/SLU, SE-750 07 Uppsala, Sweden.

Abstract: Brain structures are characterized by their complexity in terms of organization and dynamics. This complexity appears at many different spatial and temporal scales, with resulting transient micro-, meso- and macroscopic dynamical patterns. The high complexity of neural systems is partly a result of the web of non-linear interrelations between levels and parts, with positive and negative feedback loops. This in turn introduces thresholds, lags and discontinuities in the dynamics, which results in instability or metastability, where the system may shift rapidly from one state to another. By studying various kinds of transitions in the brain dynamics, we may be able to reveal fundamental properties of the brain and its constituents, also relating to cognitive and consciousness-related processes and transitions. We explore our world in a perception-action cycle, where our perceptions and actions develop and are refined through interaction with the complex and changing environment, in which we are embedded. The processed-assessed information from our environment, together with our inherited traits, provides a basis for our behaviors, which primarily ensues from a specific cognitive process, decision making. The decision making process can be seen as a transition in a metastable neural system, where the decision made by an individual could shift depending on both internal and external, in particular social context. For humans, social interaction is crucial for our cognitive and conscious capacities. The interactions between individual brains in social contexts may result in emergent phenomena at a super macro level. This symposium is intended to address some of the challenges in relating processes and state transitions at different scales from neural to mental to social systems, in what could be termed psycho-social neurodynamics. Psycho-social neurodynamics adds a new superordinate level where collective phenomena emerge across organisms, which may lead to dynamic multiscale descriptions that will ultimately reinforce the entire field of neurodynamics.

ICCN 2017

78

S9-1

NOISE AS A SOURCE OF FLEXIBLE DECISION MAKING

Hans A. Braun* and A. TchaptchetInstitute of Physiology, Philipps University of Marburg,

Deutschhausstr. 2, D-35037 Marburg, Germany

Abstract: Brains consist of functional elements, the neurons, which, compared to those of electronic devices, are extremely slow, imprecise and noisy. Moreover, neuronal systems, like biological systems in general, are principally nonlinear, include essential time-delays and, therefore, often oscillate or even exhibit chaotic dynamics. By contrast, technical systems are generally constructed with much effort to increase speed and accuracy and especially to avoid the specific characteristics of biological systems. Engineers first of all learn to linearize, to prevent oscillations, to avoid chaos, and to reduce noise. Nevertheless, biological systems are still more flexible and adaptable than technical systems, and it may be speculated that this is not instead but just because of the technically undesirable properties. We will illustrate by experimental data, supplemented by computer simulations, that biological systems preferably operate close to bifurcations where tiny fluctuations, i.e. noise, can decide whether the system goes in the one or other direction, e.g. whether an ion channel is opened or closed or whether an action potential is triggered or not (Tchaptchet et al., 2013 Brain Res 1536: 159-167; see “SimNeuron” at www.virtual-physiology.com). We also will demonstrate that randomness which is introduced at the lowest level of neural function, i.e. the opening and closing of ion channels, is not necessarily smeared out to higher levels of neuronal information processing but can even be amplified due to the typical organization of neuronal systems including not only negative but also positive feedback loops. This can be observed at all functional levels with possible impact on autonomous and mental functions up to conscious decision making. The flexibility from noise induced transitions apparently goes on cost of precision. A computer, for example, is designed to provide exact results - more or less meaningful, eventually just a single number like “42”. Humans’ decisions are often are rather vague and people often remain in doubt of the decision which they finally made. This is probably not only due to the complexity of the world but also may reflect the manifold of choices provided by a brain that can easily be shifted from on state to another by tiniest, even endogenous noise effects.

Support: BM&T (Biomedizin und Technik GbR), Marburg Office (www.BMT-GbR.com).

ICCN 2017

79

S9-2

A NEURO-COGNITIVE MODEL FOR SOCIAL DECISION MAKING

Liljenström, Hans1 and Azadeh Hassannejad Nazir2

1Agora for Biosystems. 2Division of Biometry and Systems Analysis, Departmentof Energy and Technology, ET/SLU, SE-750 07 Uppsala, Sweden.

Abstract: All through history, we have had to struggle with a complex and changing natural and social environment, partly resulting from our own activities. What is the basis for our capacity to change, to adapt and innovate in response to challenges we meet? Which role does our neural flexibility play, and how is it affected by our environmental and social interactions? For an individual, the decision to act may be determined by both internal and external factors, where emotion, as well as cognition comes into play. While emotion and cognition may influence our decisions and actions subconsciously, our conscious mind is expressed through attention and intention. Attention is about how the world is now, and is necessary for an appropriate adaptation. Intention is about what the world could be in the future, which is the basis for innovation. We use computational methods to explore the intricate complexity and interaction of cortical subsystems involved in decision making, in order to elucidate the neural processes associated with our willful acts. We have developed a population model representing the neurodynamics of decision making from perception to behavioral activity. We model the population dynamics of the three neural structures significant in the decision making process, (amygdala, OFC and LPFC), as well as their interaction. In our model, amygdala and OFC represent the neural correlates of emotion, while the neurodynamics of OFC represents the outcome expectancy of alternative choices, and the cognitive aspect of decision making is controlled by LPFC. Our model is intended to give insights on the emotional and cognitive processes involved in decision making under various internal and external contexts. Different options for actions are represented by the oscillatory activity of cell assemblies, which may change due to experience and learning. This is general for any actions, but specifically for those leading to adaptation or innovation. Knowledge and experience of the outcome of our decisions and actions can eventually result in changes in our neural structures, attitudes and behaviors. We will present simulation results that may have implications for how we make decisions for our individual actions, as well as for societal choices.

ICCN 2017

80

S9-3

PSYCHOANALYSIS, COGNITIVE NEUROSCIENCE ANDDYNAMICAL SYSTEMS THEORY

Paul E. RappDepartment of Military and Emergency Medicine Uniformed Services

University of the Health Sciences, Bethesda, MD, USA

Abstract: Increasingly, the results of cognitive psychophysiology are providing support for some, though certainly not all, of the concepts central to psychoanalysis. An important example is research showing the long-term impact of early life experiences on elements of the central nervous system important in emotional processing (particularly the hypothalamic-pituitary-adrenal axis). Further examples are provided by research showing a capacity for nonconscious (implicit) learning and by investigations of the ability of nonconscious stimuli to influence behavior. Experimental results demonstrating the plasticity of memory and the importance of emotional content to memory processes are also consistent with some elements of psychoanalytic thought. It should not, however, be supposed that the relationship between psychophysiology and psychoanalysis is a unidirectional process in which neuroscience comes to the support of psychoanalysis. As with all areas of clinical practice, psychoanalysis is scientifically important because it identifies valuable directions for future experimental research. Dynamical systems theory contributes to this process in two ways. First, it provides dynamical metaphors for psychological processes that can facilitate the conceptual integration of diverse clinical and experimental observations. Additionally, dynamical systems theory provides important signal processing technologies. This review will describe previous work on the analysis of event related potentials (ERPs) obtained in response to putatively subliminal emotionally valenced stimuli. While the results confirm the existence of a cognitive unconscious, they do not necessarily provide evidence of the psychodynamic unconscious that is a central concept of psychoanalysis. Procedures for extending the present investigations to those more demanding questions will be described. The objective of this lecture is to describe some of this work, to identify its limitations, and to suggest directions for future work, and asks. if it is possible to construct a synthesis of psychoanalysis and cognitive psychophysiology in the language of dynamical systems theory. Additionally, we ask if this synthesis can be used to increase the clinical efficacy of psychoanalytically informed psychotherapy.

ICCN 2017

81

S9-4

ON THE NATURE OF COORDINATION IN NATURE

E. Tognoli1*, M. Zhang1, and J. A. S. Kelso1,2

1The Human Brain and Behavior Laboratory, Center for Complex Systems and Brain Sciences, Florida Atlantic University, 33431-Boca Raton, FL, USA. 2Intelligent Systems Research Centre,

University of Ulster, Derry, Northern Ireland.

Abstract: Oftentimes, the mechanisms governing a system are seen as specific to that system and even further, to the particular levels of description that many an investigator favors. With the multitude of descriptions arising from the same system placed under various scientific scrutiny, it becomes difficult to mesh together the phenomenology sampled from different levels and to recognize any generality in the underlying principles. There remain some constants across of all Nature though. All systems evolve in space and time, and all systems have parts that interact with other parts. It ensues that very different parts and processes can be assembled in a single quantitative framework through their Coordination Dynamics. Taking the example of social systems in organisms simpler (e.g. fireflies) or more complex (e.g. humans), the connective fabric of their Coordination Dynamics traverses neural, behavioral and social scales. Rather than approaching those systems with three separate scientific perspectives -neuroscience, psychology and sociology-, we unite them in the study of their coordination dynamics. Here we extend a previous focus on dyads (with its emphasis on temporal behavior) to multiple agents in order to gain a fuller, spatiotemporal perspective. Empirical data from groups of eight humans add support to our earlier findings that such systems are metastable: the coordination of agents exhibit a continuous modulation of integrative and segregative forces/dispositions. This leads to ensembles that vary in size over time and simultaneously, that vary in persistence as a function of their sizes. Interestingly, fireflies, often taken as the poster-child of strong coordination or synchronization, also reveal a mixture of integration and segregation in both space and time. The experimental data are analyzed in the context of a theoretical model of Coordination Dynamics, the extended HKB model of Kelso et al., 1990, and confirm its prediction that a key organizing factor is broken symmetry. This and other work have suggested that neural, behavioral and social scales harbor the telltale signs of dwells (integration) and escape (segregation). We conclude that Nature, in all its diversity and uninterested in subsuming itself to the simpler organizing phenomena such as synchronization, in fact revels in spatiotemporal metastability.

Support: Grant MH080838 from the US National Institute of Mental Health.

ICCN 2017

82

S9-5

AN ERP STUDY REVEALS HOW TRAINING WITH DUALN-BACK TASK AFFECTS RISKY DECISION MAKING

IN A GAMBLING TASK IN ADHD PATIENTS

S.K. Mesrobian1, A. Lintas1,2, M. Jaquerod1, M. Bader3, L. Götte4, and A.E.P. Villa1,2*1NeuroHeuristic Research Group.2LABEX, HEC Lausanne University of Lausanne, Quartier UNIL-

Dorigny, CH-1015 Lausanne, Switzerland. 3Research Unit of the University, Department of Childand Adolescent Psychiatry (SUPEA), CHUV University Hospital and Faculty of Biology and

Medicine, University of Lausanne, CH-1004 Lausanne, Switzerland. 4Institute for AppliedMicroeconomics, University of Bonn, 53113 Bonn, Germany.

Abstract: Impaired decision making is among the characteristic symptoms of patients affected by Attention Deficit/Hyperactivity Disorder (ADHD). This behavioral disorder of childhood and adolescence is characterized by primary deficits of executive functions and clinical symptoms including excessive inattention, hyperactivity and impulsiveness that persist into adulthood in a vast proportion of the diagnosed adolescents. Patients are characterized by Working Memory (WM) impairment and by an abnormal sensitivity to reinforcement that is likely to influence cognitive processes such as decision making through unconscious ‘‘somatic marker signals’’ that arise from bioregulatory processes. We designed a study where participants had to perform a Probabilistic Gambling Task (PGT) in order to investigate whether a WM training can provoke a neural response having an influence on risky decision making. The whole session was composed of 10 games x 16 trials, overall 160 trials. The aim of the present study is therefore to examine the effects of an intensive WM training conducted with the Dual N-back task in a population of young adults with ADHD and match-controls through various measures including EEG recordings. The protocol included a pre-training session in the laboratory, 20 days of WM training at home (an adaptive version of the Dual N-Back consisting of visual and auditory stimuli), and a post-training session in the laboratory. During the sessions at the laboratory all participants performed the PGT while their brain activity was recorded by EEG. During the WM training, half of the participants played the adaptive variant of the Dual N-Back (training group), whereas the other half played the Dual 1-Back for the whole training period (baseline group). We analyzed event-related potentials (ERPs) triggered by the self-paced start of PGT trials. We observed that WM training affected the brain activity during the first 500 ms associated with risk taking decision processes. The N2-P3 wave component was characterized by an amplitude of P3 that was larger in all trained individuals irrespective of the group. In ADHD participants, the frontal sites appeared the most affected, whereas global brain activity was likely to be affected in controls. This study shows the benefits of cognitive training in ADHD patients, but in healthy subjects too, which would provide public health arguments against the current trends of self-administration of drugs and psychoactive substances to boost attention in high-pressure work environments. According to the research results, applications could be developed for target populations, such as cerebral cognitive deficits, addiction to electronic games, and pathological gamblers, using cognitive training on working memory, attentional control, impulsivity and decision making.

Support: Swiss National Science Foundation (Grant CR 1311-138032).

ICCN 2017

83

S9-6

CORTICAL SYNAPTIC DEVELOPMENT AND CONSEQUENCESFOR INFORMATION PROCESSING

James J. WrightDepartment of Psychological Medicine, School of Medicine,

University of Auckland, Auckland, New Zealand

Abstract: Freeman’s pioneering analysis of gamma synchrony did not specify an anatomical framework within which features of coherent objects could be consistently represented, associated, deleted, and manipulated in computations. Recent theoretical work suggests such a framework can emerge during embryogenesis by selection of neuron ensembles and synaptic connections that maximize the magnitude of synchrony while approaching ultra-small-world connectivity. The emergent structures correspond to those of both columnar and non-columnar cortex. With initial connections thus organized, spatio-temporal information in sensory inputs can generate systematic and specific patterns of synchronous oscillation, with consequent synaptic storage. The theoretical assemblies of connections resemble experimentally observed “lego sets”, while facilitation and interference among synchronous patterns, particularly when executed by fast synapses under metabolic entanglement, imply powerful parallel computation.

ICCN 2017

84

S9-7

THE CEMENT OF OUR UNIVERSE – WHY CAUSALITYDESERVES THE WHOLE BRAIN

K.C. Wende and A. JansenLaboratory for Multimodal Neuroimaging, Philipps University of Marburg,

Rudolf-Bultmann-Str.8, 35039 Marburg, Germany

Abstract: In the physical world, the relation between cause and effect is the most fundamental one. It is also a crucial aspect in biological systems. Particularly in the human brain, cause-effect links exist on multiple levels of processing, and also there are many different types of causal interactions and processes, from connections between neurons to directional interlinks between networks. But surprisingly little is known on the neural mechanisms for representing causality itself. The best example for this is the famous “launching” stimulus introduced by Albert Michotte (Michotte, A.E., 1946/1963. La Perception de la Causalite. Institut Superieur de Philosophie, Louvain): If we see an object moving towards and coming into contact with another that subsequently starts to move, we see a collision, or launch event. Regarding the neuronal basis of this universally human experience, especially the distinction of top-down and/or bottom-up processes remains unclear. First, we introduce the existing psychological theories that can be sorted into two main research backgrounds: Whereas “Gestalt”-oriented schools favor bottom-up causal “perception”, learning-theoretical schools of cognitive psychology rather assume implicit inference from causal models, i.e. top-down mechanisms, and additionally, an explicit abstract-semantic concept of causality has been proposed in linguistic fields. In neuroimaging experiments, a variety of stimuli, tasks and control tasks involve causal relations, but only few so far used the launching paradigm. Second, we summarize the behavioral findings and review the neuroimaging literature on brain mechanisms for perceptual launch-effect and cognitive causal attributions. Based on own psychophysical evidence, we suggest interacting processes for Gestalt-perception and Bayesian inference of causality, and an experimental design to firstly isolate the “bottom-up” processes: specifically, by combining temporal high-resolution (eye tracking) with spatial high-resolution (functional MR-imaging) measures, using a novel developed variant of the Michotte “launching”-paradigm that features two simultaneously launched targets (Wende, K.C., Theunissen, L., Missal, M., 2015. Anticipation of physical causality guides eye movements. Journal of Eye Movement Research 9, 1-9). Third, with appeal to physical / metaphysical and neurobiological models of causality and perception, we propose a theory on distinct neural processing systems (the “Qualia-set”, QS-theory) that in concertation establish causal links in the whole human brain.

