ABSTRACTS

NAME ABSTRACT TITLE

Takaoki Kasahara Molecular Basis of Bipolar DisorderShangkai Gao EEG Pattern Analysis and its Application in Brain

Computer InterfaceNihar Ranjan Jana Co-chaperone CHIP associates with expanded polyglutamine

protein and promotes their degradation by proteasomesSoo-Young Lee A Roadmap to the Artificial Brain and ‘OfficeMate’Min W. Jung Learning and memory in the prefrontal cortexShi-Yong Huang Pre- and post-synaptic factors both contribute to the modification

of synapses between retinal neuronsManho Kim Huntington’s disease: molecular mechanisms of

neurodegeneration and treatment for brain repairToru Aonishi Effect of Backpropagating Action Potential on Neural InteractionLatika Singh Variability in Spectro-Temporal Features: a Developmental Study

of Speech in Children

Qinye Tong How to Understand Neural Coding?Key-Sun Choi A Computational Causality for Explanatory Language

Understanding

Masumi Ishikawa A new approach to localization and navigation of mobile robots - Effective Bayesian estimation and reinforcement learning.

Kyungjin Kim Neurobiology of StressPrasun Roy Can Stochastic Resonance Imaging be a substitute for high-priced

Gadolinium scan in India?

Bao-Ming LI Regulation of Prefrontal Cortical Functions by Alpha-2-adrenoceptors: Its possible relevance to Attention Deficit Hyperactivity Disorder

Teiichi Furuichi Deciphering the genetic basis of mouse cerebellar developmentPrabodh Swain MAPK regulates phosphorylation of Neural Retina Leucine

Zipper: A Key Regulator of Rod Photoreceptor Differentiationand Function

Tao Zhang Examine synchrony of the relationship between blood pressure(BP) and renal sympathetic nerve activity (RSNA) in response tohaemorrhage in Wistar rats.Examine synchrony of the relationshipbetween blood pressure (BP) and renal sympathetic nerve activity(RSNA) in response to haemorrhage in Wistar rats.

Xin Tian From Neural Firing to Hypersynchronous Discharge in the Cortexof Epileptogenic Focus

Hiroyuki Kamiguchi The Role of Ankyrins in Neurite Growth and Polarization

Kiyotoshi Matsuoka Blind Separation of Sound Sources in Real-World SituationsSupriya Ray Neural Control of Saccade SequencesYisheng Zhu Monitoring Ischemic Brain Injury Using Nonlinear MethodsJong-Hye Han Neuroanatomical Analysis for Onoamtopoeia and Phainomime 

Words:  fMRI Study

POSTERS

NAME POSTERLing Yin Neuroinformatics and Data SharingKeiji Kamei Improvement of reinforcement learning of a mobile

robot using sensors and a genetic algorithmPaulito Palmes Robustness, Evolvability, and Optimality of Evolutionary

Neural NetworksChoong-Myung Kim

Korean Sentence Processing Mechanisms reflected on ERP patterns

Kyoungho Suk Signal transduction of auto-regulatory microglial apoptosis

Kyung-Joong Kim Informal Inference based on the Integration of Multiple Neural Networks

Michelle Jeungeun Lee

Unsupervised Extraction of Video Features for Lipreading

Su-Yong Eun Glutamate receptor-mediated signaling and the functional implication in microglial cells

Woong Sun Programmed cell death of adult generated hippocampal neurons is mediated by the pro-apoptotic gene Bax

Reddy P. Kommaddi

Biotransformation of drugs mediated by brain-specific splice variants of the drug-metabolizing enzyme, Cytochrome P450

Molecular Basis of Bipolar Disorder

Takaoki Kasahara, Tadafumi KatoLaboratory for Molecular Dynamics of Mental Disorders

RIKEN Brain Science Institute, Japan

Bipolar disorder, previously known as manic depressive illness, affects approximately 0.8% of the population and causes severe psychosocial impairment. High concordance rate of bipolar disorder in monozygotic twins (approximately 70%) suggests the role of genetic factors in this disorder.

Altered energy metabolism in the brains of patients with bipolar disorder has been reported using phosphorus magnetic resonance spectroscopy (31P-MRS). Some of the 31P-MRS findings in bipolar disorder, such as reduced phosphocreatine levels, were similar to those reported in patients with a mitochondrial disorder, i.e. mitochondrial myopathy, chronic progressive external ophthalmoplegia (CPEO). Autosomal dominantly inherited CPEO is caused by deletion of mitochondrial DNA (mtDNA) due to the mutations in the nuclear genome-encoding genes responsible for maintenance of mtDNA; mtDNA polymerase (POLG), adenine nucleotide translocator (ANT1), and mtDNA helicase (TWINKLE). All three types of diseases are accompanied by depression or bipolar disorder. Multiple deletions of mtDNA in the brain were also reported in Wolfram disease, which is another inherited disease and frequently accompanies bipolar disorder. These findings altogether suggested that bipolar disorder is related to mitochondrial dysfunction caused by accumulation of mtDNA deletions.

To clarify the role of mitochondrial dysfunction in bipolar disorder, we are currently studying pathology of bipolar disorder using molecular genetic and cellular physiological approaches. We identified several mtDNA mutations/polymorphisms significantly associated with bipolar disorder. Among them, 3644TC mutation (odds ratio = 10.4) altered a conserved amino acid residue in one subunit of the respiratory chain machinery, and cells containing the mtDNA mutation had reduced mitochondrial membrane potential. We also generated genetically engineered mice with neuron-specific accumulation of mtDNA mutations and deletions. Some preliminary results demonstrated that the mutant mice showed bipolar disorder-like symptoms. Therefore the mice will help us to understand the pathophysiology of bipolar disorder as well as to develop mood-stabilizing drugs.

EEG Pattern Analysis and its Application in Brain Computer Interface

Shangkai Gao, Xiaorong Gao, Zhiguang Zhang, Bo Hong, Fusheng YangDepartment of Biomedical Engineering, Tsinghua University, Beijing 100084, China

A brain-computer interface (BCI) is a communication channel directly connecting the brain to a computer or other external devices. BCI will be very useful for the people with severe motion disabilities.

A variety of brain signals, such as scalp EEG, cortex EEG or direct neuron activity, could serve as the original messages in a BCI system. Among them, scalp EEG-based BCI systems are probably the most acceptable systems for practical use because of its non-invasive property.

However, the EEG signals recorded from the scalp are very week with low signal-to-noise ratio and low spatial resolution due to the low conductivity of the skull and the ambient noises. It seriously restricts the development of practical BCI systems. It is commonly agreed now that the electric activities in the brain are functionally located at different regions and they are synchronized in a cooperative way. To extract task-related information buried in multi-channel scalp EEG, we propose several spatio-temporal pattern analysis methods for scalp EEG analysis. In this paper, an integrated framework of scalp EEG signal processing in BCI system is presented. The algorithms of signal pre-processing, feature extraction and classification are described in detail. Many of them have successively applied in the BCI system developments.

Co-chaperone CHIP associates with expanded polyglutamine protein and promotes their degradation by proteasomes

Nihar Ranjan Jana1, Priyanka Dikshit1, Anand Goswami1 and Nobuyuki Nukina2

1Cellular and Molecular Neuroscience Laboratory, National Brain Research Centre,Manesar, Gurgaon - 122 050,Haryana, India

2Laboratory for Structural Neuropathology, RIKEN Brain Science Institute,2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan.

A major hallmark of the polyglutamine diseases is the formation of neuronal intranuclear inclusions (NIIs) of the disease proteins that are ubiquitinated and often associated with various chaperones and proteasome components. But, how the polyglutamine proteins are ubiquitinated and degraded by the proteasomes are not known. Here, we demonstrate that CHIP (C-terminus of hsp70 interacting protein) co-immunoprecipitates with the polyglutamine-expanded huntingtin or ataxin-3 and associates with their aggregates. Transient over expression of CHIP increases the ubiquitination and the rate of degradation of polyglutamine-expanded huntingtin or ataxin-3. Finally, we show that over expression of CHIP suppresses the aggregation and cell death mediated by expanded polyglutamine proteins and the suppressive effect is more prominent when CHIP is over expressed along with Hsc70.