ICCN 2017

85

Symposium S10

ANALYSIS OF ELECTROPHYSIOLOGICAL SIGNALSIN BRAIN DYNAMICS

Organizers: Dr. Toshishisa Tanaka1 and Dr. Jianting Cao2

1Tokyo University of Agriculture and Technology, Japan2Saitama Institute of Technology, Japan


ICCN 2017

86

S10-1

FUNCTIONAL CONNECTIVITY OF THE RATDEFAULT MODE NETWORK

Daqing Guo*, Wei Jing, Yan Cui, Yang Xia, Dezhong YaoKey Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, University

of Electronic Science and Technology of China, Chengdu 610054, China

Abstract: The default mode network (DMN) is a set of distributed human brain regions that are characterized by their reduced activities during attention-demanding tasks. Recently, a similar network has also been demonstrated in rodents, which offers a preclinical model to elucidate these physiological and pathophysiological determinants. However, almost all of the rodent DMN studies have been based on functional MRI (fMRI), and the neuronal mechanism underlying rodent DMN remains poorly understood. Here, we collected electrophysiological data of the rat DMN across three different vigilance states, including wakeful rest (WR), slow-wave sleep (SWS), and rapid-eye-movement sleep (REMS). Phase locking value (PLV) and directed phase transfer entropy (dPTE) were applied to the time series to estimate the functional connectivity of the rat DMN in undirectional and directional way, respectively. We found that the electrophysiological DMN estimated by PLV is similar to that in fMRI studies, showing similar hierarchical and modular structure. Moreover, in the analysis of directional interactions, we observed well-organized anterior-to-posterior patterns of information flow in the delta band, while opposite patterns of posterior-to-anterior flow were found in the theta band. These frequency-specific opposite patterns were only observed in WR and REMS. Additionally, most of the information senders in the delta band were also the receivers in the theta band, and vice versa. These frequency-dependent reentry loop of anterior-posterior information flow within rat DMN that may offer a mechanism for functional integration, supporting conscious awareness. Overall, these findings complement the electrophysiological evidence of rat DMN, and the might also provide some novel insights into the functional integration across vigilance states.

Support: National Natural Science Foundation of China (Grant Nos. 81571770, 61527815, 81371636, and 81330032).

ICCN 2017

87

S10-2

A NEW PARADIGM BASED ON DYNAMIC VISUALSTIMULATION IN BCI

Zhaoyang Qiu, Jing Jin, Hanhan Zhang, Yu Zhang, Xingyu WangKey Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry

of Education, East China University of Science and Technology, Shanghai, China

Abstract: Background: Brain-computer interface (BCI) provided a new communication channel based on the brain activities of the disabled patients, which can translate the brain signals into computer commands for speller system, prosthesis or wheelchair. Visual based P300 BCI is one of the most common used BCI system. Usually, the stimulus used in visual based P300 BCI was the same character or picture, which could make users feel bored or lose attention. Hence, it would be very helpful in improving the performance of visual-based P300 BCI by concentrating users’ attention on the target stimulus. Method: In this study, a new paradigm using dynamic visual stimulation was presented to focus users’ attention. Three red dots in a honeycomb shaped picture would shrink to the centre of the honeycomb picture dynamically, and was finally merged in the centre position as one red dot, which was used as stimulus to evoke event-related potentials (ERPs). Six healthy subjects (3 male, aged 24±2.4) participated in this study. They were asked to focus their attention on the red dots presented in each flash. To verify the performance of this new paradigm, the face stimulus paradigm was used for comparison. Main results: The results showed that the dynamic honeycomb shaped paradigm obtained 5.0% higher average offline single trial accuracies and 2.8% higher average online accuracies compared to the face paradigm. According to the reports from subjects, the new paradigm could help to concentrate their attention. Conclusions: The proposed new paradigm could help concentrate subjects’ attention in visual tasks. The classification accuracy could be increased by this new paradigm.

Support: Grant National Natural Science Foundation of China, under Grant Nos. 91420302, 61573142. This work was also supported by the Fundamental Research Funds for the Central Universities WH1516018, Shanghai Chenguang Program under Grant 14CG3 and Shanghai Natural Science Foundation under Grant 16ZR1407500.

ICCN 2017

88

S10-3

ALPHA PHASE IS REGULATED BY GAMMA POWERIN MOUSE HIPPOCAMPUS

Tao Zhang1, Xiaxia Xu1, Zhuo Yang2

1College of Life Sciences and 2College of Medicine, Nankai University, Tianjin 300071, China

Abstract: In our previous studies (Xu, Zheng, and Zhang, Front Comput Neurosci., 2013; Xu, Liu, Li and Tao, Brain Topography, 2015; Xu, Zheng, An, Wang, and Zhang, Brain Topography, 2016), the algorithm of conditional mutual information (CMI) was employed in measuring the directional cross frequency phase-amplitude coupling (PAC) in either the hippocampal CA3-CA1 pathway or the hippocampal CA1-mPFC pathway. However, the effect of CMI on detecting the direction between two different oscillations hasn’t been justified. In this study, the PAC_CMI algorithm was validated by simulated data. Afterwards, it was used to analyze local field potentials (LFPs), obtained from mouse’s hippocampal DG region under anesthesia. Male mice were divided into two groups: enrich environment (EE, n=6) and society isolation (SI, n=6). Modulation index (MI) was used to detect the PAC. It shows that there is a significant PAC between alpha and gamma rhythms in the hippocampal DG region in either the EE group or the SI group. However, the value of MI was significantly bigger in the EE group than that the in SI group. Meanwhile, the investigation on stimulation data showed that PAC_CMI worked reliably. Moreover, PAC_CMI results from experimental data showed that the gamma rhythm directionally drove the alpha rhythm in both the mice groups. Additionally, the statistical results showed that the strength of directional driving was consideranly higher in the EE group than that in the SI group. The data suggest that the above directional driving is presumably associated with certain cognitive functions.

Support: Grants NSFC-11232005 and 31171053 to TZ.

ICCN 2017

89

S10-4

NOTCH1 SIGNALING PATHWAY IS INVOLVED IN THE VOLUNTARY RUNNING-INDUCED HIPPOCAMPAL NEUROGENESIS AND

ANTIDEPRESSANT EFFECTS OF C57BL/6J MICE

Xiaochen Zhang, Zhuo Yang*College of Medicine, State Key Laboratory of Medicinal Chemical Biology,

Nankai University, Tianjin 300071, China

Abstract: Several studies have showed that voluntary exercise may affect emotional behaviors in rodents. And hippocampal neurogenesis has great connection with this process. In this study, we investigated if the antidepressant effects and adult neurogenesis induced by voluntary running were associated with Notch1 signaling pathway. Besides, the effects of Notch1 deficiency to mouse depression-like behaviors and neurogenesis were also studied. Here, we showed that Notch1 signaling pathway was activated by voluntary running in WT mice but not in Notch1+/- mice. Results of forced swim test (FST), tail suspension test (TST) and sucrose preference test (SPT) showed that the depression-like behaviors were decreased in WT group than that in Notch1+/- group. Running reduced the depression-like behaviors in WT mice but not in Notch1+/- mice. The results of neurogenesis marker, Ki67 and DCX, showed that both the proliferation and mature processes of DG cells were influenced by Notch1 knockdown. Running could promote adult neurogenesis in WT mice but not Notch1+/- mice. These results suggest that the antidepressant effects and neurogenesis induced by voluntary running are mediated partly by Notch1 signaling pathway. It suggests that Notch1 signaling pathway may have some key targets in the therapy of depression.

ICCN 2017

90

S10-5

TRIAL-TO-TRIAL LATENCY VARIABILITY OF SOMATOSENSORY EVOKED POTENTIAL AS AN INDICATION OF

SPINAL CORD DEMYELINATION

Hongyan Cui1, Guangsheng Li2,3, Jiangbo Pu1, Cheng Kang3, and Hu Yong1,2,3

1Institue of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin. P.R.China. 2Spinal Division, Department of Orthopedics, Affiliated Hospital of

Guangdong Medical University, Guangdong, P.R. China. 3Department of Orthopedics andTraumatology, The University of Hong Kong, Hong Kong. P.R.China.

Abstract: Single trial extraction of somatosensory evoked potentials (SEP) provided a new measurement of trial-to-trial SEP latency variability (TT-SEP-LV), which could evaluate neurodynamic status of somatosensory pathway. The objective of this study was to verify changes of TT-SEP-LV during the progress of demyelination in a compressive spinal cord injury (SCI) model. Fifteen rats were distributed into three groups. SEP were measured in all rats. The severity of demyelination was evaluated by histological examination with Luxol fast blue (LFB) staining. Higher TT-SEP-LV was measured in SCI (22.4±0.99 in 2 weeks after injury and 26.2±0.65 in 4 weeks after injury) than that in intact spinal cord (15.7±0.86). Changes in TT-SEP-LV were well correlated with the severity of demyelination measured by histology (r = -0.90 and r = -0.95). It suggested that TT-SEP-LV would be an indication of spinal cord demyelination.

Support: National Natural Science Foundation of China (81572193) and CAMS Initiative for Innovative Medicine (CAMS-I2M).

ICCN 2017

91

S10-6

MOVEMENT-RELATED CORTICAL POTENTIAL IN SACCADICEYE MOVEMENTS WITH CUED-MOVEMENT TASK

Arao Funase1,2*, Yusuke Fukushima1, Ichi Takumi1

1Nagoya Institute of Technology, 2RIKEN, Japan

Abstract: Our final purpose is to obtain knowledge of brain functions related to decision-making. In this study, we focus on the EEG signals related to saccadic eye movements and we detect the difference between the EEG signals in the cued-movement task and the EEG signals in non-movements task. In our experiments, we use two cues. A go-cue are generated for showing start timing of subject’s movement. A direction-cue is shown before the go-cue is represented. The direction-cue indicated direction of eye movements. In the movement task, subjects move their eyes to a right- or a left-target when the go-cue are represented. In the non-movement task, subjects do not move their eyes when the go-cue are represented. We recorded EEG signals during the movement task and the non-movement task. As results, we obtain two EEG’s features in the movement task and the non-movement task. However, the one feature has difference between the feature in movement task and the feature in non-movement task. These features are recorded on the P3 and P4 electrodes.

ICCN 2017

92

S10-7

SIMULTANEOUS OBSERVATION AND IMAGERY OF HAND MOVEMENT ENHANCE EVENT-RELATED

DESYNCHRONIZATION OF STROKE PATIENTS

Atsuhiro Ichidi1, Yuka Hanafusa2, Tatsunori Itakura1, Toshishisa Tanaka1*1Tokyo University of Agriculture and Technology, Japan

2Division of Rehabilitation, Okayama East Neurosurgery Hospital, Okayama, Japan

Abstract: During voluntary movement, motor imagery (MI), or action observation (AO), the short-lasting attenuation or blocking of rhythms within alpha or beta band of electroencephalogram (EEG) called event- related desynchronization (ERD) is observed over the central area. Some studies showed that with the increase of the ERD during MI, impaired motor function after stroke was improved. Recently, it has been reported that the ERD of healthy subjects during combined AO and MI (AO+MI) was stronger than that during either MI or AO individually. However, it is unclear how AO+MI affects stroke patients in terms of the ERD. To investigate this, in this paper, EEG signals during the three tasks, gazing at a still picture (termed Gaze), MI, and AO+MI, of stroke patients and healthy subjects were analyzed. Statistical analyses showed that the ERD of AO+MI was stronger than that of Gaze or MI. This implies that AO+MI may be more effective approach to recover the motor function in terms of neurorehabilitation.

Support: Project for Next-Generation Research, Tokyo University of Agriculture and Technology.

ICCN 2017

93

S10-8

ASYNCHRONOUS STIMULATION METHOD FOR N100-P300 SPELLER

N. Morita and Y. WashizawaDept. of Communication Engineering and Informatics, The University of

Electro-Communications, Tokyo, Japan.

Abstract: Brain computer interface (BCI) allows people to send commands to computer, and communicate with outside world without any physical activities. In Electroencephalography (EEG)-based spelling BCI system, the performance of accuracy and information transfer rate (ITR) are important indicators. Higher accuracy gives the user comfortable input environment, and higher ITR means that the required input time is short, thus it can reduce the burden of the user. N100-P300 Speller is a spelling BCI system that uses nine visual stimulation images having six positions (2x3 matrix), and each image has four commands and two blanks. To detect the target command, this system utilizes two kinds of event related potential (ERP), N100 and P300; N100 is used to detect which position the user did gaze on, and P300 is done to detect when the target command was presented. This spelling system achieved higher accuracy and ITR compared with P300 Sp eller. However, N100-P300 Speller requires flashing nine images to input one command. For this reason, it is unable to enhance ITR without reducing the flashing intervals. The present study aims to improve ITR by an asynchronous stimulation method in N100-P300 Speller. In the conventional N100-P300 Speller, four commands are simultaneously presented, and two positions are turned off at the same time. In this study, to shorten the duration of flashing commands off, we desynchronize the duration of flashing commands on and off; we assign the flashing pattern of the commands in each position of visual stimulation. The result of our experiments showed that ITR in the proposed method increased 0.24bit/sec at an average compared with the conventional N100-P300 speller. This showed that the proposed N100-P300 Speller reduces the input time and improves ITR, hence it achieved faster spelling system with lower burden for the user. By shortening input time while the accuracy does not decline greatly, it is expected to realize more rapid and lower burden spelling system.

ICCN 2017

94

S10-9

NEURODYNAMICS ON UP AND DOWN TRANSITIONS OF MEMBRANE POTENTIAL: FROM SINGLE NEURON TO NETWORK

Xuying Xu1, Rubin Wang1, Jianting Cao2,3*1Institute for Cognitive Neurodynamics, East China University of Science and Technology,

Shanghai, P.R.China. 2Saitama Institute of Technology, Fukaya, Japan 3Brain Science Institute, RIKEN, Wako, Japan

Abstract: The phenomenon of up and down transition is an important characteristic of spontaneous brain activity, which happens in various levels of nervous system. In level of membrane potentials, it shows spontaneous periodic transitions between two sub-threshold preferred stable states. Here, we have studied the mechanisms and characteristics of up and down transitions of membrane potentials from single neuron to network model. Further more, we have developed the model by considering both excitatory and inhibitory neurons and introducing synaptic dynamics into network model. Based on this model, we studied the influence of intrinsic characteristics and network parameters on up and down activities. The main output of this study is that the network parameters have little impact on these spontaneous periodic up and down transitions. However, the intrinsic currents were found to play a leading role in the process. In this regard, we expect to explain the dynamics of up and down transitions and to lay the foundation for future work on the role of these transitions in cortex activity.

Support: National Natural Science Foundation of China (No. 11232005) and the Fundamental Research Funds for the Central Universities (No. 222201714020).

ICCN 2017

95

Symposium S11

COGNITIVE DYNAMICS OF LARGE-SCALE BRAIN CIRCUITS- A TRIBUTE TO WALTER J. FREEMAN

Organizers: Dr. Steven L. Bressler1 and Dr. Raudel Sánchez-Campusano2

1Center for Complex Systems and Brain Sciences; and Department ofPsychology, Florida Atlantic University, Boca Raton, FL. 33431, USA.

2Division of Neurosciences, Pablo de Olavide University, Seville, Spain.

Abstract: Cognitive function is thought to emerge from the coordination of brain areas in large-scale brain circuits, and cognitive dysfunction may result from their dyscoordination. The large-scale network dynamics perspective has therefore taken on special importance in modern cognitive neuroscience, neuropsychology, and neuropsychiatry. A crucial focus in the study of large-scale brain circuits is the view of cognitive dynamics as a reflection of brain network function. This focus treats brain areas as network nodes and inter-areal functional relations as network edges. It seeks to answer basic questions about how the functional interdependency of brain areas relates to cognition. Current research in this field deals with topics concerning distributed neuronal population activity and its relation to cognitive functions such as perception, decision-making, learning and long-term memory consolidation, working memory, and top-down attention. The speakers in this symposium will address issues relating to the cognitive dynamics of large-scale brain circuits that they have encountered in their own research.

ICCN 2017

96

S11-1

WHOLE-BRAIN MODELS: IDENTIFYING BRAIN STATES

Gustavo DecoCenter for Brain and Cognition. Theoretical and Computational Group.Universitat Pompeu Fabra (UPF) / ICREA. Barcelona. Department of

Information and Technologies, UPF, Barcelona, Spain

Abstract: Human neuroimaging has found that wakefulness and sleep involve very different activity patterns. Yet, it is not clear to what extent brain states differ in their dynamical complexity, i.e. in the level of integration and segregation across brain networks over time. Here, we introduce a novel measure, the Perturbative Integration Latency Index (PILI), to characterize brain states by their recovery after a strong long-lasting perturbation applied off-line. The method works by first adjusting a whole-brain computational model to the basal dynamics of wakefulness and deep sleep recorded with fMRI. Then, the model is perturbed using two distinct multifocal protocols either promoting or disrupting synchronization in randomly selected brain areas. Once perturbation is halted, we evaluate the recovery back to baseline using the PILI. We find a clear distinction between sleep and wakefulness in two independent human sleep datasets, consistently showing larger PILI in wakefulness than in deep sleep. This novel approach opens up for a new level of artificial perturbative studies unconstrained by ethical limitations allowing for a deeper investigation of the dynamical properties of different brain states.

ICCN 2017

97

S11-2

ANTICIPATORY TOP-DOWN INTER-AREAL CORTICAL COUPLING

Steven L. BresslerCenter for Complex Systems and Brain Sciences; and Department of Psychology,

Florida Atlantic University, Boca Raton, FL. 33431, USA

Abstract: Engagement in a cognitive task typically involves configuration of the mental resources needed to perform the task, and switching from one task to another involves the reconfiguration of those resources. It is believed that this configuration and reconfiguration require the preFrontal Cortex of the brain to facilitate the activation of distributed brain areas that will be involved in task execution, and defacilitate others. Although facilitation and defacilitation may occur during task execution, I consider here that they may also be initiated in advance of, and as preparation for, task execution. This point of view comes from a large-scale, distributed neurocognitive network understanding of brain function that emphasizes processes of task preparation and expectation (or task-set) in the brain in addition to processes of perception and action. In short, it requires that a distinction be made between task configuration processes and task execution processes. This paper presents and discusses some convergent lines of evidence suggesting that the preFrontal Cortex exerts top-down configuration of sensory and motor brain areas to construct task set, that this configuration depends on top-down brain processes in the beta-frequency range, and that resource configuration may occur when the brain is at rest prior to task execution.

ICCN 2017

98

S11-3

DYNAMICAL PATTERNS OF BRAIN NETWORKS AS NEURONAL CORRELATES OF AESTHETIC APPRECIATION

Juan García-Prieto 1,2 and Ernesto Pereda1*1Electrical Engineering and Bioengineering Group. Department of Industrial Engineering,

University of La Laguna. 2Laboratory of Cognitive and Computational NeuroscienceUCM-UPM. Center for Biomedical Technology (CBT), Madrid. Spain.

Abstract: The aesthetic judgment, which can be understood as the appreciation of beauty and its distinction from non-beautiful objects, is arguably one of the most humanly higher cognitive functions. The decisions about whether a perceived stimulus is beautiful is usually taken in a fraction of a second and involves different brain circuits composed of many cortical and subcortical areas, which dynamically interact to produce the aesthetic judgment. In this work, we analyze the dynamics of functional connectivity of magnetoencephalography (MEG) of brain signals at the sub-second scale during the processing of visual stimuli (pictures). We also investigate both the brain circuits involved as well as the differences that characterizes the categorization of such stimuli as either beautiful or non-beautiful, including mainly frontal brain areas but also other regions related to the reward system. We will show that, by using time resolved functional connectivity indices, it is possible to track the spatiotemporal dynamics of this higher cognitive function, a framework that can be translated to other cognitive paradigms in which the understanding of the dynamics of brain circuits is important.

ICCN 2017

99

S11-4

LARGE-SCALE DYNAMICS OF FREQUENCY-SPECIFICCORTICAL INTERACTION MAPS

J. Vezoli1*, A. M. Bastos2, C. M. Lewis1, C. A. Bosman3,4, H. Kennedy5, and P. Fries1

1Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Deutschordenstraße. 46, 60528 Frankfurt, Germany. 2Picower Institute for Learning andMemory, MIT, Cambridge, MA, 02139, USA. 3Donders Institute for Brain, Cognitionand Behaviour, Radboud University Nijmegen, Kapittelweg 29, 6535 EN Nijmegen,

Netherlands. 4Swammerdam Institute for Life Sciences, Center for Neuroscience,Faculty of Science, University of Amsterdam, Sciencepark 904-1098 XH Amsterdam.5Inserm U1028, Stem Cell and Brain Research Institute, 18 avenue du Doyen Lépine,69500 Bron, France; Université de Lyon, Lyon1, UMR-S 846, 69003 Lyon, France.

Abstract: Higher-order cognitive functions require an integration of top-down and bottom-up information that is thought to be conveyed through anatomical feedback and feedforward connections, respectively. In order to effectively integrate its different inputs, a given area must be able to identify what information is top-down vs. bottom-up. This might be achieved anatomically, since feedforward and feedback connections have different source and termination layers (Markov, Vezoli et al., J. Comp. Neurol. 2014). However, strong inter-laminar connectivity implies that these signals could quickly become locally intermixed. We recently described a putative mechanism for the cortex to functionally integrate bottom-up and top-down inputs (Bastos, Vezoli, Bosman et al., Neuron 2015; Michalareas et al., Neuron 2016) based on frequency specific inter-areal synchronizations. The finding that feedforward or bottom-up information is conveyed through gamma-frequency synchronization and feedback or top-down through beta-frequency synchronization is coherent with previous findings (Bressler et al. Stat. Med. 2007; Van Kerkoerle et al. PNAS 2014). However, the topography and dynamics of these frequency-specific networks has not been studied systematically. I will present work-in-progress exploring these different band-limited networks for their topographic properties. When the beta and gamma networks were investigated separately, this revealed distinct topographical differences. Consistent with the recent insight that gamma (beta) predominates in feedforward (feedback) signaling, we found the gamma network to be strongest among early visual areas, and the beta network among fronto-parietal areas. This is likely related to laminar differences in the origin of the respective anatomical projections. Finally I will present dynamics of these networks through different periods of the task engaging varying levels of cognitive processing.

ICCN 2017

100

S11-5

FUNCTIONAL STATES OF CORTICAL-SUBCORTICALNETWORK NODES

R. Sánchez-Campusano1,2*, I. Fernández-Lamo1, J. M. Delgado-García1,A. Gruart1, and S.L. Bressler2

1Division of Neurosciences, Pablo de Olavide University, Seville-41013, Spain2Center for Complex Systems and Brain Sciences; Department of Psychology,

Florida Atlantic University, Boca Raton, FL. 33431, USA.

Abstract: Although studies on brain networks and their relation to cognitive functions have been predominantly performed from human neuroimaging, networks can be analyzed at different scales, —irrespective of species, brain data modality, or the spatio-temporal resolution of the neural event. The approach followed in this work treats the rat cortical (prefrontal cortex and hippocampal circuits) and subcortical (accumbens or thalamic reuniens nuclei and basolateral amygdala) areas as network nodes and their inter-areal functional interdependences as network edges. In a previous work (Gruart et al., Cereb. Cortex, 2015) we demonstrated that associative learning is able to evoke more-or-less stable changes in neuronal population activity in selected cortical/subcortical sites. In the same way, a recent study (Fernández-Lamo, et al., Cereb. Cortex, 2017) helps to understand when and where associative learning is taking place in the brain. However, a still-open question is how all the information of the network is encoded and processed when learning is being engraved in the brain? Here, we have recorded the synaptic strength —namely, the slope of the chronically evoked field postsynaptic potentials (fPSPs), and the simultaneous local field potentials (LFPs) in selected brain sites during the acquisition of operant conditioning tasks in behaving rats. Also we implemented an analytical approach that integrate all the functional information of the network on a flexible and scalable ‘hypercube’ where the evoked synaptic-timing-behavioral states, the LFP spectral measures, and the dynamic interdependences (cross-correlation, cross-spectrum, coherence, causality, or connectivity) configure a full repertory of functional activity maps during operant conditioning tasks. Preliminary results indicate that during the acquisition of the learning, the main significant changes of the network were taking place in the outputs and in extrinsic nodes of the hippocampal circuit, always close to the asymptotic level of acquisition of the operant conditioning task, and just during the execution of a precise sequence (pressing the lever–going to the feeder–eating) of rat behaviors. The implication of this experimental-analytical approach is that the learning requires multisynaptic states, but that multiple states should not differ simply in their synaptic strength, – i.e., other underlying rules with different degrees and levels of coding are necessary.

Support: Grants P11-CVI-7222 to A.G., and BFU2014-56692-R to J.M.D.-G and to A.G.; as well as the Grant JC2015/00177 (Fulbright-MECD Postdoctoral Fellowship Program) to R.S.-C.

ICCN 2017

101

Symposium S12

DYNAMIC MODELLING OF EEG AND fMRI

Organizer: Dr. Xu LeiSleep and neuroimaging Center, Faculty of Psychology,

Southwest University in China, Chongqing, China.

Abstract: EEG and fMRI recordings measure the functional activity of multiple coherent networks distributed in the cerebral cortex. Identifying the dynamic features from the neuroelectric and hemodynamic signals may help to explain the complex relationships between different brain regions. In this symposium, different methods were proposed for the dynamic modelling of EEG and fMRI, both for task and resting state. First, based on the simultaneous EEG-fMRI recording, dynamic functional connectivity was extracted during sleep. Second, a biophysically based mean-field model was developed to uncover the potential roles of the basal ganglia in controlling absence seizures. Third, the adaptive directed transfer function was proposed to evaluate the time-varying cortical connectivity during facial recognition. Finally, a complete analysis pipeline was proposed detect spatial maps of resting-state networks using high-density EEG recordings. This symposium is intended to address the challenges in dynamic modelling of EEG and fMRI data from different perspectives: neural computation, biomedical engineering, and cognitive neuroscience.

ICCN 2017

102

S12-1

SPONTANEOUS THETA RHYTHM PREDICTS INSOMNIA DURATION:A RESTING-STATE EEG STUDY

Wenrui Zhao1, Dong Gao2, Faguo Yue2, Yanting Wang2, Dandan Mao2, Tianqiang Liu1, Xu Lei1*

1 Sleep and Neuroimaging Center, Faculty of Psychology, Southwest University, Chongqing, China.2 Sleep Psychology Center, Daping Hospital, Third Military Medical University, Chongqing, China.

Abstract: Increased theta power and subjective sleepiness during waking EEG had been found in many researches of sleep deprivation. However, rare study had ever investigated the theta rhythm in awake and its cortical generators in insomnia disorder (ID). Consequently, based on the scalp EEG signal and its brain cortex distribution reconstructed by a network-based source imaging, we explored the abnormal theta power of insomniacs with different insomnia duration and its cortical generators. Results indicated that, compared to good sleepers, only ID with insomnia duration above 3 years presented sustained decreased theta power in multiple networks. Intriguingly, the theta power of frontoparietal and deep structure network was negatively correlated with the insomnia duration. These findings suggested that decreased waking theta power in ID may be the electrophysiological correlate of subjective sleepiness deficiency, and the theta power of FPN and DSN were good predictors for the insomnia duration.

ICCN 2017

103

S12-2

BIOPHYSICAL MODELS OF ABSENCE SEIZURES

Daqing Guo*, Mingming Chen, Jiakang Wang, Shan He, Dezhong YaoSchool of Life Science and Technology, Key Laboratory for NeuroInformation of Ministry of

Education, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 610054, China

Abstract: Accumulating evidence has suggested that the genesis of absence seizures is highly associated with abnormal interactions within corticothalamic network. The basal ganglia, indirectly mediating communications between the cerebral cortex and thalamus, have been confirmed to contribute to suppressing absence seizures through inactivating the neural activation level of substantia nigra pars reticulata (SNr), which projects inhibitory signals both to thalamic reticular nucleus (TRN) and specific relay nuclei (SRN) of thalamus. However, the neural dynamical mechanisms underlying the termination of absence seizures by the basal ganglia are still remain unclear. Here, we develop a biophysically based mean-field model of basal ganglia-corticothalamic (BGCT) network to uncover the potential roles of the basal ganglia in controlling absence seizures. We find that the basal ganglia not only can successfully suppress absence seizures with the isolated SNr-TRN pathway through inactivating neural activities of SNr, but also can control absence seizures via enhancing the neural activation level of SNr with the isolated SNr-SRN pathway. Moreover, due to competitions between SNr-TRN and SNr-SRN pathways, we find that increasing or decreasing neural activities of SNr could control absence seizures under some certain conditions, which suggest that the basal ganglia can bidirectionally control absence seizures. Additionally, we find that the basal ganglia can also suppress absence seizures via the new identified inhibitory pallido-cortical pathway, which directly relays the output of globus pallidus external segment (GPe) to cerebral cortex. Furthermore, we find that several GPe-related pathways, including direct- and indirect-related pathways, also play critical roles in controlling absence seizures. Importantly, we observe that the basal ganglia can bidirectionally control absence seizures through the nigrothalamic pathway (including the SNr-TRN and SNr-SRN pathways), which can be shaped by the pallido-cortical pathway. Overall, these findings highlight that the basal ganglia play important roles in controlling absence seizures, and might also provide some novel insights into the treatment of absence epilepsy.

Support: National Natural Science Foundation of China (Grant Nos. 81571770, 61527815, 81371636, and 81330032).

ICCN 2017

104

S12-3

ELECTRICAL CORTEX TIME-VARYING NETWORK BASED ONTHE INVERSE OPERATION: A STUDY ON N170 FOR

EMOTIONAL FACE RECOGNITION

Yin Tian* and Wei XuBio-information College, Chongqing University of Posts

and Telecommunications, Chongqing-400065, China

Abstract: Using the adaptive directed transfer function (ADTF) method to evaluate the time-varying cortical connectivity from high-resolution electroencephalography (EEG), the prevent study is to investigate the related information of N170, a negative event-related potential component (ERP) appeared about 170ms that is elicited by facial recognition. Three kinds of emotional faces, namely, positive, neutral and negative faces, were comparatively investigated via the time-varying processing of N170. Our data showed that the source’s relative location of N170 existed significantly different between the positive and negative faces, with the former being observed a stronger source activation in right occipital region, and the latter showing strongest out-degree in right temporal-parietal region among the three emotional faces. No significant difference was observed between positive and neutral faces. In particular, the out-degree of the bilateral temporal-parietal region presented a positive correlation with the subjects’ emotional validity for positive and negative faces. Namely, the greater out-degree of bilateral temporal-parietal region for positive faces, the greater positive emotion for subject and the greater out-degree of bilateral temporal-parietal for negative faces, the greater negative emotion for subject. The correlation between emotional validity and out-degree of bilateral temporal-parietal region for neutral faces is similar to the positive faces. Three kinds of emotional letter were investigated, finding compared to the emotional faces, the right temporal-parietal region activation was observed in positive and negative letter, and the middle temporal gyrus was observed for all emotional letter. These findings indicate that the N170 not only was modulated by emotion, but also reflected the face structure coding. The time-varying network method provided a novel way to interpret N170.

Support: National Natural Science Foundation of China (#61671097); the Chongqing Research Program of Basic Science and Frontier Technology (No.cstc2017jcyjBX0007; No.cstc2015jcyjA10024); the Chongqing Key Laboratory Improvement Plan (cstc2014pt-sy40001); and the University Innovation Team Construction Plan Funding Project of Chongqing (CXTDG201602009).

ICCN 2017

105

S12-4

HIGH-DENSITY EEG PERMITS THE DETECTION OF RESTINGSTATE NETWORKS

Q. Liu1,2*, R. Farahibozorg3,4,5, C. Porcaro6,2,7, N. Wenderoth1,2, D. Mantini1,2,4

1Laboratory of Movement Control and Neuroplasticity, KU Leuven, Belgium. 2Neural Control of Movement Laboratory, ETH Zurich, Zurich, Switzerland. 3MRC Cognition and Brain Sciences Unit, Cambridge, UK.