A Roadmap to the Artificial Brain and ‘OfficeMate’

Soo-Young LeeBrain Science Research Center, Department of BioSystems, and Department of EECS

Korea Advanced Institute of Science and Technology, Korea

The Korean Brain Neuroinformatics Research Program got into the 3rd phase from June 2004 for 4 years, which is regarded as the final phase of Korean brain national research program started from November 1998 for 10 years sponsored by Ministry of Science and Technology. In the 3rd phase, in addition to the continuing development of engineering models on functional artificial systems for vision, auditory, inference, and behavior, we would like to develop a “Artificial Brain” to combine all the 4 functions and an integrated demonstration system, i.e., “Artificial Secretary” alias “OfficeMate” with exceptional human-like information processing capabilities.

We will develop an integrated hardware and software platform for the brain-like intelligent systems, which combine all the technologies developed for the brain functions in the second phase. With 2 microphones, 2 cameras (or retina chips), and one speaker, the Artificial Brain will be able to see, hear, speak, and think. The sound localization, speech enhancement, visual attention, face recognition, lip reading, and emotion recognition and representation will be included. The Artificial Brain will have proactive self-learning capability to develop his/her intelligence by estimating his/her current status, asking good questions to the right persons, and incorporating the answers into his/her knowledge. The ability of user modeling will also be included for practical user interfaces.

With this platform, we plan to develop a testbed application, i.e., “OfficeMate.” The OfficeMate may be regarded as an Artificial Brain specifically trained for the job of secretarial and administrative works. He/she will be able to receive phone calls, adjust schedules, and prepare draft documents for me.

The scientific and technical challenges are enormous. The understanding on brain information processing mechanism is very very limited, and we will need exercise our imagination and educated guesses to fill up the missing holes. During the last 6 years we have developed information-theoretic algorithms for the biological information processing in the human auditory pathway. We will further extend this approach to the audio-visual processing, knowledge representation and processing, and mental development through proactive learning.

Intelligence to Machines! Freedom to Mankind!

Learning and memory in the prefrontal cortex

Min W. Jung Neuroscience Laboratory, Institute for Medical Sciences,

Ajou University School of Medicine, Suwon 443-721, Korea

Modifying behavioral strategies in accordance with changes in environment is extremely important for survival. The prefrontal cortex (PFC) is likely to play a crucial role in this adaptive process considering that one important function of the PFC is the planning of future behaviors. In order to investigate neural mechanisms by which the PFC adaptively modifies its activities based on past experience, we investigated learning-induced changes in neural activity and synaptic plasticity in rat PFC. Single neuron recording studies in behaving animals revealed that PFC neural activities change rapidly in parallel with behavior learning. Moreover, correlations among neurons were altered in the process of learning, and long-term potentiation was induced by high-frequency stimulation in sensory cortical projections to the PFC. These results suggest that synaptic weights are modified within the PFC in the process of new task learning so that neural activity changes dynamically as an animal learns a new behavioral strategy. Same neurons exhibited different activity patterns but correlations among neurons were similar across two different behavioral tasks, suggesting that multiple behavioral strategies are represented in an overlapping, distributed manner in the PFC neural network. These studies stress the importance of learning and memory as an essential component of the PFC functions.

Role of GAP-43 in Differentiation of Cerebellar Granule Cells

R Mishra, K F Meiri# and S ManiNational Brain Research Centre, Manesar,Gurgaon-122050, Haryana, India

#Tufts University School Of Medicine, Boston, USA

GAP-43 is a nervous system specific protein that plays an important role in regulating growth cone responses to extracellular signals. GAP-43 is expressed as early as E9.5 in mouse, which implicates its possible role in neurogenesis. All GAP-43 (-/-) mice display abnormal foliation of specific lobules at the cerebellar vermis, a defect that is apparent from the day of birth. Further, GAP-43 knockout mice have smaller cerebella and reduced size of external granule cell layer. We investigated whether the reduction in EGL was due to reduced cell proliferation. Using whole cerebellar cultures from P4 wild type and knockout mice we show that there is a two-fold increase in BrdU labeled cells in the knock out cultures as compared to the wild type cerebellar cultures. We also show that proliferation response to bFGF when added to the defined culture medium is greater in wild type cerebellar cultures than for the knockout cultures. Similarly the proliferation response to Shh, an important factor that regulates granule cell proliferation in the developing cerebellum, was also reduced in the knockout cultures as compared to wild type cultures. We are currently testing the hypothesis that the increase in BrdU labeled cells seen in the knockout is due to a pertubation in cell cycle length. Taken together with the decreased response of knock out cerebellar cells to extracellular signaling molecules, this in turn could lead to abnormal EGL formation and foliation. We are also investigating whether increased apoptosis in the absence of GAP-43 could contribute to a reduced EGL in the knockouts.

Supported by: 1R03TW006050 (Fogarty International Award) KFM & SM

Pre- and post-synaptic factors both contribute to the modification of synapses between retinal neurons

Shi-Yong Huang1 & Pei-Ji Liang2,CA

1. Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences320 Yue-Yang Road, Shanghai 200031, China

2. Department of Biomedical Engineering, Shanghai Jiao Tong University1954 Hua-Shan Road, Shanghai 200030, China

There are three types of cooperative phenomena in synapses between cones and horizontal cell found in our laboratory. 1) Repetitive red flashed increase the R/G horizontal cell’s response amplitude to red light; 2) Repetitive red flashes progressively strengthened the synaptic connection between red-cone and luminosity-type horizontal cell (LHC); 3) A dim red background light greatly enhanced the response amplitude of LHC to green test flash, and vice versa. Present study suggested that the mechanisms involved in these phenomena were different between each other. Pharmacological evidence indicated that the activation of D2 receptor might be responsible for the red flickering induced responsiveness enhancement in the R/G HC, and that the potentiation of red response in LHC is attributed to the change of the postsynaptic intracellular calcium concentration, and that the mutual color enhancement in LHC is related to glutamate transporter and the activation of mGluRs located at the presynaptic terminals of cone. The synapses between photoreceptors and LHC also have a competitive side: when synapses between red cone and LHC grown stronger and prosper after repetitive red flashes, other synapses between green cone and LHC were instead weakened, and vice versa. However, there is still no evidence to clarity the mechanism(s) involved in the competitive suppression in LHC. Taken together, red and green cone afferents interact on the horizontal cell, and different cellular mechanisms are involved in the competition and cooperation.

Acknowledgements: This research was supported by grant from the National Foundation of natural Science of China (No. 30170263).

Huntington’s disease: molecular mechanisms of neurodegeneration and treatment for brain repair

Manho KimDepartment of Neurology Seoul National University, Seoul, Korea

Huntington's disease (HD) is a fatal, genetically based neurodegenerative brain disorder in which a loss of neostriatal neurons is a main characteristic. The CAG trinucleotide repeat mutation encoding an expanded polyglutamine tract induces progressive deficits in intra- and inter-cellular signaling, and subsequent disease symptoms.

Altered protein interaction has been first proposed as the main mechanism of neurodegeneration. Thereafter, intranuclear or intracellular aggregates, proteolytic cleavage of huntingtin (cf. caspase, calpain), altered transcription or other signalling deficits were reported. Recently, stem cell transplantation is of benefit to protect neurons against neurodegeneration as well as recover the functional deficit in the experimental HD model.

This presentation focuses on the current knowledge of molecular mechanisms of neurogeneration in HD and the use of this information to identify potential therapeutic targets.

Effect of Backpropagating Action Potential on Neural Interaction

Toru Aonishi 1, Hiroshi Miyakawa 2, Masashi Inoue 2, Masato Okada 3

1Tokyo Institute of Technology, RIKEN Brain Science Institute, Japan2 Tokyo University of Pharmacy and Life Science

3RIKEN Brian Science Institute, University of Tokyo, PRESTO

It is a serious problem that the information could not be shared with physiologists and theorists in the brain science. Theorists and physiologists do not have the common language to express the nerve system, because they have different backgrounds. In our research group, by sharing mathematical neuron models through a common platform refereed to as NEURON simulator, we try to collaborate with those who have different backgrounds. By such new style of collaborations, we elucidate roles of the dendritic backpropagating action potential in the neural interaction.

The membrane can be modeled by the parallel circuit that consists of inward currents and outward currents with nonlinear I-V relations. If the balance between the inward current and the outward current is satisfied, there is a singular point where the effective membrane impedance diverges to infinity. This kind of singularity is universal in nerve membranes. By using NEURON simulator, we show a dramatic change of EPSPs by regulations of outward currents in backpropagating states. This phenomenon reflects the singularity of the membrane impedance. From a picture of such extreme phenomenon, we can elucidate roles of the dendritic backpropagation in the neural interaction. Next, we observe phase response curves of a neuron in oscillatory states. This experiment includes previous experiments for EPSP modulations in backpropagating states, and thus the effect of such extreme phenomenon on network dynamics can be elucidated.

Variability in Spectro-Temporal Features: a Developmental Study of Speech in Children

Latika Singh and Nandini C. SinghNational Brain Research Centre, Manesar, Gurgaon-122050, Haryana, India

  

We carried out a study to examine the variability in the acoustic properties of speech for normally developing children. We measured and compared the joint spectral and temporal features by estimating modulation spectra. These modulation spectra were obtained by calculating the two-dimensional Fourier transform of the autocorrelation matrix of the speech signal in its spectrographic representation. Various parameters were determined to quantitatively study the changes in these features and results revealed significant differences that might be related to learning that occurs during development. The results show increase in separability as a major trend associated with speech development in normal children. Between ages 3 and 5, separability increases rapidly moving towards adult speech, which is quite separable. Reduction in modulation depth with age is another important parametric change. It is in accordance with previous studies showing decrease in temporal and spectral parameters during development. The examination of such characteristics in children provides us with information on how these parameters of speech are acquired and mastered as a function of development and could lead to newer insights to corresponding anatomical and neuromuscular development.

How to Understand Neural Coding?

Qinye Tong and Guang LiDepartment of Biomedical Engineering, Zhejiang University,

Hangzhou 310027, PR China

Eric R Kandel put an end to the development of neuroscience over last one hundred years [1]. He mentioned in the finis: Physicists and chemists have often distinguished their disciplines from the field of biology, emphasizing that biology was overly descriptive, atheoretical, and lacked the coherence of the physical sciences. This is no longer quite true. By “This is no longer quite true”, Eric R Kandel referred to the emergence of molecule and cellular neurobiology. Admittedly, analysis of biochemical processes such as neurotransmitter, ion channel already brought us clear results, yet it is useful to understand neural information. The change of molecule element in neurons does influence the work of the whole neural system, just as the deteriorated resistance will reduce the picture quality. However, the chemical composition of the resistance and the picture are different concepts in two strata, in other words, they are two things. Hence, even if the molecule and cellular neuroscience is consummate one day, the main work of neuroinformatics will still be qualitative description.

Gilles Laurent put a paragraph in his article in the journal “SCIENCE”: Studying a neural code requires asking specific questions, such as the following: What information do the signals carry? What formats are used? Why are such formats used? Although superficially unambiguous, such questions are charged with hidden difficulties and biases.

We believe that, in order to bring neuroinformatics from qualitative description to rational analysis. To change “hidden difficulties and biases” in neural coding, an essential problem (problem in conception) need to be solved. From the ideas of traditional engineering technique, it is unbelievable that an unstable instrument can precisely measure small signal. On the contrary, the olfactory receptors in the dog’s olfactory system finish their rebirth in 35 to 45 days. It is amazing that such an unstable system could have outstanding sensitivity – the dog can differentiate odors from several kilometers away. From the nonlinear viewpoint, the traditional concepts about engineering technique are all linear which emphasize on stable, balanced, orderly, deterministic and coincident aspects. But biology system is nonlinear which emphasize on unstable, unbalanced, chaos, indeterminate and inconsistent aspects. These two ideas are totally opposite to each other. To study the mechanism of neural coding, we should discard linear views and learn to use nonlinear concepts to analyze problems.

Our opinion is neural information is processed in the stratum of neural network composed of neuron connection, not in molecule level nor the neuron ensemble level. A series of neural impulse represent the neural information. There are underlying rules in this neuron induced impulses, which is determined by nonlinear dynamics. Therefore, using nonlinear dynamics is the right way to decode neural code.

Several problems need to solve to verify that neuron impulses are the carrier of the information:

1) Are there corresponding relationship between the neural impulse series and the input signals from outside?

2) Is “impulse sequence space” an orderly space? If we gather all the neural impulses series in the neural system to form an “impulse series space” Ω, Ω must be an “orderly space”. This is because a very important feature of signal is the difference between big and small. Eyes could receive light signal that is bright or dark; ears could receive sound signal that is loud or feeble; it is the same that the olfactory system could receive odor signal that is strong or weak. To set up a corresponding relationship between the neural impulse series and the input signals from outside, we must ensure that Ω space must be a orderly space.

Ω={ηi} （1）

Ω is called sequence space. If we can elucidate Ω space, then neuroinformatics begin its time of rationality, otherwise it will keep in the level of qualitative description. What need to solve now is what characteristics does Ω space has. As proclaimed in the set theory, some sets of elements could form a group (as the renormalization group、Galois group), some sets could form a ring of integers, or algebra (as the bool algebra). What system could Ω form? What kind of transform could be processed in Ω space?

3) How to solve the conflict between the unstable neural system and the deterministic signal processing? Neural system is an extremely unstable system, there is the plasticity everywhere in the neural system. This is represented by the variability of ηi. Contradiction will happen when correspond each ηi to the deterministic information. Of course, the first idea appearing in head is the statistic method, in other words, considering the statistics of many ηi as the representation of a kind of information. Years of research prove that this method is useless. This is because the neural system is nonlinear and extremely unstable. The statistic method is useless in this situation. New ideas are needed to solve this problem.

This paper gives an example of olfactory system to carefully analyze the above four questions. First, sort the trajectories (impulse series), then define the distance and transfer a problem from a ”trajectory space” into a ”distance space”. Thus, according to the functional analysis, calculations are permitted in “distance space.”

The main task of studying neural coding is to explain how the irregular neural impulse changes with the input signal. Upon finding this rule, we could elucidate the information transform in neural system and the mechanism of neural coding. Circle maps in neurons is an important theoretical tools.

First, considering the response signal of a neuron under impulse stimulus of invariable frequency. We use the classic H-H equation to describe potential change in neurons (as in (1)). Though many people have improved the H-H equation, we know that these improvements are only quantitative mending without qualitative differences. Our discussion does not lose any generality.

The computer simulation result is listed below:

(2)

According to the computer simulation, we get the figure of circle map:

With this circle map rule, we can understand the meaning of irregular impulse sequences. Taking the olfaction as the research object, we clarify the relation between the thickness of the odor and the impulse series of all kinds of olfactory neurons, as well as the rule that governs the information change between olfactory neurons.

Raising the concept of “orderly space”, we admit the indetermination and unstability in neural system. It is not necessary for all parameters in the H-H equation to be precise and unchanged. Moreover, same conclusion can be drawn on the present reformed the H-H equation if only the equation structure keep unchanged. In another words, although the H-H equation describes the neurological electrophysiology qualitatively our conclusion should be able to show the actual electrophysiology.

A Computational Causality for Explanatory Language Understanding

Key-Sun Choi1 and Du-Seong Chang2

1Division of Computer Science, KAIST, BOLA, KORTERM, Korea2Spoken Language Technology Division, KT, Division of Computer Science, KAIST,

Causality or Causal relation refers to “the relation between a cause and its effect or between regularly correlated events”. Causalities in the document are represented implicitly, or by lexical patterns. Although the causality inference was tried in some direction, the causality extraction and its applications are not sufficient. In this paper, we focus on the extraction of causalities that are explicitly represented, and we discuss some document understanding applications using the causality.

We take prior consideration of the explicit causality that exists between noun phrases. Causality patterns that connect two noun phrases are known to be causal verbs. We use lexical patterns as a filter to find causality candidates and we transfer the causality extraction problem to the binary classification. To solve the problem, we introduce probabilities for word pair, concept pair and cue phrase that could be a causality pattern. With these probabilities, we will propose a causality classifier based on the Naïve Bayes classifier. The probabilities are learned from the raw corpus in an unsupervised manner. With this probabilistic model, we increase both precision and recall. Our causality extraction shows an F-score of 77.37%, which is an improvement of 37.6% over the baseline model. The long-distance causality is extracted with the binary tree-styled cue phrase.