4Graduate School of Life Sciences, University of Cambridge, Cambridge, UK. 5Department of Experimental Psychology, Oxford University, Oxford, UK. 6LET’S-ISTC-CNR, Fatebenefratelli Hospital, Isola Tiberina,

Rome, Italy. 7Dept. of Information Engineering, Marche Polytechnic University, Ancona, Italy.

Abstract: Background: The existence of resting state networks (RSNs) in the human brain has been largely documented by functional magnetic resonance imaging (fMRI) and magneto-encephalography (MEG) studies (Fox and Raichle, 2007; de Pasquale et al., 2010; 2012; Brookes et al., 2011; Hipp et al., 2012; Gillebert and Mantini, 2013). However, no research group has been able to map brain networks using EEG recordings so far. In this study, we demonstrate that high-density EEG (hdEEG) can be used to detect RSNs. Methods: We collected 5-minute resting state hdEEG (256 channels) signals, electrode positions and T1-weighted structural MRI in 19 subjects (age 28±5.9 years, 14 females). We developed a dedicated processing pipeline, which included 4 main processing steps: 1) ICA-based EEG artifact reduction (Mantini et al., 2008); 2) creation of 12-tissue realistic head model using a 12-layer finite element method (FEM) to estimate how electrical signals transmit from each brain source to the sensors (Hallez et al., 2007); 3) reconstruction of brain activity by the eLORETA method (Pascual-Marqui et al., 2011); 4) temporal ICA on down sampled (1Hz) power time series of voxels. After estimating the component maps in individual space, we warped them to MNI space, and selected the EEG RSNs by matching them with fMRI-RSN templates. Finally, group-level RSN maps were generated by means of a random-effect analysis (Smith and Nichols, 2009), using a voxel-wise non-parametric permutation test (RANDOMISE in FSL). Results: We identified 14 RSNs (group-level: N=19, p<0.001, TFCE corrected) from hdEEG data. These 14 RSNs are: default mode network (DMN), dorsal attention network (DAN), ventral attention network (VAN), right frontoparietal network (rFN), left frontoparietal network (lFN), language network, opercular network (CON), auditory network(AN), ventral somatomotor network (VSN), dorsal somatomotor network (DSN), visual foveal network (VFN), visual peripheral network (VPN), medial prefrontal network (MPN) and lateral prefrontal network (LPN). We obtained the spatial correlation between EEG-RSNs and fMRI-RSNs. Furthermore, to test the robustness of the pipeline, we split the continuous 5-minute hdEEG into 2 pieces of 2.5-minute signals (segment 1 and segment 2). Our results allowed to obtain the spatial maps of 14 RSNs generated by segment 1 and segment 2 respectively, and the spatial correlation between them. Conclusions: We developed a complete analysis pipeline to detect RSNs spatial maps using hdEEG recordings. Our work suggests that hdEEG can be used as an alternative to MEG to investigate the electrophysiological basis of functional networks.

ICCN 2017

106

S12-5

SEIZURES DYNAMICS IN A MEAN-FIELD MODEL WITHBURSTING DYNAMICS

Zhihui Wang and Qingyun WangDepartment of Dynamics and Control, Beihang University, Beijing 100191, China

Abstract: There exists a feedback loop between the thalamus and cortex, which has been implicated in pathologies such as epileptic seizures. Besides that, the abnormal interactions and the delays induced by signals transmitting around the corticothalamic loop are believed to be connected with epileptic seizure. However, the relevant biophysical mechanisms between conduction delays and seizures dynamics are poorly understood. Then in this paper, we use a mean-field model of the corticothalamic system including bursting dynamics in the reticular nucleus to explore the changes of interactions strength and delays leading to pathological seizure states. As a result, we obtain some dynamic transition phenomena of different firing patterns, and then analyze the bifurcation mechanism of corresponding firing transition through changing some physiological related parameters. It provides a theoretical basis to better understand seizures dynamics. Hopeful, these numerical results could be significant for future experimental and clinical studies.

Support: National Science Foundation of China (Grants 11325208, 11572015 and 11172017).

POSTERS

ICCN 2017

108

Poster P1

AN ELECTROPHYSIOLOGICAL APPROACH TO THE STUDY OF THE CLAUSTRUM: RECORDING CLAUSTRAL NEURONS IN ALERT BEHAVING

RABBITS

M. Mar Reus-García*, Agnès Gruart, José M. Delgado-GarcíaDivision of Neurosciences, Pablo de Olavide University, Seville

Abstract: Despite of the fact that the claustrum (CL) has been the subject of several anatomical and theoretical studies along the past three decades, its main functions in alert behaving animals still remain unknown. Indeed, anatomical and embryological studies revealed that the CL is a thin, long, sheet-like neuronal structure located between the putamen and the insular cortex and that it is originated from the insula. One of its most remarkable features is that the CL sends projections and receives inputs from all regions of the cortex. At the present moment, all we know about its function is speculative, although it is assumed that it could be involve in cognitive processes and in the integration of different sensorial modalities. In order to study the functions of this interesting neural structure, we have recorded in rabbits the firing activities of identified CL neurons during the acquisition of a classical eyeblink conditioning. For conditioning, we used a delay paradigm: a tone as conditioned stimulus (CS) followed by an air puff as unconditioned stimulus (US) that co-terminated with it. Conditioned responses were determined from the electromyographic activity of the orbicularis oculi muscle. Neurons were recorded with glass electrodes and the proper location of recorded neurons was determined by their anti- or orthodromic activation from the ipsilateral motor cortex. Preliminary results shown that CL neurons present low rates of spontaneous firing and that they are activated during paired CS-US presentations, but their firing are less noticeable in well-conditioned animals.

Support: Grants from the Spanish MINECO (BFU2014-56692-R) and Junta de Andalucía (BIO1388 and P07-CVI-7222) to A.G. and to J.M.D.-G.

ICCN 2017

109

Poster P2

STRUCTURE AND DYNAMICS OF SELF-ORGANIZED NEURONAL NETWORK WITH AN IMPROVED STDP RULE

Rong Wang, Ying Wu, Mengmeng Du, Jiajia LiState Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace,

Xi’an Jiaotong University, Xi’an 710049, China

Abstract: The chemical synapses in a neural network are known to be modulated by the neuronal firing activities through the spike-timing-dependent plasticity (STDP) rule. In this paper, we improve the multiplicative STDP rule by adding a momentum item with the aim of overcoming the low rate with which the neuronal network self-organizes into a stable complex structure. We find that the improved STDP rule with suitable momentum factors significantly speeds up the evolutionary process of the self-organized neuronal network. In addition, we explore the topological structure of self-organized neuronal network using complex network method. We show that the improved STDP rule generally results in a smaller node degree, clustering coefficient and modularity of self-organized neuronal network. Furthermore, we investigate the dynamical behaviors of self-organized neuronal network. We observe that depending on the momentum factor, the improved STDP rule has different effects on the network synchronization, neural information transmission, modularity and network complexity. Remarkably, for a specific momentum factor, the self-organized neuronal network shows the highest global efficiency of information transmission and the best combination between functional segregation and integration, which reflects the optimal dynamics as well as the topological structure. Our results provide a reasonable and efficient modulating rule of chemical synapse underlying the neuronal firing activities.

Support: National Natural Science Foundation of China (Grant Nos. 11272242, 11472202).

ICCN 2017

110

Poster P3

A PSEUDO-NEURON DEVICE AND FIRING DYNAMICS OF THEIR NETWORKS SIMILAR TO NEURAL SYNCHRONIZING

PHENOMENA BETWEEN FAR DISTANT FIELDS IN BRAIN

T. Yano1, Y. Goto2, T. Nagaya3, I. Tsuda4, S. Nara1

1Graduate School of Natural Science and Technology, Okayama University. 2Junior College, Beppu University. 3Faculty of Engineering, Oita University. 4Graduate School of Science, Dept. of

Mathematics, Hokkaido University, Sapporo. Japan

Abstract: A pseudo-neuron hardware device called Dynamic Self-Electro-optic Effect Device (DSEED) is proposed and considered. First, the two kinds of neuron-like pulsed oscillations ((i) fast spiking type, (ii) threshold spiking type) are theoretically predicted and their nonlinear oscillation properties are discussed. The case (i) was partly reported in our previous papers (Fig. 1a), so this paper is the first report of the case (ii) (Fig. 1b & 2). Next, firing (pulsing) pattern dynamics of their diffusion coupled DSEED networks of the both spiking types are considered and the computer experiments indicate that there are the three kinds of firing dynamics, (a) transient chaotic firing state, (b) entirely synchronized (coherent) firing state, (c) partly synchronized firing state between far distant fields in the network. The case (a) and (b) were partly reported in ICCN2011 briefly with employing rather less neuron number (400̴900) for simplicity. The new results reported in this paper are, (1) the experiments in larger neuron number case (up to 512☓512) that result in the more realistic and new phenomena (Fig. 2), (2) the discovery in the case (c) obtained by the computer experiments is discussed. It shows that the firing patterns are quite similar to neural synchronization phenomena observed in brain (Fig. 3 & 4). So, this device and their networks are, if successfully implemented by hardware, quite useful to verify and develop theories of neural (or coupled nonlinear oscillator) networks to consider or to understand the mechanisms of brain functions.

Support: MEXT KAKENHI Grant Number JP24120707, and Cooperative Research Program of “Network Joint Research Center for Materials and Devices”.

ICCN 2017

111

Poster P4

EFFECT OF SPIKE-TIMING-DEPENDENT PLASTICITY ON STOCHASTIC SPIKE SYNCHRONIZATION IN AN EXCITATORY NEURONAL

POPULATION

Sang-Yoon Kim and Woochang LimInstitute for Computational Neuroscience and Department of Science Education,

Daegu National University of Education, Daegu 42411, S. Korea

Abstract: We consider an excitatory population of subthreshold Izhikevich neurons which exhibit noise-induced spikings. This neuronal population has adaptive dynamic synaptic weights governed by the spike-timing-dependent plasticity (STDP); the synaptic weights vary via a Hebbian plasticity rule depending on the relative time difference between the pre- and the post-synaptic spike times. In the absence of STDP, stochastic spike synchronization (SSS) between noise-induced spikings of subthreshold neurons was previously found to occur over a large range of intermediate noise intensities through competition between the constructive and the destructive roles of noise. Here, we investigate the effect of additive STDP on the SSS for various values of the rewiring probability p in the Watts-Strogatz small-world neuronal network which interpolates between the regular lattice with high clustering (p=0) and the random graph with short average path length (p=1) via random uniform rewiring. A ``Matthew effect’’ in synaptic plasticity is found to occur due to a positive feedback process. Good synchronization gets better via long-term potentiation (LTP) of synaptic weights, while bad synchronization gets worse via long-term depression (LTD). As a result, a step-like rapid transition to SSS occurs by varying the noise intensity, in contrast to the relatively smooth transition in the absence of STDP. Furthermore, a ``plateau’’ of SSS with nearly same degree is formed within the range of the SSS. Emergence of LTP and LTD of synaptic weights are investigated in details through microscopic studies based on both the distributions of time delays between spike times of the pre- and the post-synaptic neurons and the pair-correlations between the pre- and the post-synaptic IISRs (instantaneous individual spike rates). Finally, a multiplicative STDP case depending on the synaptic weights is also studied and compared with the above additive STDP case (independent of the synaptic strengths).

ICCN 2017

112

Poster P5

STUDY OF DYNAMIC MECHANISM FOR RHYTHMICTRANSITION OF GLIAL-NEURONAL NETWORK

Mengmeng Du, Ying Wu*State Key Laboratory for Strength and Vibration of Mechanical Structures,

School of Aerospace, Xi’an Jiaotong University, Xi’an, China 710049

Abstract: The dynamic behaviors of neural clusters is closely related to brain diseases, such as, rhythmic oscillations, transitions of different rhythmic ranges. High frequency oscillations (greater than 80Hz) are recorded in epileptiform seizure onset in patients with temporal lobe epilepsy. In epileptic seizures, rhythm transitions from the fast frequency region (e.g., Hundreds of Hertz) to the slow frequency region (e.g., only a few Hertz) are equivalent to rapid changes of the initiation and termination of seizure events. Moreover, numerous studies have shown that glial cells directly involved in neuronal discharge activities. At present, little attention has been paid to the influence of rhythm dynamics of glial-neuronal network. The relations between rhythm transitions of neuronal cluster and epileptic seizures is mostly obtained from the surgical resection experiments. Therefore, distinguishing the rhythmic transitions associated with the onset and termination of epileptic seizures may provide an important clinical guide for the selection of the optimal period for the treatment of epilepsy. In current paper, we constructed a glial-neuronal network model in the hippocampus area containing extracellular ions diffusion dynamics. Results verify the direct correspondence relations between rhythmical oscillations of different frequencies and the onset or termination of epileptic seizures by numerical simulation method.

Support: National Natural Science Foundation of China (11472202); the Open project funds for the Key Laboratory for NeuroInformation of Ministry of Education (ZYGX2016K006).

ICCN 2017

113

Poster P6

CHANGES IN PHASE SYNCHRONIZATION OF EEG DURING DEVELOPMENT OF SYMBOLIC COMMUNICATION SYSTEMS

M. Fujiwara1, T. Hashimoto1, G. Li1, J. Okuda2, T. Konno3, K. Samejima4, and J. Morita5

1Japan Advanced Institute of Science and Technology, Asahidai 1–1, Nomi, Ishikawa 923-1211, JAPAN. 2Kyoto Sangyo University, Kamigamo-Motoyama, Kita-Ku, Kyoto 603-8555, JAPAN. 3Kanazawa Institute of Technology, Ogigaoka 7-1, Nonoichi, Ishikawa 921-8812, JAPAN. 4Tamagawa University, Tamagawa Gakuen 6-1-1, Machida, Tokyo 194-8610, JAPAN. 5Shizuoka University, Naka-Ku 3-5-1, Hamamatsu, Shizuoka 422-8017, JAPAN.

Abstract: While neural synchrony viewpoint has attracted attention for studying coordination behavior (Tognoli et al., 2007; Dumas et al., 2010; Yun et al., 2012), a neural mechanism for coordination behavior via symbolic communication has not been well studied from the viewpoint. To identify changes in neural synchrony during a course of establishment of symbolic communication systems, we analyzed Phase Locking Value (PLV) (Lachaux et al., 1999) for hyper-scanning EEG data (Li et al., 2016) recorded during a symbolic communication task (Konno et al., 2013). PLV is an index of phase synchronization, which is known to reflect the cognitive process of finding meaning in visual stimuli (Rodriguez et al., 1999; Castelhano et al., 2013). In the symbolic communication task, a pair of participants played a coordination game on computer screens, where the aim was to bring their agents, located randomly in one of four rooms (2x2 configuration), to the same room. Before moving, each participant sent the partner a message by choosing one geometric figure from four options (˜Ã¿Ì), whose meanings were neither predefined nor initially shared. Diagonal movement was prohibited, which demanded a mutual understanding of connotations (informing initial room/destination) as well as denotations (figure-room mappings) of symbolic messages for better performance. The game was repeated for 60 trials. In the initial five trials, the best performance pair showed long-distance synchronizations in latency periods 150-300 ms and 450-750 ms with a desynchronization period (300-450 ms) between them at 40 Hz frequency (gamma band) after receiving the partner’s message. This pattern was similar to Rodriguez et al.’s (1999) observation that showed synchronization/desynchronization during a face perception and a transition between two different cognitive states. The synchronization around 500 ms became stronger and continued longer in the last five trials, where the best performance pair successfully established a shared communication system. Transition between synchronization and desynchronization and enhancement of synchronization in the later trials were not observed in the worst performance pair. These results may suggest that the phase synchrony around 500 ms and later is involved in the cognitive process of finding meaning in symbolic messages.

Support: Grants JSPS KAKENHI 26240037.

ICCN 2017

114

Poster P7

RATBUTTON: A USER-FRIENDLY TOUCHSCREENPRESENTATION SOFTWARE

C. Andreu-Sánchez*, M. A. Martín-Pascual, A. Gruart, and J.M. Delgado-GarcíaNeurocinematics, 08174-Barcelona, Spain

Division of Neurosciences, Pablo de Olavide University, 41013-Seville, Spain

Abstract: Psychology and cognitive neuroscience have been using for the past decades several analogic systems to present stimuli and evaluate protocols. During the last years, there has been a clear flow to digital systems. Those have expanded possibilities for researchers. Digital systems, however, tend to require learning programming language. So, behavioral researchers are asked, not only to design, analyze and study their protocols, but also to learn some specific software language to write them. Here, we are presenting a software for touchscreen research in psychological and neuroscientist environment, with no need of programming language learning. We are introducing RatButton, a software for presenting interactive stimuli in touch screens, designed for psychological and cognitive neuroscience experimentation, with human and animal models. RatButton is available for real touch screen devices with real touch interactivity, it does not need programming, and it does not require a connection to an external PC. RatButton software has been developed in C, C++ and Objective-C environments for touch screen devices with iOS. It requires an iOS 9.0 version or later. The software is, carefully developed to be used with Virtubox. It is a stimuli presentation system using RatButton, able to control different hardware connections in a scientific environment. VirtuBox manages inputs and outputs between RatButton and external devices, such as a feeder, a lighting system, or a sound system. The possibilities for this are very wide. VirtuBox also creates an easy environment for researcher so there is no need of coding for controlling the connections. RatButton offers different standard protocols, however researchers can make several changes in the protocols through a Settings page. RatButton manages results itself but, as some researchers have already installed in their labs data acquisition systems, results can also be externally managed through cable connection. RatButton has also been used in Brain-machine interfaces (BMI) environments.

ICCN 2017

115

Poster P8

DIFFERENCES IN PERCEIVING NARRATIVES THROUGHSCREENS OR REALITY

M.A. Martín-Pascual*, C. Andreu-Sánchez, J. M. Delgado-García, and A. GruartNeuro-Com Research Group, Universitat Autònoma de Barcelona, 08193-Barcelona, Spain


Abstract: Perceiving and understanding a narrative requires a high level of attention. While we are watching an audio-visual work or seeing a real performance we are unconsciously segmenting the content through eyeblinks. In the case of audio-visual works, the segmentation in the perception is usually double as the director uses to cut the content in different shots. We wanted to look for differences in spontaneous blink rate evoked by attending the same narrative across a movie or across a live theatrical performance. Here, we have created a real theatrical stimulus and three different audio-visual movies (with the most common video editing styles each: sequence shot, Hollywood style, and MTV style) with the same narrative. We displayed them randomly to 40 subjects and compared their visual perception in the two conditions: screened stimuli versus performed play. We obtained that watching narratives through screens inhibits significantly spontaneous blink rate compared to seeing them performed in real world. For that reason, and taking into account previous studies, we believe that audio-visual works receive more attention that live actions. In our opinion, this should be taking into account for the creation of communication strategies, not only in advertising and marketing contexts, but also in learning contexts. Furthermore, we have analyzed how previous audio-visual experience of subjects would affect to this question. For that, half of our participants (n=20) were media professionals, while the rest (n=20) were non-media professionals. We obtained that media professionalization inhibits spontaneous eyeblink rate in both conditions, screened stimuli and real performance, compared to non-media professionals. We believe that watching screens steadily over time in professional context, with high level of attention, affects how we perceive not only screened-stimuli but, more interestingly, reality. We think it will be of interest, in the future, to see how this affects to video gamers who spend so many hours making decisions related to audio-visual content not for professional purposes but for leisure.

ICCN 2017

116

Poster P9

BEHAVIOURAL AND BRAIN ACTIVITY MODULATIONTHROUGH NEUROFEEDBACK TRAINING USING

ELECTROENCEPHALOGRAPHY

T. Kimura and J. OkudaDepartment of Intelligent Systems, Faculty of Computer Science and Engineering,Kyoto Sangyo University, Kamigamo-Motoyama, Kita-ku, Kyoto 603-8555, Japan.

Abstract: Neuroscience studies have traditionally employed an experimental approach that examined neurophysiological responses associated with cognition and behaviour. Recently, a novel approach using neurofeedback training has been developed to investigate cognitive and behavioural changes resulted from induction of a specific brain activity pattern, i.e., an opposite causal direction between experimental manipulation and brain responses. So far, this approach has succeeded in showing improvement of visual discrimination ability (Shibata et al., Science, 2011), modulation of facial preferences (Shibata et al., PLoS Biol., 2016), extinction of fear conditioning (Koizumi et al., Nature Hum. Behav, 2017), and so on. These studies used information decoded from spatial patterns of functional magnetic resonance imaging (fMRI) data as a feedback signal, which limited temporal resolution of the training, as well as use of time-relevant information for the feedback signal. Moreover, brain activity changes associated with the neurofeedback training have been less investigated. In the present study, we developed a feedback training system that utilized information decoded from scalp-recorded electroencephalography (EEG). We explored effectiveness of EEG neurofeedback with better temporal resolution that used frequency information of the brain electrical activities as a feedback training signal. We tried to show a behavioural enhancement effect as improvement of reaction times (RTs) to monetary incentive delay (MID) task (Knutson et al., NeuroImage, 2000) that was designed to induce activation of reward-related brain regions. We also explored how brain activity patterns were modulated through the EEG neurofeedback training. As a result, after four-day training in which participants tried to reproduce a specific pattern of EEG power spectrum (5-70 Hz frequency range) corresponding to the pattern during MID trials with faster RTs, four out of five participants showed RT improvement for a post-training MID task. Analyses of EEG data during the post-training MID task revealed higher probability of appearance of the trained EEG spectral pattern during any MID trial types (faster RTs, slower RTs, and control trials without monetary incentive by RTs). The present results clearly indicate behavioural effectivenenss of the EEG neurofeedback training, in parallel with the effect of overall enhancement of the trained brain activity state.

Support: Grants KAKENHI 15H05878 and 26240037.

ICCN 2017

117

Poster P10

COMPLEXITY OF HEART RATE AS A VALUEOF BEHAVIORAL COMPLEXITY

A. V. BakhchinaV.B. Shvyrkov Laboratory of Neuronal Bases of Mind, Institute of Psychology,

Russian Academy of Sciences, Moscow, Russia

Abstract: Autonomic neural system is the main way for the brain-body coordination. Heart rate variability (HRV) reflects activity of ANS and some cortical structures (Thayer et al, 2009). As a rule HRV analyses is used for evaluation of emotional or functional states, s.a. stress, arousal, high cognitive control, sleepiness etc (Acharya et al, 2006). We suppose these different states can be considered as characteristics of behavior formed at different stages of ontogeny. Therefore we investigated whether HRV in the early-formed behavior (“old”) differs from HRV in the later-formed (“new”) behavior. Basing on the fact that usually “old” behavior is less complicated than “new” behavior (Lewin, 1946;. Anokhin et al., 1996), we hypothesized that complexity of heart rate is less in the “old” behavior than in the “new”. Here, we have recorded RR-intervals (intervals between consecutive heartbeats) in 25 healthy subjects (age from 21 to 35 years), who had mathematical specialization. Participants had to pass two tests. The first test included the sentences with mathematical words (later-formed behavior) and the second test included the sentences with words were in common current use (early-formed behavior). The task was to add one missing word in each sentence. The tests were performed using personal computer, the order of tests was counterbalanced across subjects. To evaluate the complexity of heart rate we estimated the sample entropy (SampEn). SampEn is a measure, quantifying the regularity and complexity of time series (Richman and Randall, 2000). Using Wilcoxon test we compared SampEn in both tests. The values of SampEn were significantly higher in the mathematical test performance (median=1.04; quartiles: 0.93-1.14) than in the performance of the common used words test (median=1.01; quartiles: 0.88-1.04) (Z=2.81, p=0.004). In other words complexity of heart rate was higher when participants actualized later-formed behavior. It is important to notice that the mean of the heart rate did not differ between tests. It means that those heart rate fluctuations were not related with changes of the blood flow velocity. The main output of this study is that the behavioral complexity is reflected not only in the brain activity, but also in the body activity.

Support: Grant RFBR N16-36-60044 mol_а_dk, within the research programme of a Leading Scientific School of Russian Federation: “System Psychophysiology” (NSh-9808.2016.6).

ICCN 2017

118

Poster P11

CHANGES IN BRAIN ACTIVITY DURING INSTRUMENTALBEHAVIOUR AFTER ADDITIONAL LEARNING IN RATS

Vladimir GavrilovInstitute of Psychology, Russian Academy of Sciences, 129366-Moscow, Russia

Abstract: To study how additional learning may change the brain activity during realization of initially learnt behavior, we compared EEG-potentials in rats performing an instrumental lever-pressing task before and after additional training in a slightly different environment. EEG was recorded over motor, retrosplenial posterior and visual areas of the cortex. A similar configuration of behavior-related EEG-potentials was observed during performing the instrumental task before and after additional learning, which suggests that, in general, common brain processes underlie the behavior in the compared conditions. However, differences in the amplitudes and latencies of components of behavior-related potentials shown in this work support the hypothesis that the composition of the elements of individual experience underlying this behavior changes after additional learning.

Support: Russian Science Foundation №14-28-00229.

ICCN 2017

119

Poster P12

CORTICAL AND SUBCORTICAL ACTIVITIES FOR FOODAND SOCIAL INTERACTIONS WITH RATS

F. Rocha-Almeida*, A.R. Conde-Moro, J.M. Delgado-García, and A. GruartDivision of Neurosciences, Pablo de Olavide University, 41013-Seville, Spain

Abstract: As a basic physiological need, food is a natural reward used in many experimental procedures with rodents to study learning processes or decision-making tests. On the other hand, social interaction also has an important role and it could be used as a positive reinforcement, proving that rodents can press a lever to gain access to a social contact with another animal. In order to study the differences in brain activities between these two types of reinforcements, we used two modified and adjacent Skinner boxes divided in two equal-size compartments separated by a guillotine door. One of these Skinner boxes has two available levers: i) one lever that, when pressed, provides access to food pellets, with a 1:1 fixed ratio schedule; and ii) another lever that, when pressed, allows 10 s of visual and partial physical contact with a rat located in the adjacent box. This access is achieved by the mechanical opening of a guillotine door that gives access to a stainless steel grid separating the 2 boxes. Every test session has a duration of 20 min for, at least, 10 consecutive days. Rats were implanted with recording electrodes in the medial prefrontal cortex (cingulated, prelimbic, and infralimbic cortices), the accumbens septi nucleus (shell and core), the mediodorsal thalamus and the hippocampus (CA1 area). Selected rats were feed ad libitum and were previously placed in social isolation, during one month, to increase their motivation for social interactions. Local field potentials (LFPs) were recorded during all experimental procedures. Preliminary analyses of recorded LFPs indicate significant differences just before pressing the levers to obtain the respective rewards (food pellets or social interactions), but mostly when comparing LFPs recorded in the moment when rats eat the collected pellet with the ones that they are socially interacting with another animal.

ICCN 2017

120

Poster P13

ROLE OF INHIBITORY CONTROL PROCESSESIN DECISION-MAKING PROCEDURES

J. A. García-Moreno*, C. Andreu-Sánchez, M. Á. Martín-Pascual, J. M. Delgado-García, and A. Gruart


Abstract: Decision making is a field of study which has reached great relevance nowadays. There are several so-called “executive” processes, which underlie this concept which enable the development of flexible and goal-oriented behaviors, such as the ability to suppress a specific action when it is not suitable to the current context or the ability to cancel an action in progress when an unpredictable cue indicates that it should be avoided. To study these processes, different experimental models have been developed, mainly the go/no-go task and the stop signal task, respectively. The main difference between these two paradigms is that the go/no-go task assesses the ability to discriminate contextual cues indicating whether the execution or the non-execution of a given action will be reinforced, meanwhile in stop signal task an unpredictable and delayed cue indicates that we have to cancel the current action in progress. The first task measures the number of responses in no-go trials or commission errors, whilst the second task measure the speed or latency of the go signal reaction time and the stop signal reaction time derived from the inhibitory control process. In the second task, the manipulation of the delay in which the stop signal is presented is decisive (stop signal delay, SSD). To study neural mechanisms underlying motor vs. cognitive activities, we have selected the go/no-go task. The reason is that our objective is to evaluate local field potentials (LFPs) related to the ability to discriminate contextual cues that indicate whether the execution or non-execution of a given action will be reinforced. Thus, we will be able of recording electrophysiological signals related to the condition in which the non-execution of a response is reinforced — namely, in absence of any motor activity. We have implanted chronic electrodes in cortical (prefrontal, parietal, premotor and motor areas) and subcortical (accumbens septi, thalamus) structures in experimental rats, whose activity is expected to be related to cognitive and/or motor processes. The aim is to record LFPs at the indicated sites during the performance of go/no-go tasks and to determine the involvement of the recording sites in this decision making procedures.

ICCN 2017

121

Poster P14

SPECTRAL POWER AND MATURATIONAL FREQUENCY-COUPLING DIFFERENCES BETWEEN ATTENTION DEFICIT AND CONTROLS

CHILDREN AND ADOLESCENTS

Elena I. Rodríguez-Martínez1, Brenda Y. Angulo-Ruiz1, Antonio Arjona-Valladares1, Francisco J. Ruiz-Martinez1, Jaime Gómez-González2 and Carlos M. Gómez1*

1Human Psychobiology Lab, Experimental Psychology Department, University of Seville, 41018-Seville, Spain. 2UGC of Mental Health, Virgen Macarena Hospital, 41009-Seville, Spain

Abstract: Attention deficit disorder (ADD) is a common psychiatric disorder affecting children, adolescents, and adults. It interferes with many areas of normal development and functioning in child’s life, and predisposes to psychiatric and social pathology in later life. It has been observed a developmental delay in the Electroencephalogram (EEG). The Maturational Lag model proposes that ADD is developmentally inappropriate for their age, and they would perform in behavior and EEG parameters in a way that would be normal in younger children. The resting EEG provides non-invasive spectral markers of brain function, with no need of complex experimental protocols. We have previously found a correlation between theta and beta spectral power along development in control subjects, indicating a co-maturation between those two rhythms. We hypothesized that ADD patients would show a different spectral power values compared with healthy subjects, and possibly a different theta-beta maturational coupling. These EEG parameters would serve as EEG biomarkers for ADD. Open eyes resting state EEG was recorded in a sample of 36 controls and 36 ADD subjects (6-17 years old). The power spectral density (PSD) from 0-46 Hz was computed. ANOVAs to compare spectral power between control and ADD subjects were obtained. PSD correlations of the whole range of frequencies were calculated in order to observe possible differences in the co-maturation of the different brain rhythms in both groups of subjects. An increase in delta power in ADD subjects with respect to control subjects was obtained, indicating a predominance of slow waves in ADD subjects. While control subjects presented a significant correlation between low frequency rhythms and beta rhythm, ADD subjects presented a reduced maturational frequency-coupling between these rhythms. The increase of low frequency rhythms in ADD suggests a developmental delay in ADD children, given that power of brain rhythm is decaying with age in normal subjects. The lack of maturational frequency-coupling between low frequency rhythms and beta suggest a differential pattern of development in ADD children with respect to controls.

Support: Grants of the Spanish Ministry of Economy and Competitiveness [grant numbers PSI2013-47506-R and PSI2016-80059-R] and by a research grant from Janssen-Cylag.