When causality noun phrase pairs are selected from one document or from the same domain with the same topic, we can make a causal network like that shown in Figure 1. When we assume that it is independent from events that are not represented in the graph, we can respond to some causal questions such as “What is the cause of the cancer?” ‘Cigarette smoking’ and ‘tobacco products’ in the sentence (1) are the causal information of the term ‘gum disease’. This causal information is one of pure collocation information whose inter-term distance is so long that N-gram could not catch up.

“Cigarette smoking and use of tobacco products may also cause gum disease.”(1) Causality as a long-distance collocation information can improve the performance of the text mining system. When we assume that two terms that have similar causal information are similar terms, we can use the causal information for the term classification. We prove that the causality is one of the positive features for the term clustering. Our term clustering shows a precision of 70%, which is an improvement of 32.9% over the lexical similarity-based model.

Figure 1: Causal network for ‘protein’

A new approach to localization and navigation of mobile robots - Effective Bayesian estimation and reinforcement learning.

Masumi Ishikawa, Fredrik Linåker, Keiji KameiDepartment of Brain Science and Engineering,

Kyushu Institute of Technology, Japan

Introduction: Two central issues in a mobile robot is how to make localization, i.e. estimation of its location and orientation, and navigation to a given goal more efficient. For efficient localization we pro- pose a new technique of using an omni- directional camera and 35-dimensional rotation invariant feature vectors called polar higher order local autocorrelation functions (PHLAC)[1].

For efficient navigation we propose to introduce sensory information into reinforcement learning (RL) to increase its learning speed and the probability of reaching a goal, and to decrease the probability of collision [2]. We also propose to use a genetic algorithm for optimizing the values of parameters in RL [3].

Localization: The PHLAC is an extension of HLAC, which is translation invariant. Basic idea is that translation invariance on a panoramic view is equivalent to rotation invariance on an omnidirectional view. It provides rotation invariance to the polar HLAC directly on the omni- directional view. This is combined with particle filters, which carry out 5000 localization hypotheses in parallel, resulting accurate estimation of the location of a continuously moving real robot.

Navigation: A key idea of introducing sensory information is to directly modify value functions (Q-values) near an obstacle based on sensory information in addition to the modification of Q-values at the current location of a mobile robot based on a reward from the environment in conventional RL.

We also propose to optimize the values of parameters in RL with the help of a genetic algorithm. An additional idea is to take advantage of inheritance in a genetic algorithm; Q-values in RL in the previous generation are used as the initial Q- values in the next generation to further accelerate learning.

Experimental results: The average location error is 31mm in the 1100mm by 800mm arena. Estimated body positions overlap the actual ones in over 95% of the time steps. The average orientation error of the robot is 5.5 degrees.

The average number of actions need- ed to reach a given goal for the optimal values of parameters in RL decreases by about 30% compared with RL with that for tentative parameters, resulting an approximately shortest path. The number of goals reached increases more than 2 times faster and the number of collisions is much smaller compared to conventional RL.Conclusions: Computer experiments have well demonstrated the effectiveness of localization by PHLAC and of reinforcement learning by introducing sensory information and a genetic algorithm.

References: [1] F. Linåker, M. Ishikawa, IROS-2004, pp. 4026-4031, Sendai, 2004.[2] K. Kamei, M. Ishikawa, IJCNN, pp.3185-3188, Budapest, 2004.

[3] K. Kamei, M. Ishikawa, A genetic approach to optimizing the values of parameters in reinforcement learning for navigation of a mobile robot, to appear in ICONIP-2004.

Neurobiology of Stress

Kyungjin Kim, Ph.D.Brain Research Center, 21st Century Frontier Program in Neuroscience, and

School of Biological Sciences, Seoul National University, Seoul 151-742, Korea

Stress in adulthood can exert profound influences on physiological and behavioral consequences, but the extent to which prolonged maternal stress affects the brain functions of adult offspring remained largely unknown. Chronic immobilization stress to pregnant mice affected fetal development. When pups born from stressed mice were reared in an environment identical to that of non-stressed normal condition, several physiological parameters such as serum corticosterone level, body weight and hippocampal mineralocorticoid (MR) and glucocorticoid (GR) mRNA levels in maternally stressed offspring were similar to those shown in the control mice. However, maternally stressed offspring showed a significant reduction in N-methyl-D-aspartate (NMDA) receptor-mediated long-term potentiation (LTP) measured in the CA1 area of hippocampal slices. A subsequent biochemical analysis indicated that there was a clear decrease in synaptic NR1 and NR2B subunits of NMDA receptor in the hippocampus with an apparent reduction of interaction between these two subunits. Along with these electrophysiological and molecular aspects, Morris water maze test and passive fear avoidance test showed that spatial learning and memory and fear avoidance responses were impaired in maternally stressed adult offspring. These results suggest that prolonged maternal stress leads to malfunctions of the brain, which extend to and are revealed in adulthood.

Can Stochastic Resonance Imaging be a substitute for high-priced Gadolinium scan in India?

Prasun Roy, Vani K, T Ray, A K Saini Computational Neuroscience and Neuroimaging Laboratory

National Brain Research Centre, Manesar, Gurgaon-122 050, Haryana, India

The technique of using organometallic chelated compounds having high

magnetic moment as gadolinium and holmium (‘contrast agents’ as gadodiamide) have been an important armamentarium for neuroimaging, along with the novel approach of nanoparticle based gadolinium targetting. However the cost of gadolinium is expensive in the scenario of patients in developing countries. We probe the possibility of using the approach of stochastic resonance imaging (SRI) to enhance MR images so that the enhanced image could approximate gadolinium enhanced images. Gadolinium enhancement of MR proton signal is basically effected by a stochastic activation induced by gadolinium atoms. Proton relaxation processes occur, actuated by microscopic effects as probabilistic fluctuation of local dipolar field due to the stochastic kinetic motions of the gadolinium nuclei. We consider magnetization of water medium as a dependent variable of the stochastic nature of nuclear relaxation process, namely the noise intensity inducing the relaxation process that is effected by the gadolinium; there is an optimal amount of gadolinium level needed for maximal enhancement.

We propose a bijective mapping between the magnetic signal intensity continuum and the voxellated grayscale gamut and show transformationally that stochastic activation of voxellated greyscale correlates with stochastic kinetic gadolinium effect. We perform a stochastic resonance enhancement of the voxellated MR signal and administer a programmed stochastic perturbation on pre-gadoliniated T1 image of different brain lesions. There is appreciable enhancement of the images which compare with the post-gadolinium images of the lesion. The noise correlogram between stochastic resonant image and gadoliniated image shows an inverted U graph, the characteristic signature of stochastic resonance, that indicates that maximum enhancement and correlation occurs at a particular optimum stochastic input level. We apply the technique to investigate MR image enhancement in neoplastic and infective lesions of the brain (e.g. glioma and tuberculoma), and to angiography. Future prospects could be to explore the possibility of evaluating SRI to study ‘tropical ring lesions’ of brain, a key neuroradiological challenge in India, being hypothesized to be associated with chronic infective and inflammatory processes.

Regulation of Prefrontal Cortical Functions by Alpha-2-adrenoceptors: Its possible relevance to Attention Deficit Hyperactivity Disorder

Bao-Ming LIInstitute of Neurobiology, Fudan University

220 Han-Dan Road, Shanghai 200433, China

The prefrontal cortex (PFC) plays an essential role in the so-called executive functions: the ability to hold information on-line in mind (working memory), regulate our attention, inhibit inappropriate behaviors, and plan and organize for the future. It is known that the PFC is very sensitive to change in the adrenergic environment. Norepinephrine (NE) has marked effects on PFC functions, and these actions may have particular relevance to Attention Deficit Hyperactivity Disorder (ADHD).

During the past decade, our laboratory has focused on the alpha-2-adrenergic regulation of prefrontal cortical functions. Blockade of alpha-2-adrenoceptors in the dorsolateral PFC by local infusion of the alpha-2-adrenergic antagonist yohimbine markedly impairs working memory ability in monkeys (Li et al. 1994). Conversely, similar treatment with the alpha-2-adrenergic agonist guanfacine produces a delay-dependent improvement in working memory (Mao et al. 1999). Consistently, iontophoretically applied yohimbine suppresses PFC neuronal activity related to working memory, whereas clonidine, either systemically or iontophoretically administered, has an opposite effect (Li et al. 1999). Thus, alpha-2 adrenoceptors in the PFC regulate working memory at both behavioral and cellular levels.