ICCN 2017

122

Poster P15

BEHAVIORAL WORKING MEMORY DEVELOPMENT IN ATTENTION DEFICIT CHILDREN AND ADOLESCENTS. CLASSIFICATION BY LINEAR

DISCRIMINATION ANALYSIS

Elena I. Rodriguez-Martínez1*, Antonio Arjona-Valladares1, Francisco J. Ruíz-Martínez1, Manuel Morales1, Jaime Gómez-González2 and Carlos M. Gómez1

1Human Psychobiology Lab, Experimental Psychology Department, University of Seville, 41018-Seville, Spain. 2UGC of Mental Health, Virgen Macarena Hospital, 41009-Seville, Spain

Abstract: Attentional deficit disorder (ADD, ADHD) is a complex disorder in which not only attention, but also executive functions are impaired. Working memory (WM) is a central function for performance, which is developing across childhood and adolescent periods. The impairment of WM has been considered a landmark of attentional deficit. However a behavioral characterization of this function is far from complete. Our group has elaborated, using the WM test battery for children (WMTBc) and the delayed match-to-sample test (DMTS), an extensive description of how working memory develops with age. Particularly, and using the WMTBc we have demonstrated an improvement of performance with age of the three sub-components of Baddeley’s model: Executive component, Phonological loop and Visuospatial sketchpad. By mean of DMTS and oddball tasks, improvement of RTs, the reduction of variability of RTs, the improvement of the index of discriminability (d’) and the decrease of behavioral errors have also been demonstrated with increasing age. Present experiment tries to elucidate possible WM behavioral differences between control and ADD children and adolescents, and determine the percentage of subjects that can be correctly classified by means of linear discriminant analysis. The central hypothesis is that WM behavioral performance would be impaired in ADD and these variables would permit the classification of control and ADD subjects. One hundred and eighty one control and forty one ADD children and adolescents (6-17 years old) were behaviorally recorded using WMTBc, DMTS and oddball tasks. Behavioral performance between both groups was compared by means of ANOVA. Linear discrimination analysis based on the behavioral variables was used to classify both groups of subjects. ADD children presented a behavioral impairment in the three tasks: WMTBc, DMTS and odd ball suggesting an impairment in WM performance in attention deficit subjects. They obtained lower direct scores in the three subcomponents of the Baddeley’s WM model, lower d´ values, produced more errors and presented higher variability in RTs than controls. The discriminant analysis was able to classify correctly around 70% of controls and ADD children. The results suggest that WM is a central core dysfunction in ADD and useful as a diagnostic tool.

Support: Grants of the Spanish Ministry of Economy and Competitiveness [grant numbers PSI2013-47506-R and PSI2016-80059-R] and by a research grant from Janssen-Cylag.

ICCN 2017

123

Poster P16

EVENT RELATED POTENTIALS DURING A DELAYED MATCH-TO-SAMPLE TEST TO EVALUATE WORKING MEMORY DEVELOPMENT IN CONTROL

AND ATTENTION DEFICIT CHILDREN AND ADOLESCENTS

Antonio Arjona-Valladares1*, Elena I. Rodríguez-Martínez1, Francisco J. Ruíz-Martínez1,Jaime Gómez-González2 and Carlos M. Gómez1

1Human Psychobiology Lab, Experimental Psychology Department, University of Seville., 41018-Seville, Spain. 2UGC of Mental Health, Virgen Macarena Hospital, 41009-Seville, Spain

Abstract: A neurophysiological Working Memory (WM) model has been proposed by Fuster (2007) based on the recording of single neurons during Delayed-Match-to-Sample Tests (DMTS). The model proposes a reciprocal interaction between prefrontal cortex and posterior sensory neurons that would permit the maintenance of the remembered item in WM. Using the DMTS paradigm, we have shown the human neurophysiological correlates of coding, retention and matching phases in children and adults (Barriga-Paulino et al., 2017). During the coding and matching phases, a sequence of visual Event Related Potentials (ERPs) appears, and a slow wave is present during the retention phase. Children presented a higher amplitude than adults in most of these components. During the retention phase, adults presented a negativity extending most of the scalp, while children presented a slow negativity in posterior sites and a positivity in anterior sites, suggesting a protracted maturation of frontal areas in children. As WM impairment has been considered a core feature of the Attention Deficit Disorder (ADD), it would be important to define the neurophysiology of the DMTS tasks in ADD children. Differences in ERPs amplitude with respect to controls, would permit to characterize WM processing differences in ADD. Thirty-two ADD diagnosed subjects and thirty-eight controls (6-17 years old) were recorded during a DMTS visual task. The ERPs amplitudes of ADD and control subjects were compared in the whole period (encoding, retention and matching phase) by means of the cluster mass permutation test, which controls for multiple comparisons in time and space (electrodes). Results showed statistical significant differences between both groups in ERPs amplitude for the slow wave, starting in the last part of the coding phase and continuing during the retention phase; ADD children presented lower amplitude than the control group. Electrodes CP6, P4 and P8, located on the right side of the posterior area, showed these significant differences. The lower amplitude of the slow wave in ADD children suggests a dysfunctional activation of the WM, possibly related to the difficulty to focus attention during the coding and retention phases, inducing the impairment in WM performance observed in these children.

Support: Grants of the Spanish Ministry of Economy and Competitiveness [grant numbers PSI2013-47506-R and PSI2016-80059-R] and by a research grant from Janssen-Cilag.

ICCN 2017

124

Poster P17

STOCHASTIC MULTI-RESONANCE INDUCED BY NOISEIN A NEURONAL NETWORKS OF SUBNETWORKS

Xiaojuan Sun, Zhaofan Liu, Huiyan LiSchool of Science, Beijing University of Posts and Telecommunications, Beijing, China

Abstract: Human brain is a complex network containing about 1010 neurons with 1014 links between them, and there are different cortical circuits containing a number of neurons that have functional role in learning and cognition. In visual area stochastic resonance can be a useful tool to quantify the ability of visual zone interpreting noise contaminated visual pattern. Here we study stochastic multi-resonance induced by noise in a neuronal network of subnetworks under subthreshold signal. And the subnetworks have small world structure and neurons inside the neuronal network are connected by electrical synapses. Stochastic Multi-resonance is considered as a bunch of noise intensity at which the output of system is enhanced. With different sinusoidal signal forcing on every neuron, we find that the number of optional noise intensity that make the neuronal network be able to detect the subthreshold signal. We study the phenomenon of SMR from temporal evolution of mean filed and inter-spike interval respectively. Under certain noise intensity, the temporal evolution of mean field is spiking regularly and there can be several spikings during the period of the subthreshold signal. Moreover, by comparing the interspike intervals of the neurons inside the neuronal network with the period of the subthreshold signal, we illustrate the underlined mechanism of the observed SMR phenomena. With the obtained results, we can conclude that fine-tuned signal and appropriate noise intensity are vital for the appearance of stochastic multi-resonance on complex neuronal networks.

Support: National Natural Science Foundation of China (Grant Nos. 11472061, 11572084).

ICCN 2017

125

Poster P18

A MODEL OF PLASTICITY-DEPENDENT NETWORK ACTIVITYIN RODENT HIPPOCAMPUS DURING EXPLORATION

OF NOVEL ENVIRONMENTS

P. Theodoni1,2, B. Rovira2, and A. Roxin2

1Institute of Brain and Cognitive Science, NYU Shanghai, China2Computational Neuroscience Group, Centre de Recerca Matemàtica, Bellaterra, Spain

Abstract: Place cells of the rodent hippocampus fire action potentials when the animal traverses a particular spatial location in a given environment. Therefore, for any given trajectory one will observe a repeatable sequence of place cell activations as the animal explores. Interestingly, when the animal is quiescent or sleeping, one can observe similar sequences of activation, although at a highly compressed rate, known as “replays”. It is hypothesized that this replay underlies the process of memory consolidation whereby memories are “transferred” from hippocampus to cortex. However, it remains unclear how the memory of a particular environment is actually encoded in the place cell activity and what the mechanism for replay is. Here we study how spike-timing dependent plasticity (STDP) during spatial exploration shapes the patterns of synaptic connectivity in model networks of place cells. We show how an STDP rule can lead to the formation of attracting manifolds, essentially patterns of activity which represent the spatial environment learned. These states become spontaneously active when the animal is quiescent, reproducing the phenomenology of replays. Interestingly, the attractors are formed most rapidly when place cell activity is modulated by an ongoing oscillation. The optimal oscillation frequency can be calculated analytically, is directly related to the STDP rule, and for experimentally determined values of the STDP window in rodent slices gives values in the theta range. A major prediction of these model is that the pairwise correlation of place cells which encode for neighboring locations should increase during initial exploration, leading up to the critical transition. We find such an increase in a population of simultaneously recorded CA1 pyramidal cells from a rat exploring a novel track. Furthermore, in a rat in which hippocampal theta is reduced through inactivation of the medial septum we find no such increase. This is consistent with the model, which predicts orders of magnitude lower learning rates when theta is absent.

Support: Grant BFU2012-33413 to A.R. The authors have been partially funded by the CERCA program of the Generalitat de Catalunya.

ICCN 2017

126

Poster P19

HIGH-DENSITY SIMULTANEOUS RECORDINGS FROMVISUAL CORTEX AND SUPERIOR COLLICULUS INA RAT: A PILOT STUDY IN RETINAL PROSTHESIS

A. Barriga-Rivera*, T. Guo, N. H. Lovell, J. W. Morley, and G. J. SuaningGraduate School of Biomedical Engineering, University of New South Wales, 2052 NSW, Australia

Abstract: Sight is arguably the most important sense for the safety and preservation of human beings. There are more than 30 million blind people worldwide and approximately 200 million suffering from a moderate to severe degradation of their visual function. Because blindness is one of the most debilitating disorders that impacts significantly on the quality of life, researchers around the globe are seeking to find therapies to restore sight. Retinal neurostimulators, so-called ‘bionic eyes’, have a demonstrated track record of success in restoring functional vision by electrically stimulating the retinal ganglion cells (RGCs). These cells are output neurons of the retina that connect the eye and the brain, and are normally viable in some degenerative conditions of the retina such as retinitis pigmentosa. The Holy Grail of retinal neuromodulation is the capacity to replicate the neural code through electrical stimulation. This pilot study aims to show the feasibility of simultaneous recordings using multi-electrode arrays (MEAs) in two visual centres, the superior colliculus (SC), and the visual cortex (VC). This study was approved by the Animal Care & Ethics Committee of UNSW Sydney. A female Long-Evans rat, 15 weeks of postnatal age, was anaesthetised using a combination of intravenous (ketamine + xylazine) and gaseous (isofluorane) agents. A retinal electrode was implanted in the retrobulbar space. Next, a Buszaki32 and a Buszaki64 MEA (Neuronexus, Michigan, USA) were inserted in the SC and the VC respectively, to record neural activity elicited by visual and electrical stimulation of the eye. Both electrodes were interfaced to RZ2-8 BioAmp Processor (Tucker Davis Technology, Florida, USA). Neural spikes were thresholded and latencies identified. The P50 activation threshold, defined as the mid-point of a sigmoidal regression, was estimated by fitting data from both locations to a sigmoidal curve. The use of this technique can help us to devise new stimulation configurations by improving our understanding of the responses elicited by novel stimulation paradigms in bionic vision research.

Support: Australian National Health and Medical Research Council APP1109056. The contents of the published material are solely the responsibility of the Administering Institution, a Participating Institution or individual authors and do not reflect the views of the NHMRC.

ICCN 2017

127

Poster P20

DECOMPOSITION OF SUPERIMPOSED CHAOTIC SPIKE SEQUENCES BY USING THE BIFURCATING NEURON

Akihiro Yamaguchi1, Yutaka Yamaguti1, and Masao Kubo2

1Faculty of information engineering, Fukuoka Institute of Technology, 30-1 Wajirohigashi, Highashi-Ku, Fukuoka, 811-0295, Japan. 2Department of Computer Science, National Defense

Academy of Japan, 1-10-20 Hashirimizu, Yokosuka, Kanagawa, 239-8686, Japan.

Abstract: The temporal structure of spike firing timing is considered to play an important role in information processing in the brain. In our previous studies, we have shown segmentation and feature linking of input images by using the chaotic cellular neural network to achieve chaotic synchronization of evoked spike sequences. The neuron model used to generate spike sequences with chaotic inter-spike intervals was based on the bifurcating neuron and described by the spike response model. The bifurcating neuron is a chaotic integrate-and-fire neuron that was introduced by Lee and Farhat (Neural Networks, 2001). Advantages of a chaotic spike sequence include its diversity and exponential decay of correlation function. By using these properties, we were able to distinguish different chaotic spike sequences and link identical chaotic spike sequences. In this study, decomposition of superimposed chaotic spike sequences was investigated from the viewpoint of neural information coding by employing a simple network model that we constructed using the bifurcating neuron. Bifurcating neuron dynamics are determined by the amplitude and phase shift value of its internal oscillator. Our network model consists of two types of neurons: a transmitter neuron and a receiver neuron. The transmitter neurons generate spike sequences with chaotic inter-spike intervals. The generated spike sequences are superimposed and inputted to the receiver neuron. The receiver neuron also generates spike sequences via its own dynamics and inputted sequences. The phase response curve determines if the response of the receiver neuron to the input spike is positive or negative, depending on the time from the last spike firing. The firing of the next spike occurs earlier for a positive response and later for a negative response. By employing numerical simulation, we constructed a phase response curve to achieve chaotic synchronization between the transmitter neuron and the receiver neuron, with the same phase shift value. In this presentation, we describe our network model and present the results of the numerical simulations. Then, we discuss the relationship between our results and information linking in the neural system.

ICCN 2017

128

Poster P21

HIPPOCAMPAL AND PREFRONTAL CORTEX NETWORK DYNAMICS ARE MODULATED BY SEROTONIN RECEPTORS AND

ANTIPSYCHOTIC DRUGS

T. Gener*, M. Alemany, and M.V. PuigHospital del Mar Medical Research Institute,

Barcelona Biomedical Research Park, 08003-Barcelona, Spain

Abstract: Cognitive deficits are a core clinical feature of schizophrenia (SCZ), but respond poorly to available medication. Thus, understanding the neural basis of these deficits is crucial for the development of new therapeutic interventions. The types of cognitive processes affected depend upon a dynamic communication between the prefrontal cortex (PFC) and hippocampus (HPC) that is likely accomplished via neural oscillations. Atypical antipsychotic drugs are more efficient than typicals in treating cognitive symptoms in SCZ. They bind preferentially to cortical serotonin 5-HT1A and 5-HT2A receptors while typicals are potent dopamine D2R antagonists. Here, we aim at understanding the PFC-HPC network dynamics underlying the cognitive amelioration mediated by atypical antipsychotic drugs and the role of the serotonin system. We investigated the actions of antipsychotic drugs and serotonin compounds on PFC-HPC neural oscillatory activity and synchrony in freely-moving mice exploring an open field. The following drugs were administered (IP): atypical antipsychotics clozapine, risperidone; typical antipsychotic haloperidol; 5-HT1AR agonist 8-OH-DPAT, antagonist WAY100635; 5-HT2AR agonist DOI, antagonist M100907. Our results show that 5-HT1AR activation with 8-OH-DPAT markedly reduces theta (8 Hz) and high gamma (50-100 Hz) oscillations in PFC and HPC and PFC-HPC phase synchronization, and these are reversed by WAY100635. Similar results were observed with clozapine, risperidone and haloperidol along with an exacerbation of delta waves (4 Hz); however, this was not reversed by WAY100635. This suggests that antipsychotic actions on PFC-HPC oscillations may not be mediated by 5-HT1AR during alert states, a result unexpected for clozapine. Thus, 5-HT1AR exert strong influences on theta and gamma oscillations in PFC and HPC and PFC-HPC connectivity. The reduction of theta and gamma oscillatory activity and the decrease of PFC-HPC connectivity observed after administration of all drugs may have a negative impact on cognitive processing. Ongoing work investigates the relevance of these effects for object recognition memory in the subchronic phencyclidine mouse model of SCZ. Ongoing work also explores the influences of 5-HT2AR drugs on PFC-HPC network dynamics to help dissect the role of the serotonin system in antipsychotic drug action.

Support: NARSAD Young Investigator Award to M.V. Puig.

ICCN 2017

129

Poster P22

CONNECTING MATHEMATICAL MODELING WITH ELECTROPHYSIOLOGICAL EXPERIMENTS: THE VIRTUAL

LABORATORIES SIMNERV AND SIMNEURON

A. Tchaptchet* and H.A. BraunInstitute of Physiology, Philipps University of Marburg,

Deutschhausstr. 2, D-35037 Marburg, Germany

Abstract: Experts in mathematical modeling often do not have many insights into the problems of experimental neurophysiologists while many electrophysiologists do not know how to make use of their data for mathematical modeling. Many attempts have already been made, also by our group, to overcome such obstacles to broader use of physiologically adequate mathematical simulations in direct relation to experimental data (Postnova et al., 2010 Pharmacopsychiatry 43 (Suppl. 1): S82-S91; Tchaptchet et al., Brain Res 1536: 159-167). Among others we have designed virtual laboratories like SimNerv and SimNeuron for experimentation in simplified but realistically appearing lab environments on the computer screen. All stimulation and recording devices are freely adjustable and mathematical algorithms guarantee for the physiologically adequate reactions of the virtual neurons and nerves, also considering their physiological diversity. These virtual laboratories have originally been designed for students’ experimentation in practical courses. However, it turned out that the laboratories can also provide new insights for experienced neuroscientists. For experimentalists it is important that the Hodgkin-Huxley type equations are given in a modified form which allows direct overtaking of the experimentally determined key values. The mathematicians can make their own voltage and current recordings to see how basic current- and voltage-clamp data from conventional experiments are reflected in the model parameters. Fully functioning demo versions can be downloaded from www.virtual-physiology.com. More information and demonstrations will be given at the poster.

Support: BM&T (Biomedizin und Technik GbR), Marburg Office (www.BMT-GbR.com).

http://www.virtual-physiology.com

ICCN 2017

130

Poster P23

MEDIAL PREFRONTAL CORTEX INVOLVEMENT ININTERACTIVE BEHAVIORS BETWEEN RATS

A.R. Conde-Moro*, F. Rocha-Almeida, R. Sánchez-Campusano,J. M. Delgado-García and A. Gruart


Abstract: The brains of social animals are continuously exchanging information and coordinating interdependent behaviors among the members of their groups. These interactions provide them with better strategies for feeding, mating, and protecting themselves from predators. To this day, many scientists have tried to reproduce interactive behaviors in the laboratory context, but the majority of these studies have been focused only on a behavioral level and the studies looking directly at brain activities that might be underlying these behaviors are still scarce. The main objective of this study is to identify the electrophysiological properties that allow animals to work together in order to obtain a common reward. For that aim we have developed a behavioral procedure to reproduce these behaviors in two customized adjacent Skinner boxes that were divided by a metallic grid. The experimental boxes are configured in a way that the two rats could see, smell and have limited physical contact through the grid. Rats were progressively trained to climb at the same time (and stay simultaneously for 2 seconds) on a platform in order to get food pellets for both of them. It took 4-5 days for them to learn to climb individually on the platform and another 5-6 days to do it simultaneously. This set up was also compatible with the in vivo electrophysiological recording of local field potentials (LFPs) throughout this task. Electrodes were implanted in the medial prefrontal cortex (mPFC, including cingulated, prelimbic and infralimbic areas) of all rats as these areas have been previously related with cooperative behaviors in humans and non-human primates. Preliminary results of the recorded LFPs indicate the selective involvement of the mPFC during interactive behaviors in rats, showing differences in the LFPs spectral power when the rats are climbing on the platform individually as opposite to when climbing on it simultaneously.

Support: Grant BFU2014-56692-R to A.G. and to J.M.D.-G.

ICCN 2017

131

Poster P24

COMPUTER SIMULATION OF NOISE EFFECTS IN THE NEIGHBOUR OFSTIMULUS THRESHOLD FOR A MATHEMATICAL MODEL OF

HOMEOSTATIC REGULATION OF SLEEP WAKE CYCLES

Wuyin Jin1, Qian Lin2, An Wang1, and Chunni Wang3

1School of Mechanical & Electronical Engineering, Lanzhou University of Technology, 730050 Lanzhou, China. 2Editorial Department of Journal of Lanzhou University of Technology, Lanzhou

University of Technology, 730050 Lanzhou, China. 3Departmentof Physics, Lanzhou University of Technology, Lanzhou 730050, China.

Abstract: The effects of noise, expectedly, seem to be less relevant when the neurons operate in spike generating regime for a suprathreshold, however, the situation is complete different in the neighbour of threshold where noise can induce significant changes of the impulse patterns, furthermore, in the central neural system, the neurons often work in the neighborhood of threshold, but neurons are heterogeneous and noise is inevitable. In this work, we study the spatiotemporal behaviors of noise effects in the neighbour of stimulus threshold for a mathematical model of homeostatic regulation of sleep wake cycles by hypocretin/orexin, which proposed by Svetlana Postnova, Karlheinz Voigt, and Hans Albert Braun (J. Biol. Rhythms., 2009, 24, 523), which are composed of neurons nearby the neighborhood of threshold. The effects of noise added to the stimulus, the conductance, the modulation function, and the activation variables are investigated respectively based on a circadian input skewed in sine function proposed by Serge Daan, Domien G. M. Beersma, and Alexander A. Borbéy (Am. J. Physiol. 246:R161-R178). The computer simulation results suggested that the regulatory mechanism of the model is collapsed and the coupled two neuron of the model show very irregular activities, it looks ‘terrified’ that fall asleep or loss sleep transform in nondeterminate time.

Support: National Nature Science Foundation of China (No. 11071029 and 11372122).

ICCN 2017

132

Poster P25

EFFECTS OF TEMPORAL INTEGRATION ON COMPUTATIONAL PERFORMANCE OF SPIKING NEURAL NETWORK

Fangzheng Xue1, Yang Zhang1, Hongjun Zhou2 and Xiumin Li 1*1College of Automation, Chongqing University, Chongqing 400044, China

2School of Economics and Business Administration, Chongqing University, Chongqing 400044, China

Abstract: In spiking neural networks (SNN) information is considered to be encoded mainly in the temporal patterns of their firing activity. Temporal integration of information plays a crucial role in a variety of cognitive processes, such as sensory discrimination, decision-making or interval timing. However, it is rarely considered in traditional computational SNN models. In this paper, we investigate the influence of temporal integration on the computational performance of liquid state machine (LSM) from two aspects: the synaptic decay constant and time delay from presynaptic neurons to the output neurons. LSM is a biologically spiking neural network model for real-time computing on time-varying inputs, where the high dimensionality of dynamical spikes are transformed into smoothly changing states through synaptic integration into the readout neuron. Our experimental results show that increasing the decay constant of synapses from SNN to the output neuron can remarkably improve the computational performance due to the enhancement of temporal integration. Moreover, transmission delays have an even larger impact on the richness of dynamical states, which in turn significantly increase the computational accuracy of SNN. These results may have important implications for the modelling of spiking neural networks with excellent computational performance.

Support: Grants from National Natural Science Foundation of China (No. 61304165 and No. 61473051), and Natural Science Foundation of Chongqing (No. cstc2016jcyjA0015).

http://topics.sciencedirect.com/topics/page/Decision-making

ICCN 2017

133

Poster P26

ABNORMAL FIRING RATE OF DEEP CEREBELLAR NUCLEI NEURONS IN LURCHER MICE IS RELATED WITH A POOR PERFORMANCE OF THE

CLASSICAL EYEBLINK CONDITIONING

J.C. López-Ramos1*, Z. Houdek2, J. Cendelín2, F. Vožeh2, J.M. Delgado-García1

1Division of Neurosciences, Pablo de Olavide University, ES-41013 Seville, Spain2Department of Pathophysiology Faculty of Medicine, Charles University, Pilsen, Czech Republic.

Abstract: Classical eyeblink conditioning is one of the experimental models more widely used for the study of the neuronal mechanisms underlying the acquisition of new motor and cognitive skills in behaving mammals. Currently, there are two different interpretations of the role of the cerebellum in the acquisition and storage of eyelid responses learned through classical conditioning. One of them proposes that the cerebellum is the place where this type of associative learning takes place and it is stored, while the opposite suggest that the cerebellum is involved in the proper performance of both palpebral reflexes and learned movements. Our aim was to check these two opposite theories, using for that the Lurcher mice, a well-known model of cerebellar degeneration (see Porras-García et al., Eur. J. Neurosci., 21, 979, 2006). Mice were prepared for classical eyeblink conditioning and for recording of the unitary activity of cerebellar interpositus neurons. Chronic electrodes for stimulation and recording were implanted in the eyelid, and a craniotomy was carried out in the cerebellar skull. Eyelid movements were recorded with the help of a magnet fixed to it, and with the help of a high velocity camera. Neurons were identified by their antidromic activation from the contralateral red nucleus. Animals were conditioned with a tone as conditioned stimulus, and an electric shock as unconditioned stimulus in simultaneity of the recording of interpositus neurons. Trace and delay conditioning were made. Results indicate a lower learning index in Lurcher mice, probably due to its higher muscle excitability. Antidromically identified interpositus neurons presented firing rates related with both reflex and conditioned eyelid responses. Its instantaneous frequencies were delayed with respect to the electromyography of their orbicularis oculi muscles, but not with respect to the proper muscle movement. This pattern was altered in Lurcher mice, in parallel with an important deficit for the proper execution of conditioned eyelid responses. The cerebellum seems to be related with the realization of the movement, more than with its acquisition.

Support: Grants BFU2011-29089, P07-CVI-02487 to J.M.D.-G.; and Grants BFU2011-29286, P07-CVI-02686 to A.G.

ICCN 2017

134

Poster P27

CORTICAL SLOW WAVE PROPAGATION PATTERNS AND NETWORK MEMORY IN DIFFERENT BRAIN STATES IN THE MOUSE

M. Dasilva1*, A. Pazienti3, M. Mattia3 and M.V. Sanchez-Vives1,2

1Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain. 2Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain. 3Istituto

Superiore di Sanità (ISS), 00161 Rome, Italy.

Abstract: Slow oscillations are present during slow-wave sleep and deep anesthesia and constitute the default mode of cortical activity upon which cognitive functions emerge during wakefulness. Studying the dynamics of the transitions from slow-wave activity to wakefulness or from deep to light anesthesia might therefore contribute to our understanding of the emergence of complex network dynamics underlying brain computations. Here we studied the generation and propagation of slow waves under different anesthesia levels and thus different brain states, by means of an array of 32 surface electrodes that cover a large part of one hemisphere of the mouse. The propagation of slow waves was detected relying on the multisite multiunit activity. For each wave, a matrix of time lags between local activation onsets was estimated that reflected the shape of the propagating activity wavefronts. The different spatial patterns of generation/propagation were clustered and their frequency and degree of diversity was quantified. The frequency of slow oscillations increased monotonically with the lightening of anesthesia, while the diversity of propagation patterns increased. Specifically, while in deep anesthesia we observed a dominance of two types of wavefronts regarding origin and direction of propagation for medium and lighter levels of anesthesia the diversity of waveform patterns increased, reflecting an increased excitability along with a higher richness of activity patterns. Interestingly, the intrinsic memory of the network increased for more excitable states, such that wavefronts revealed a larger dependence on the previous wave pattern. The mechanisms underlying both features will be discussed.

Support: Grants PCIN-2015-162-C02-01 (FLAG ERA) by MINECO to M.V.S.-V., and HBP SGA1 (WaveScalES) Contract 720270 by HUMAN BRAIN PROJECT to M.V.S.-V. and M.M.

ICCN 2017

135

Poster P28

BEHAVIORAL, ELECTRICAL AND MORPHOLOGICAL EFFECTSOF CHRONIC GROWTH HORMONE/IGF-I HYPERSECRETION

IN ADULT RATS

R. Leal-Campanario1*, J.F. Martin-Rodriguez2, V.D. Ramos-Herrero1, G. Gutiérrez-Parra1, Á. Flores2, A. Madrazo-Atutxa2, D.A. Cano2, A. Gruart1, J.M. Delgado-Garcia1, A. Leal-Cerro2

1Division of Neurosciences, Pablo de Olavide University, Seville, Spain2Institute of Biomedicine (IBiS), Virgen del Rocío University Hospital, Seville University, Seville, Spain

Abstract: Growth hormone (GH) and IGF-I play a significant role in the structure and functioning of developmental and mature brains. Moreover, selective neuroprotective and regenerative effects have been ascribed to GH and, particularly IGF-I, both in vitro and in vivo. Interestingly, chronic GH/IGF-I hypersecretion has been suggested to underlie cognitive deficits in acromegalic patients. Here, we aimed to test the hypothesis that chronic GH/IGF-I hypersecretion results in cognitive deficits by studying these functions in an animal model of chronic GH/IGF-I hypersecretion. Wistar Furth rats were injected (s.c.) with GH-producing GC cells to induce a GH-secreting tumor. Control rats were injected with PBS. In a group of tumor-implanted rats, tumor was surgically extirpated 8 weeks after cells injection. GH and IGF-I levels returned to normal levels upon removal of the tumor. Learning and memory functions were assessed with associative learning tasks 10 weeks after cells implantation. The tests included an appetitive operant conditioning and a passive avoidance task. The synaptic efficacy of hippocampal circuits (CA3-CA1 synapse) was assessed by inducing long term potentiation (LTP) in alert behaving rats (see Gruart et al., J. Neurosci., 2006). LTP was followed up to 4 days after its induction. Although the three groups of rat behaved similarly in an open field, tumor-bearing rats displayed better learning performances than both tumor-resected and control rats. In addition, tumor-bearing rats presented significantly larger and longer-lasting LTPs than control and tumor-resected animals. To determine whether increased neurogenesis could underlie improved LTP and learning performances, cell proliferation was analyzed by injecting rats with a daily dose of 5-bromo-2’-deoxyuridine (BrdU; 150 mg/kg) for 3 consecutive days. Immunohistochemical analysis in the subgranular zone of the hippocampus of doublecortin, MCM2/DCX, calretinin, calbindin and NeuN was performed. Results suggest that chronic GH/IGF-I hypersecretion did not increase hippocampal neurogenesis but promotes neuronal differentiation, migration and maturation.

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Poster P29

BEHAVIORAL AND COGNITIVE IMPAIRMENTS INDUCEDBY LOW DOSES OF MK-801 AND KETAMINE

M. Lovera-Ulecía*, L. Moreno-Lama*, M.Á. Gómez-Climent, J.M. Delgado-García, A. GruartDivision of Neurosciences, Pablo de Olavide University, 41013-Seville, Spain

Abstract: N-methyl-D-aspartate receptors (NMDARs) are ionotropic glutamate receptors with a key role in behavioral and cognitive processes. Disruption of NMDARs has been traditionally linked to several neurological diseases, including schizophrenia. NMDAR antagonists can be used as experimental models of symptoms associated to the neural disorders caused by NMDAR dysfunctions as well as in pre-clinical studies, to evaluate the effectiveness of potential antipsychotic drugs or cognitive enhancers. The effects of low doses (0.05, 0.1, and 0.2 mg/kg) of MK-801 (a non-competitive NMDAR antagonist) on motor and cognitive functions were assessed in adult mice. The three doses increased motor activities and evoked inverted-U prepulse inhibition changes, but only the two higher doses impaired associative learning, therefore allowing its application in pre-clinical studies of cognitive-related deficits. In addition, this study was aimed to determine the motor and behavioral effects produced by subanesthetic doses of ketamine in adult mice and the possibility of generating a mild cognitive impairment model for pharmacological purposes. We evaluated how low doses (5, 10, and 15 mg/kg) of ketamine affected the acquisition of an instrumental conditioning task, as well as its effect on motor and prepulse inhibition capabilities. Results of ketamine administration indicate a clear dose-dependent decrease of learning abilities, and motor and prepulse inhibitory effects at the higher dose. Thus, ketamine administration at these three doses can be used as a model of cognitive impairment and for the induction of schizophrenic symptoms. The expression of the GABA synthetic enzyme glutamic acid decarboxylase (GAD) and of the vesicular glutamate transporter (vGLUT) in the prefrontal cortex, striatum, and accumbens septi nucleus was modified by both learning and MK-801 and ketamine administrations. According to the collected results these two drugs could be used, at low doses, as experimental model of selective cognitive-involving diseases.