Recently, we reported that some of the important symptoms of ADHD can be recreated by blocking alpha-2 adrenoceptors in the PFC. In addition to the weakened working-memory capability and working-memory related neuronal activity described as above, infusions of yohimbine into the dorsolateral PFC increase impulsivity in monkeys. During chronic intra-PFC administration of yohimbine, monkeys tested on a go/no-go task show a selective deficit in no-go performance: they could not inhibit a touching response to the no-go signal (Ma et al 2003). Meanwhile, the monkeys demonstrate a dramatic increase in locomotor activity in home cages during treatment with yohimbine (Ma et al 2004), very reminiscent of the increased activity found with PFC ablations in monkeys or humans. Similar results have been repeated in rats with yohimbine infusion into the medial prefrontal cortex (Ma et al, unpublished data).

In addition, we also found that visuomotor associative learning, a task that requires the ventral and orbital prefrontal cortex (Wang et al. 2000), is also sensitive to manipulation of alpha-2 adrenoceptors in the PFC. Systemic administration or local infusion of guanfacine into the ventral prefrontal cortex significantly enhances the monkey’s ability to map 1:1 associative relationships between visual patterns and motor responses: the monkeys show an increased capability to apply win-stay/lose-shift and change-stay/change-shift learning strategies (Wang et al. 2004a; Wang et al 2004b).

It has been speculated that striatal DA mechanisms underlie the hyperactivity observed in ADHD patients. Our studies in monkeys and rats, together with studies by other authors in this field, strongly suggest that, alpha-2-adrenergic activation tunes

the prefrontal cortex to an optimal functional status, and dysfunction of alpha-2 NE system in the PFC may contribute to locomotor hyperactivity, impulsivity and poor regulation of working memory, which form the cardinal symptomology of ADHD.

Deciphering the genetic basis of mouse cerebellar development

Teiichi FuruichiLaboratory for Molecular Neurogenesis,

RIKEN Brain Science Institute, Wako 351-0198, Japan

The brain is the ultimate genetic system to which a large number of genes are devoted. In the post-sequencing era, it is now possible to elucidate how the brain develops and functions on a genetic basis. We focus on the postnatal development of the mouse cerebellum as a model system, since it develops through a series of cytogenetic and morphogenetic events (cell proliferation and migration, dendrogenesis and axogenesis, synaptogenesis, myelination, foliation and fissurization, etc.) on schedule within the first three weeks of life. We attempt to decipher the "genetic blueprint" for cerebellar development by profiling all of the transcription (i.e., the transcriptome) responsible for developmental stages on a genome-wide basis (e.g., fluorescence differential display, cDNA microarray, and GeneChip). Then, the spatial (cellular) and temporal (developmental) specificities associated with the expression patterns were analyzed by performing in situ hybridization (ISH) brain histochemistry and reverse transcription-polymerase chain reaction (RT-PCR), respectively. We have successfully systematized the information collected regarding gene expression in an online "Cerebellar Development Transcriptome (CDT) database". I will introduce about the transcriptomic feature of cerebellar development and the CDT database. By applying these novel genome-wide approaches, we are able to access a large number of differentially-expressed genes, including those that had not yet been characterized in the nervous system, and those which had only been predicted in silico. Among these novel cerebellar developmental genes we identified, I will also introduce about the developmental roles of three genes: Cupidin/Homer2 (a postsynaptic scaffold protein that interacts with mGluR1/5, IP3R, Shank, Drebrin, etc., in granule cells), CAPS2 (a presynaptic, vesicle-associated protein that regulates the activity-dependent release of the neurotrophins NT-3 and BDNF from the parallel fiber terminals of granule cells), and Opalin (a transmembrane glycoprotein that specifically localizes to the paranodal loop of the myelin sheath that wraps around the axons of Purkinje cells).

MAPK regulates phosphorylation of Neural Retina Leucine Zipper: A Key Regulator of Rod Photoreceptor Differentiation and Function

Prabodh Swain, Sandeep Kumar, Dharmesh Patel, Anand SwaroopNational Brain Research Centre, Manesar, Gurgaon- 122050, Haryana, India

Department of Ophthalmology and Visual Sciences, University of Michigan, USA

NRL is a bZIP group of DNA binding protein expressed in retina and pineal gland. Mutation of NRL gene has been associated with different autosomal dominant retinitis pigmentosa. One of the implications studied in the transactivation of rhodopsin minimal promoter suggested that mutated NRL alters the synergistic transactivation of rhodopsin promoter in the in vitro reporter assay. To understand the exact biochemical alterations of NRL produced by such disease mutations we expressed mutated proteins in vitro and performed in vitro phosphorylation. Metabolic labelling of NRL revealed that S50T and P51L substitutions affected the protein phosphorylation drastically. The multiple phosphoisoforms of NRL are collapsed into 1-2 major protein bands in SDS-PAGE analysis. Further to understand the nature of kinase(s) responsible for NRL phosphorylation, we identified a mitogen activated protein kinase that specifically phosphorylates NRL. Deletion of the entire transactivation domain of NRL abolished the MAPK mediated phosphorylation of the protein. We suggest that MAPK is one of the kinase responsible for the phosphorylation (primary post translational modification) of NRL. Such finding of the role of MAPK in the phosphorylation of NRL provided an important clue to unravel the complex regulatory processes involved in the rod differentiation and function.

Support: Department of Biotechnology, Govt of India

Examine synchrony of the relationship between blood pressure (BP) and renal sympathetic nerve activity (RSNA) in response to haemorrhage in

Wistar rats.

Tao Zhang1 and Zhuo Yang2

1College of Life Sciences, 2Medical School, Nankai University, PR China, 300071

Recently we employed a power spectral technique and a cross-sample entropy (CSE) method (Rickman & Moorman, 2000) to study synchrony of the relationship between BP and RSNA during right atrial stretch to mimic plasma volume expansion (Yang et al, 2002). CSE revealed that during the reflex inhibition there was more synchrony between the oscillating signals in the BP and RSNA sequences. In the present study we have used a similar analysis of these signals during a mild haemorrhage which reflexly causes an increase in RSNA in an attempt to maintain BP constant.

The experiments were performed on 10 anaesthetised (urethane 650 mg.kg-1, chloralose 50 mg.kg-1) Wistar rats. BP was measured from a femoral artery and RSNA from a branch of renal nerve after exposing the left kidney retroperitoneally. A 33 second high frequency (1 KHz) sampling of BP and RSNA was recorded and rectified. The trachea was cannulated and spontaneous respiration maintained. Rectal temperature was maintained at 37oC by a heating blanket. A femoral vein was cannulated and 1 ml of blood was removed into a pre-heparinised syringe over 1 min and 5 mins later slowly reinfused. Data are expressed as mean ¡À S.E.M., and analysed using repeated measures ANOVA. Statistical differences were considered significant when p<0.05. Rats were killed by overdose of urethane at the end of experiment.

Haemorrhage decreased BP and increased RSNA (25.9 ¡À 2.4%). A coherence measurement from power spectral analysis failed to detect significant changes between baseline and haemorrhage in either averaged coherence over the range 0-10 Hz or coherence at heart rate frequency. However a non-linear dynamic analysis of the group data using CSE measurements showed that the relationship between BP signals and RSNA time series did increase during haemorrhage. Such an increase in entropy indicates that the volume reflex control system has a greater power to nullify the disturbance than would be the case if increased nerve activity was more synchronised. Intrathecal administration of the glutamate receptor antagonist, kynurenic acid (2 mM) significantly reduced the reflex increase in RSNA (13.4 ¡À 2.9%) caused by haemorrhage. Analysis of the RSNA-BP time series during kynurenic acid block showed there was no change in total power, power at heart rate frequency, coherence at heart rate frequency, or in the cross-sample entropy measurements. Thus the decrease in regularity between BP and RSNA during the reflex increase in RSNA was prevented by blocking spinal glutamate receptor.

The data from both linear and non-linear dynamic analysis together suggest that reflex adjustments to blood volume disturbances are not mediated via brainstem tone generating network oscillators but depend on enhancement of direct synaptic input to final common pathway neurones.

References:Yang Z, Zhang, T & Coote JH (2002) Exp Physiol 87, 461-468Rickman JS & Moorman JR (2002) Am J Physiol 278, H2039-H2049

From Neural Firing to Hypersynchronous Discharge in the Cortex of Epileptogenic Focus

Xin Tian & Yijun SongThe Department of Biomedical Engineering,

Tianjin Medical University, Tianjin, 300070, China

The aim of this study is to investigate the hypersynchronous discharges in epilepsy from neuron to brain with chronic temporal lobe epilepsy (TLE) rats.

TLE rat model was prepared by lithium-pilocarpine method. The epilepsy – like EEG in temporal lobe and hippocampus of TLE rats during seizures were shown, which might be caused by hypersynchronous discharges. The neuronal apoptosis at hippocampus were also detected in our study by in situ TUNEL.

The question arisen here is the mechanism of the hypersynchronous discharges in the Cortex related to hippocampus, although neurons decrease here due to the apoptosis.

From the micro (neuron), there is a bursting in the firing neuron. There is a high nonlinearity and nonstationarity of the bursting in neuron, and the bursting might be consisted of several components with different frequencies. A time-frequency coding is proposed and implemented to investigate the neurophysiologic mechanism of the neural firing. The results of neural coding of firing neuron is applied to macro to understand the hypersynchronous discharges happened in the cortex related with hippocampus although there is the neuronal apoptosis.

The Role of Ankyrins in Neurite Growth and Polarization

Hiroyuki KamiguchiLaboratory for Neuronal Growth Mechanisms

RIKEN Brain Science Institute, Japan

During development, neurons send out neurites that differentiate into axons or dendrites. Axons elongate and reach their appropriate targets to form neuronal networks. These developmental events highly depend on various functional molecules, including the cytoskeletons and cell adhesion molecules (CAMs). For example, mutations of L1, a CAM in the immunoglobulin superfamily, cause abnormal axon tract development in humans and mice. The cytoplasmic tail of L1 binds ankyrins that associate with the actin-spectrin cytoskeleton. The major ankyrin isoforms expressed in the developing nervous system are 440-kD ankyrin-B and 480/270-kD ankyrin-G. Ankyrin-B mediates L1 coupling with retrograde actin flow, thereby acting as a molecular clutch that regulates neurite growth. In contrast, ankyrin-G and its associated protein, IV spectrin, form a diffusion barrier that maintains polarized L1 distribution in the axon. My talk will focus on the dynamic and static roles of ankyrins in regulating neurite growth and axon-dendrite polarity.

Blind Separation of Sound Sources in Real-World Situations

Kiyotoshi Matsuoka and Akio YamazaskiDepartment of Brain Science and Engineering

Kyushu Institute of Technology, Japan

Blind source separation (BSS) is a method for recovering a set of statistically independent signals from the observation of their mixtures without any prior knowledge about the mixing process. It has been receiving a great deal of attention from various fields as a new signal processing technique. Among conceivable applications of BSS the most promising one might be separation of sound signals. Indeed, in the literature of BSS one can see a lot of papers that describe experiments on sound separation. In our experience, however, although the conventional methods for BSS are able to achieve separation for artificially synthesized data, they do not necessarily work well for real-world data. Separation accuracy is often unsatisfactory and, what is worse, they sometimes reveal incomprehensible instability.

As known well, in the subject of BSS, the definition of the sources has a certain indeterminacy: a source signal transformed by any linear filter can also be considered a source signal. Corresponding to the indefiniteness of the sources, the choice of the separator has an arbitrariness. For this point one of the authors proposed a principle called the minimal distortion principle (MDP): “Among the feasible separators, choose the one that best preserves the quality of the signals observed at the sensors (microphones).” The BSS algorithm discussed in this paper also adopts the principle.

The task of ICA is basically to find the inverse of the mixing matrix and to apply it to the observation. In practical applications the microphone array should be made compact, but then the mixing matrix becomes almost singular particularly for low frequencies. If the separator is constructed by a FIR filter with MDP for such a nearly singular situation, a large number of taps or parameters (say, some thousands taps) become necessary. It is not easy to determine such a large number of parameters in a reliable manner. Actually we sometimes face the following phenomenon. When applying an iterative ICA algorithm to a given data, in the beginning the algorithm appears to behave in a desired manner, but as the iteration goes on, suddenly some instability occurs.

Looking at the result in such a situation, we usually found that the following thing occurs. Some frequency components of a source appear at an output terminal of the separator while other frequency components of the same source appear at a different terminal. This phenomenon is probably due to a too high frequency resolution when a long filter length is adopted. Time-domain algorithms for BSS are usually thought to be relatively free from this kind of permutation problem as compared to frequency-domain approaches, but it is not necessarily the case.If adversely the algorithm is performed with a shorter filter length, the stability will considerably be improved, but the accuracy of separation will be unsatisfactory. A solution to this trade-off problem is to relax the MDP constraint. By relaxing the constraint, we can reduce the length of the separating filter without degrading the separation accuracy so much. Thus how to determine the degree of the normalizing

constraint, which is relevant to the quality of the separated signals, and the filter length, is a very important problem. This paper shows some useful suggestions indicating how to choose those parameters.

Neural Control of Saccade Sequences

Supriya Ray National Brain Research Centre, Manesar, Gurgaon- 122050, Haryana, India

The spatiotemporal organization of motor sequences enables complex goal directed behaviors. We use the saccadic eye movement system as a simple model system to understand the control of sequential behavior by having subjects perform a variety of modified double-step tasks in which targets in different locations elicit saccade sequences. By systematically varying the time at which the second target appeared relative to the first saccade we show how sequential saccades maybe programmed concurrently. Using different manipulations we describe results from behavioral experiments in which sensory, attentional and cognitive influences modulate the degree of parallel processing. We also show how such behavioral experiments can be used in conjunction with electrophysiological experiments to test how neural networks may implement behavioral control.

Monitoring Ischemic Brain Injury Using Nonlinear Methods

Yisheng Zhua, Yihong Qiua, Shanbao Tongb

aDepartment of Biomedical Engineering, Medicine, Johns Hopkins University, USAbDepartment of Biomedical Engineering, Shanghai Jiao Tong University, China

The brain's electrical activity following: 1) graded ischemic injury; 2) hypoxia-ischemic injury; 3) ischemic injury with pre-injection of NAALADae inhibitor has been studied. Animal experimental models of brain injury were used. Two channels of EEG, one channel of ECG were recorded continuously during the experiments. EEG has been analyzed by Tsallis time-dependent entropy (TDE). Both mean and variance of TDE have good specificity to injury and recovery. The mean TDE decreases as the EEG becomes less complex during the brain injury; and TDE increases gradually as the brain recovers. Heart rate variability (HRV) which were extracted from ECG has been analyzed by several nonlinear algorithms. The brain injury results in a reduction of HRV while a recovery brings HRV back to nearly normal level. These results suggest that quantitative EEG and ECG can be used for monitoring brain injury.

Neuroanatomical Analysis for Onoamtopoeia and Phainomime Words:  fMRI Study

Jong-Hye Han and Kichun NamDepartment of Psychology, Korea University, Korea

The purpose of this study is to examine the Neuroanatomical areas related with onomatopoeia (sound-imitated word) and phainomime word (motion-imitated word). Using the block-designed fMRI, whole-brain images (N=11) were acquired during lexical decisions. We examined how the lexical information initiates brain activation during visual word recognition. The onomatopoeic word recognition activated the bilateral occipital lobes and superior mid-temporal-gyrus, whereas the phainomime words recognition activated left SMA and bilateral cerebellum as well as bilateral occipital lobes. Regions more activated for the phainomime word than onomatopoeia included left SMA and bilateral cerebellum. Regions more activated for the onomatopoeia than phainomime word included left superior and mid-temporal gyri. The word recognition for onomatopoeia plus phainomime word showed activation on bilateral middle and superior temporal gyrus, right supramarginal gyrus, left middle temporal gyrus, left middle occipital gyrus, and right occipital gyrus. This is the first fMRI research to analyze onomatopoeia and phainomime word.