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Poster P30

VISSOR: AN ALGORITHM FOR THE DETECTION, IDENTIFICATION, AND CLASSIFICACION OF THE ACTION POTENTIALS DISTRIBUTED ACROSS

ELECTROPHYSIOLOGICAL RECORDINGS

C.R. Caro-Martín, J.M. Delgado-García, A. Gruart and R. Sánchez-Campusano*Division of Neurosciences, Pablo de Olavide University, 41013-Seville, Spain

Abstract: Pattern recognition of neuronal discharges is the electrophysiological basis of the functional characterization of brain processes, so the implementation of a spike-sorting algorithm is an essential step for the analysis of neural codes and neural interactions in a network or brain circuit. We developed an unsupervised automatic computational algorithm for the detection, identification, and classification of the neural action potentials distributed across electrophysiological recordings, and for the clustering of these potentials based on the shape, phase, and distribution features, which are extracted from the first-order derivative of the potentials under study. This algorithm was implemented in a customized spike-sorting software called VISSOR (Viability of Integrated Spike Sorting of Real Recordings). The validity and effectiveness of this software were tested by the classification of the action potentials detected in extracellular recordings of the rostro-medial prefrontal cortex (rmPFC) of rabbits during the classical eyelid conditioning.

Support: Grants from the Spanish MINECO (BFU2011-29286) and Junta de Andalucía (BIO122, CVI 2487, and P07-CVI-02686) to A.G. and J.M.D.-G; as well as the Grant BES-2012-052748 (Predoctoral fellowship from MINECO) to C.R.C.-M.

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Poster P31

ERFo, AN ALGORITHM FOR EXTRACTING A RANGE OF OPTIMAL FREQUENCIES OF AN ELECTROPHYSIOLOGICAL RECORDING

C.R. Caro-Martín1*, A. Gruart1, J. M. Delgado-García1 and A.E.P. Villa2

1Division of Neurosciences, Pablo de Olavide University, 41013-Seville, Spain2Neuroheuristic Research Group, University of Lausanne, 1005 Lausanne, Switzerland

Abstract: Signal filtering is a crucial step in the analysis of raw electrophysiological recordings. This process is important to eliminate frequency components associated with noise and recording artefacts. Two problems should be addressed: what is the optimal frequency range of the signal and which frequency values (extreme values, maximum and minimum) are characteristic of the raw signal power spectrum. We developed an algorithm called ERFo (Extractor of Range for Filtering optimization). This algorithm determines the frequency range boundaries meant to be optimal for the observation of the spectrum with the largest power in the range of interest. The regular differentiations (first and second derivatives) of the raw signal are used to detect the maximum and minimum amplitudes, which are reported in the algorithm to determine the frequency range of the raw signal filtration. The regular differentiations were calculated by a convolution between the regular differentiations of kernel function with the raw signal. In particular, this algorithm can be used for off-line analysis of extracellular electrode recordings to attend of the most optimal filtering as a pre-processing stage for waveforms spike sorting of single units.

Support: Grants from the Spanish MINECO (BFU2011-29286) and Junta de Andalucía (BIO122, CVI 2487, and P07-CVI-02686) to A.G. and J.M.D.-G; as well as the Short-term training fellowship (EEBB-I-16-10562) to C.R.C.-M.

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Poster P32

POSTNATAL DEVELOPMENT OF SLEEP-WAKE CYCLE IN NORADRENALIN DEFICIENT MICE: INVOLVEMENT IN LEARNING

E. Domínguez-del-Toro* and A. Prados-PardoDivision of Neurosciences, Pablo de Olavide University, 41013-Seville, Spain

Abstract: Many neurological disorders affecting considerably the population, such as ADHD, epilepsy or Parkinson’s disease concern a nucleus of the brainstem: The Locus Coeruleus. This fact motivates the study of the noradrenergic system, its normal functions and how different lesions are involved in diverse diseases. Ear2 mutant mice are born and survive with the absence of more than 70 % Locus Coeruleus’ neurons. These mice have been demonstrated to present a functional impairment of the forebrain clock during adulthood. Considering that this area is involved in the regulation of the sleep-wake cycle also in young animals (and also proposed as possible regulators of different processes involved in cortical maturation), the aim of this work is to study how the respiratory and sleep parameters are affected by neuronal loss of the above mentioned region during early postnatal development. For such purpose, oxygen consumption, the electrical activities at the neck muscles, heart and brain of Ear2 mutant mice have been registered during the two first postnatal weeks. Oxygen consumption (ml/g/min) was measured daily. On the day of electrophysiological recordings, at P3, P7, P10 or P14 and under anaesthesia (hypothermia), the pup was implanted with two EMG hook recording electrodes aimed to the nuchal muscle, with two ECG recording electrodes in the chest and two EEG electrodes (only at P14). After recovery for at least 1 h in a humidified incubator maintained at thermoneutrality (35°C), electrodes (together with ground ones) were connected to differential amplifiers (Biopac MP35) and signals were recorded for 1 hour. EMG, ECG and EEG signals were digitized at 1 kHz with BSL 3.7 software. The EMG and EEG signals for each subject helped us to distinguish between REM sleep, no-REM sleep and wakefulness. The main output of this study is that Locus Coeruleus’ neuronal loss affects the sleep-wake cycle maturation. As a result, at P14 we observe a reduction of time spent in NoREM sleep and an increase in time spent in REM sleep, together with an increase in Heart Rate and in oxygen consumption. We conclude that noradrenergic system controls these activities during the second postnatal week.

Support: Grant BFU2014-56692-R.

ICCN 2017

140

Poster P33

SYNCHRONY AND RHYTHM IN A SMALL WORLDCORTICAL NEURAL NETWORK

Xia Shi, Zhiheng LiuSchool of Science, Beijing University of Posts and Telecommunications,

Beijing 100876, China

Abstract: Neural synchronization is known to play a crucial role in many physiological functions such as information binding and wake-sleep cycles. The synchronization of neuronal signal was proposed as one of the mechanism to transmit and code information in the human brain. In this paper, we mainly study the brain rhythm and synchronous activity in a small world cortical neural network, which is modeled by the Izhikevich neuronal model. We used the regular spiking cells and the chattering cells to describe the excitatory neurons and the fast spiking cells to model the inhibitory neurons. Numerical results show that by tuning four key parameters, the ratio of excitatory to inhibitory neurons, the connection weights of the excitatory neurons, the synaptic connection probability and the number of nearest neighbor of each code, the system will exhibit various synchronization status. In addition, what is important is that the change of synchronization status is in accordance with the brain rhythm. When the system reach the complete synchronization, the main rhythm is always the theta rhythm. Our results might give significant implications to understand the brain rhythm and the synchrony in the cortical neural network.

Support: National Natural Science Foundation of China (Grant No. 11272065).

ICCN 2017

141

Poster P34

PRECISION CONTROL OF BIOLOGICAL REACTION-DIFFUSSION NETWORK BY USING SYNCHRONIZATION

Jianwei Shen, Lingli Zhou, Linan GuanInstitute of Applied Mathematics, Xuchang University,Xuchang, Henan 461000, China

Abstract: In this work, we will investigate how to control expression of cancer cell in neural network. We address that there is signal transmission between cancer cell and drug molecules via synchronous control. In our study, we assume first that the movement of cancer cell is a random walk process in the plane, which can be described by Langevin equation, and we can derive the corresponding probability density equation. In addition, we use reaction-diffusion equation to express the concentration change of drug molecules. We know that vesicles can be combined with the outer membrane of cells to release the cargo which plays a role of signal transmission in fact, the process of vesicle docking with their target membrane is a synchronization process. Then, based on this principle, we controlled the above two dynamical systems to realize the synchronization between them which represents an effective drug treatment process. We believe this synchronous control mechanism is reasonable and two examples are given to illustrate the correctness of our results obtained in this paper.

Support: Grants from National Natural Science Foundation of China (Nos. 11272277, 11572084) and Innovation Scientists and Technicians Troop Construction Projects of Henan Province, China (Grant No. 2017JR0013).

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142

Poster P35

MULTIPLE EPILEPTOGENIC FOCI CAN PROMOTE SEIZUREDISCHARGE ONSET AND PROPAGATION

Denggui Fan1 and Qingyun Wang2

1School of Mathematics and Physics, University of Science and Technology, Beijing 100083, P.R. China. 2Department of Dynamics and Control, Beihang University, Beijing 100191, P.R. China.

Abstract: Clinical electroencephalogram (EEG) of focal seizures shows that the cerebral cortical local neurons are first activated (epileptic foci), followed by rapid synchronous discharges which then rapidly spread to the surrounding normal brain regions. Based on a spatially-extended computational model of cortical electric activity with realistic mesoscopic connectivity, we reconstructed the single epileptic focus and multiple epileptic foci by activating the activity level of local neuronal cluster with single-pulse stimulation disturbance, to simulate the physiologically observed synchronous brain activity of epileptogenic focus onsets and propagations. Results show that single epileptic focus with smaller excitatory activity region fails to spread into the surrounding brain regions, except for transient propagation to the neighborhood which eventually disappears with the recession of activity energy. However, as the excitatory activity region corresponding to the single epileptic focus getting larger, the synchronous oscillations of adjacent neuronal populations can not only be successfully initiated, but also can propagate to the surrounding farther normal brain regions, due to the local and remote feedforward excitatory connectivities. This can ultimately cause a comprehensive onset of focal epilepsy. In particular, to investigate the effect of multifocal seizures on the propagations of epileptic onsets, we divided the large single focus into three equal multifocal regions. Detailed investigation reveals that compared to the single epileptic focus multifocal seizure onsets are more easily to promote the generalized epileptic seizures and increase the spreading speed of synchronous oscillations of epileptic seizures.

Support: National Natural Science Foundation of China (Grant Nos. 11325208, 11572015 and 11172017), the Project funded by China Postdoctoral Science Foundation (Grant No. 2016M600037) and the Fundamental Research Funds for the Central Universities (FRF-TP-16-068A1).

ICCN 2017

143

Poster P36

COHERENCE-BASED CODING IN SPIKING NEURAL NETWORKWITH GLOBAL INHIBITORY FEEDBACK

Jinli Xie, Qinjun Zhao, and Jianyu ZhaoSchool of Electrical Engineering, University of Jinan, 250022 Jinan, China

Abstract: Neuronal signaling between neurons can be regulated through synaptic connections. It is widely assumed that the amplitudes of neural response depend on presynaptic history. We focus on the coherence-based coding properties in this study, and investigate how global inhibitory feedback shapes information transmission in spiking neural networks. Numerical simulations and computed input-output transfer functions are used to determine the coding properties and show the changes in network response amplitude resulting from feedback interact with the related effects of inhibitory synapses. The coherence is decreased with respect to the feedback modulation of the network, suggesting that the inhibitory feedback is capable of low-pass filter characteristics. More importantly however, the overall coherence drops with increasing feedback gain, while the mutual information per spike remains about the same. The nearly invariable values of mutual information per spike can be explained by the compensation of the varying mean firing rate. Our results further indicate that the transmission time of inhibitory synapses also plays key role in modulating the coherence. The monotonic coherence improves as the transmission time increases. The mutual information per spike keeps almost constant with growing transmission time because of the enhanced firing rate. Thus, inhibitory feedback that control the firing state of postsynaptic neurons can be significantly in altering the network coding property.

Support: National Natural Science Foundation of China (Grant No. 61203375).

ICCN 2017

144

Poster P37

NEURAL GENERATOR OF THE N2 COMPONENT FOR ABSTINENT HEROIN ADDICTS IN A DOT-PROBE TASK

Hongqian Li1, Qinglin Zhao1, Bin Hu1, Yu Zhou1 and Quanying Liu2

1Laboratory of Ubiquitous Awareness & Intelligent Solutions, Lanzhou University, 730000-Lanzhou, China.2Neural Control of Movement Laboratory, ETH Zurich, 8057 Zurich, Switzerland.

Abstract: Target-elicited N2 component of event-related potential (ERP) has been considered to be involved in target detection in the attentional processes. We aim to link the target-elicited N2 in a dot-probe task and the drug-related attention bias in heroin dependence, and further estimate the brain regions involved in the generation of the target-elicited N2. We recorded 64-channel electroencephalograms (EEG) from 17 abstinent heroin addicts (AHAs) and 17 healthy controls (HCs) during the dot-probe visual task. Individual N2 sources were localized using exact low resolution electromagnetic tomography (eLORETA). Compared to HCs, AHAs generated larger N2 amplitude in both congruent and incongruent conditions, suggesting that target detection processing in AHAs might require more attention resources. Moreover, N2 component was mainly generated in the Brodmann areas (BAs) 7, 23, 24, 31, 30, 32 and 40, implying that the frontoparietal cortex played a critical role in target detection processes.

Support: National Basic Research Program of China (973 Program) (No.2014CB744600), the Program of International S&T Cooperation of MOST (No.2013DFA11140), the National Natural Science Foundation of China (grant No.61210010, No.61632014), the National key foundation for developing scientific instruments (No.61627808), Program of Beijing Municipal Science & Technology Commission (No.Z171100000117005).

ICCN 2017

145

Poster P38

SELF-ASSEMBLY OF CORTICAL NETWORKS AND THERESULTING COGNITIVE FRAMEWORK

James J. WrightDepartment of Psychological Medicine, School of Medicine,

University of Auckland, Auckland, New Zealand

Abstract: During fetal development the growth of neurons in the embryonic cerebral cortex leads to a system able to begin adaptive learning immediately after birth. The dividing neuron precursors in the developing cortex fire synchronously with each other, and if prevented from doing so they die. It is assumed that the group of surviving cells is that which obtains the maximum resources by their cooperative activity, and minimizes the metabolic cost of their growth. Thus the maximization of synchrony and the minimization of axonal lengths act as evolutionary selection pressures in the growing cortex. Simulations of growth show that meeting these constraints results in final arrangements of neuron cell bodies and synapses, and cell responses to stimuli, reproducing those seen in both columnar and non-columnar cortex of higher vertebrates. The dynamic mechanisms involved in the simulated development include equilibria of pulse exchange in synchronous oscillation, and metabolic entanglement of synaptic dynamics operating under STDP and BCM rules of synaptic modification, as well as topology of “ultra-small-world” axonal connections. The same mechanisms, extended into the post-natal world of sensory and motor activity, may explain much of mature cortical information processing, since the antenatal order offers a framework upon which post-natal learning can systematically develop. This would enables representation of complete spatiotemporal sensory images, rather than “features”, and similar mechanisms may be general to all sensory modes and motor outputs. Groups of cells firing in synchrony linked by dynamic synapses, are logically equivalent to the point attractors of attractor neural networks, and convergence to these attractors with metabolically entangled synapses bears some analogy to quantum computing. When interactions between cortical areas and cortical/subcortical interactions are also included, properties of general computation and self-supervision of learning are also implied.

IV. GENERAL INFORMATION

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1. Information for plenary lectures and presentersLecturers should make their presentation in about 45 minutes. This will allow some extra time for a few questions. Presenters should note that the total time assigned to plenary lectures is 1 hour. In accordance, restrict your introductory words to a minimum. They could allow a few questions at the end of the lecture only in the case that the time schedule make it possible.

2. Information for symposium organizersSymposium organizers are expected to arrive at the session room 15 minutes before the session begins, and check the attendance of speakers in the session. Power point presentations should be stored in the expected presentation order in the computer provided by the Organization. In order to avoid projection problems, the use of private computers will be not allowed.Please note that, independently of the number of people participating in it, the maximum time allowed to each symposium is 2 hours. In accordance, please inform to the participants in your symposium the time allowed for their respective presentations.

3. Information for speakersSpeakers invited for an oral presentation in the different symposia should contact the organizer of the symposium for details of presentation order and time, as well as for the time allowed for his/her presentation. Please, go 10 minutes in advance to the beginning of your session with your PPT or PDF file to be stored in the proper order in the computer provided by the Organization.

4. Information for poster presentersApart for the plenary lectures and symposium presentations, we will have no more oral presentations. Posters will be permanently displayed along the whole Meeting, allowing a long time for questions and discussions. Nevertheless, poster presenters should be available nearby their posters at the times reserved for the six poster sessions. Please note that poster size has to be 120 cm high and 80 cm wide.

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noteS

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