POSTER

Neuroinformatics and Data Sharing

Ling Yin, Guang Li, Yiyuan Tang, Xianglan Jin, Xiaowei Tang Neuroinformatics Workgroup of China, 301 Hospital, Beijing, China

1. Development in OECD-GSF-NI-WG and Neuroinformatics

In Jan 2004, there was a meeting of the Organisation for Economic Co-operation and Development (OECD) committee for scientific and technological policy at ministerial level. The 2002 Report on Neuroinformatics from the Global Science Forum Neuroinformatics Working Group of OECD (OECD-GSF-NI-WG) was submitted to the ministers attending the meeting. It highly recommended to establish a new global mechanism, the INCF (International Neuroinformatics Coordinating Facility), created an associated funding scheme, the PIN (Program in International Neuroinformatics) and establish national nodes and research programs in Neuroinformatics. It also recommended that the management and exploration of data about the brain can be best achieved through a coordinated, multidisciplinary, international effort. Ministers expressed their appreciation for the work of OECD-GSF-NI-WG, and agreed that the study of human brain would be one of the most difficult and rewarding scientific challenges of the 21st century. They also agreed that interested countries should join together to create optimal conditions for the expansion and international coordination in this new field. In Apr. 2004, the most recent meeting on Neuroinformatics was held in Paris by OECD-GSF. Members from 21 countries attended that meeting. Details on several recommendations were warmly discussed.

2. Data Sharing in China

Data sharing in Science and Technology is a very important policy in China. Management and Sharing System of Scientific Data for Medicine is a key project of the National Basic Platform for Science and Technology for year 2003 in the Ministry of Science and Technology, P. R. China. As the paramount part of the National Engineering of Scientific Data Sharing, the System is undertaken by Chinese Academy of Medical Sciences, Chinese Center for Disease Prevention and Control, Chinese PLA General Hospital, and Chinese Academy of Traditional Chinese Medicine. Scientific data resources in medicine will be integrated together in the way of distribution physically and unification in logic by the system. The system covers most of the fields in medicine, including basic medicine, clinical medicine, public health, traditional Chinese medicine, special medicine, pharmacology and innovated drug etc. In addition, the system also specially sets up database for SARS and respiratory diseases.

3. Some Suggestions to Neuroinformatics and Data Sharing

From the above, we can see there are some overlaps between Neuroinformatics and Data sharing. In a way, Neuroinformatics is data sharing in all levels of neuroscience. Some experiences and suggestions about data sharing are also suitable to Neuroinformatics, as shown the following: 1) In order to strengthen international cooperation of establishment of Neuroinformatics data bank we need to

set up unified data bank criteria on the basis of data integration and modification from scattered scientists and facilities. We need to set up bank groups of neuroscience data, something similar to gene bank to make it sharable, extendable to reach some kind of scale and authorization. 2) In order to reach true meanings of data sharing, we need to establish an integrated service system of international data management and sharing of neuroscience data to break the barriers among basic medicine, clinic medicine, preventive medicine, public health and pharmacology, etc. It will offer one-stop service via index and catalogue inquiries for data service and network environment of therapeutics, prevention, control and research of specific diseases. 3) To speed up collecting top human resources for access and sharing of neuroscience data, normal training programs should be offered.

Improvement of reinforcement learning of a mobile robot using sensors and a genetic algorithm

Keiji Kamei and Masumi Ishikawa

Dept. of Brain Science and Engineering, Kyushu Institute of Technology, Japan

Background and Idea: Reinforcement learning (RL) is frequently used in mobile robots, but suffers from slow learning. To solve this difficulty we propose to intro- duce sensory signals into RL in a direct way. Another difficulty is that we generally don’t have prior information on the values of parameters in RL. To solve this difficulty we propose to use a genetic algorithm (GA) with inheritance for optimizing the values of parameters in RL.

Methods: In addition to directly modify value functions (Q-values) near an obstacle based on sensory information, we also restrict the reduction of Q-values to only the region where the distance to the obstacle is less than a given threshold. The latter helps to generate the shortest path to a given goal and to pass through a narrow corridor.

RL has such parameters as a discount rate, a learning rate, an in the -greedy policy, rewards for actions, a reward from the environment, a reward from sensory information, and its thresh- old in modifying Q-values. The length of a chromosome is 48 bits, with 6 bits for each parameter. Parameters are coded in a linear scale except for a discount rate, which is coded in a logarithmic scale.

Let the probability of the selection of each gene locus and crossover be 10%. 50 individuals are generated initially, for each of which fitness is evaluated. We then generate 25 new individuals in addition to the original 50 individuals. Out of 75 individuals, 50 individuals with higher fitness are selected. The resulting 50 individuals constitute the next generation.

Results of Computer Experiments: In computer experiments using a mobile robot in Fig. 1 we assume 3 kinds of actions, i.e., moving forward by 10cm, turning right or left by . It has ultrasonic sensors, which can accurately measure the distance to an obstacle not exceeding 80cm. Table 1 indicates the results of computer experiments. Fig.1 Mobile robot “TRIPTERS mini”, (a) overview, (b) positions of sensors.

Table 1 The results of computer experiments over the last 500 episodes. “Optimal” and “tentative” stand for the performance by the optimal parameters and by tentative parameters, respectively.

　#forwar

d #rotation #goalsoptimal 24.31 19.95 500tentative 39.16 23.09 500

Conclusions: Our key idea is to optimize the values of parameters in RL with the help of a GA with inheritance. We demonstrate that the optimization of parameters decreases the average number of for- ward actions and that of turning by about 40% and 20%, respectively. Moreover, all the episodes succeed in reaching a given goal.

Robustness, Evolvability, and Optimality of Evolutionary Neural Networks

Paulito Palmes , Shiro Usui Neuroinformatics Laboratory RIKEN Brain Science Institute

2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan

Artificial neural network (ANN) is a popular tool of researchers for activities that involve machine-learning tasks such as prediction, generalization, and classification. One of the major problems for its successful implementation, however, is the absence of a general rule to guide implementers on how to choose the appropriate architecture and initial state in a given problem domain. Since majority of ANN approaches rely on the gradient approach to discover the correct relationship between its input and output, inappropriate choices of its architecture and initial states often lead to overfitness or underfitness of the training data. One promising approach to help in the ANN design problem is the use of evolutionary computation (EC). ANN design can be regarded as an optimization problem where the goal is to evolve optimal network structure and weights. There are two major ways to carry out this evolution, namely: invasive evolution and non-invasive evolution. Non-invasive approach evolves ANN structure by EC and adapts its weights by BP (backpropagation). Since weights are not stored during evolution, its structure evolution forces retraining of all its weights by BP which makes the entire process inefficient and prone to the local optima problem. On the other hand, invasive approach simultaneously evolves ANN’s structure and weights without relying on the gradient information. Since both weights and structures are locally stored and participate in the evolution process, optimal weights and structures are not relearned but propagated to the succeeding generations. These simultaneous evolutions create a feedback loop such that any shortcoming in its structure exploration is compensated by its weight adaptation, and vice-versa. Our empirical investigation shows that invasive evolution is robust from various forms of perturbation and produces ANN with stable and optimal solution.

Korean Sentence Processing Mechanisms reflected on ERP patterns

Choong-Myung Kim, and Kichun NamDepartment of Psychology, Korea University, Korea

Korean language has different structures from Indo-European languages and other Asian languages. The current study was designed to examine the ERP patterns and the cortical areas related with the lexical, syntactic, and semantic component in Korean sentence comprehension. In Experiment 1, ERP patterns related with the reading comprehension were examined and in Experiment 2, ERP patterns associated with the listening comprehension were investigated. For the syntactic violation, P600 and Late Positivity after 700 msec were measured and for the semantic anomaly, N400 and Late Positivity were observed in Experiment 1 and 2 commonly.  P600 components for the syntactic violation occurred in the left frontal and central lobes, while N400 components for the semantic anomaly appeared in the left all lobes. The difference between reading and listening comprehension is that the N100 component is measured for the semantic anomaly in listening, whereas the N100 component is recorded for the syntactic violation in reading. These results implicate that the early sentence processing varies depending on the sentence presentation modality, while the semantic and syntactic processing is common across modalities.

Signal transduction of auto-regulatory microglial apoptosis

Kyoungho Suk, Heasuk Lee, Eunyung Son, Jaeyoon Jeong, Jayoung Lee, Boyoung Jung, Dae Young Jung

Department of Pharmacology, Kyungpook National University School of Medicine, Daegu, 700-422, Korea

Activation-induced cell death (AICD) is an auto-regulatory mechanism for the immune system to remove unwanted activated immune cells after making appropriate use of them. Although AICD has been first identified in lymphocytes, recent works indicated that both microglial cells and astrocytes in CNS might be under the control of a similar regulatory mechanism. In contrast to AICD of T lymphocytes where Fas-FasL interaction plays a central role, neither Fas-FasL interaction nor TNF was important in AICD of microglial cells. Instead, nitric oxide (NO) produced by activated microglial cells themselves was the major cytotoxic mediator. Inflammatory stimuli such as LPS and IFN played a multiple role in AICD of microglial cells. They not only induced the indirect apoptotic pathway via production of NO, but also initiated the direct apoptotic pathway through the induction of caspase-11 or antiproliferative BTG1 gene. While caspase-11 induction and its activation were required for NO-independent apoptotic pathway, IRF-1 and NF-B were involved in NO-dependent apoptosis of microglial cells mainly by mediating NO synthesis (via iNOS induction). BTG1 participated in the AICD of microglia by lowering the threshold for apoptosis; BTG1 increased the sensitivity of microglia to apoptogenic action of NO. The auto-regulatory apoptosis of activated microglia was mediated through Toll-like receptor (TLR)4, but not TLR2, based on the studies using TLR2 or TLR4-deficient mice and dominant negative mutants. The main difference between TLR2 and TLR4 signaling in microglia was IRF-3 activation and IFN production followed by STAT1 activation; while TLR4 agonist induced IRF-3 activation and IFN production, TLR2 did not. Taken together, AICD of microglia appears be an auto-regulatory mechanism that controls the microglial activation, and the failure of the auto-regulatory mechanism may be in part responsible for the deleterious effects of microglial activation associated with CNS pathologies. Thus, further elucidation of molecular mechanisms underlying the auto-regulation of microglial activation may enhance our understanding of pathogenesis of CNS disorders such as neurodegenerative diseases.

Informal Inference based on the Integration of Multiple Neural Networks

Kyung-Joong Kim and Sung-Bae ChoDepartment of Computer Science, Yonsei University,

134 Shinchon-dong, Sudaemoon-ku, Seoul 120-749, Korea

In human brain, the interaction of multiple modules generates a high-level functionality such as inference and cognition and incorporates both symbolic and connectionist processing. As inference is least developed and unknown function of the brain, it is a challenging problem to explore and implement the function in order to discover the brain and apply it to several interesting problems. Usually, inference of human brain is not static but dynamic and informal. Implementing such characteristics is one of the challenging tasks for cognitive modeling. Similar to the human brain, the integration of multiple models for better performance can be exploited as an inference model. In this research, we attempt to devise a number of neural network models and combine them using behavior network and fuzzy integral which have flexibility for developing complex adaptive systems and apply the idea into real-world applications including web usage prediction and robot control.

Since exponentially growing web contains giga-bytes of web documents, users are faced with difficulty to find an appropriate web site. Using profile, information retrieval system can personalize browsing of the web by recommending suitable web sites. User's evaluation on the web contents can be used to predict users’ preference on web sites and construct profiles automatically. User profile represents different aspects of user's characteristics, thereby we need an ensemble of neural networks that estimate user's preference using the web contents labeled by user as "like" or "dislike." Fuzzy integral is a combination scheme that uses subjectively defined relevance of models and structure adaptive self-organizing map (SASOM) is a variant of SOM that is useful to pattern recognition and visualization. Fuzzy integral-based ensemble of SASOM’s trained independently is used to estimate user profile and tested on UCI Syskill & Webert data. Experimental results show that the proposed method can perform better than not only previous naïve Bayes classifier but also majority voting of SASOM’s.

Similarly, NN (Neural Network) based on CA (Cellular Automata) models complex phenomenon by simple rules, and optimized by genetic algorithm. Like many evolutionary approaches to robot control such as neural network evolved by genetic algorithm and fuzzy controller optimized by genetic algorithm, NN based on CA can be applied to robot control. Behavior modules such as avoiding obstacles and following light are evolved on the model. They are evolved incrementally by starting with simpler environment needed simple behavior and gradually making it more complex and general for complex behaviors. Because evolving higher behaviors

directly is difficult, we combine several basic behaviors by symbolic behavior network. Robot selects one of the basic behavior modules evolved or programmed at each time. We evaluate the performance of robot using Khepera simulator and modify simulator interface for visualization of the action selection procedure. Simulation results show the possibility of the symbolic combination of action modules for higher behaviors.

Unsupervised Extraction of Video Features for Lipreading

Michelle Jeungeun Lee1 and Soo-Young Lee1,2

1 Department of BioSystems 2 Brain Science Research Center and Department of EECS

Korea Advanced Institute of Science and Technology, Korea

It is very important to know the basic components of the patterns we want to recognize or synthesize. For speeches the basic components, also called as features, are Gabor-like signals localized both in time and frequency. For images the features are Gabor-like edge patterns. In this paper we report the features of video streams extracted from the video clips of human lip motion. Three unsupervised algorithms are investigated for the extraction of the video features. The Principal Component Analysis (PCA) results in global features, while the Independent Component Analysis (ICA) and Non-negative Matrix Factorization (NMF) result in local features. The effects of the time frames are analyzed and their statistical characteristics are investigated. The resulting features may be applicable to lip-reading and generation of lip videos for specific sounds.

Glutamate receptor-mediated signaling and the functional implication in microglial cells

Su-Yong Eun, M.D., Ph.D.Div. of Brain Disease, Dept. of Biomedical Science

National Institute of Health 122-701, Korea

It has been recently shown that the expression of various types of neurotransmitter receptors are not restricted to neurons but also observed in majority of glial cells. However, their function in glial cells is not known well in both physiological and pathological conditions. Here, we investigated the role of glutamate receptor on immediate-early genes (IEGs) in primary cultured and BV-2 microglia.

Our results demonstrated that both c-fos and c-jun mRNA and protein were dramatically induced following treatment with various glutamate receptor agonists (500 μM); N-methyl-D-aspartic acid (NMDA), kainic acid (KA), (S)-α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and (RS)-3,5-dihydroxyphenylglycine (DHPG). The responses were significantly suppressed by specific antagonists and also by calcium chelating agents EGTA and BAPTA-AM. Our results suggest that glutamate receptor activation regulates IEGs gene expression by modifying intracellular calcium levels in microglia. In addition, glutamate treatment markedly induced microglial cell proliferation, morphological transformation and the expression of inflammatory cytokines such as inducible nitric oxide synthase (iNOS) and tumor necrosis factor (TNF-alpha). Our results present the evidences that glutamate might be a potent microglial activator in a certain pathological condition. These findings might provide an insight to understand the function of microglial glutamate receptors in neuron-to-glial interaction under the excitotoxic conditions.

Programmed cell death of adult generated hippocampal neurons is mediated by the pro-apoptotic gene Bax

Woong SunDepartment of Anatomy, Brain Korea 21, Korea University College of Medicine,

126-1 Anam-Dong, Sungbuk-Gu, Seoul 136-705, Korea

In the dentate gyrus (DG) of the adult mouse hippocampus, a substantial number of new cells are generated daily, but only a subset of these survive and differentiate into mature neurons, whereas the majority undergo programmed cell death (PCD). However, neither the intracellular machinery required for adult stem cell-derived neuronal death, nor the biological implications of the significant loss of these newly generated cells have been examined. Several markers for apoptosis failed to reveal cell death in Bax-deficient mice and this, together with a progressive increase in neuron number in the DG of the Bax-KO, indicates that Bax is critical for the PCD of adult-generated hippocampal neurons. Whereas the proliferation of neural progenitor cells was not altered in the Bax-KO, there was an accumulation of doublecortin (DCX), calretinin (CR)+ and NeuN+ postmitotic neurons, suggesting that Bax-mediated PCD of adult-generated neurons takes place during an early phase of differentiation. The absence of PCD in the adult also influenced the migration and maturation of adult generated DG neurons. These results suggest that PCD in the adult brain plays a significant role in the regulation of multiple aspects of adult neurogenesis.

Biotransformation of drugs mediated by brain-specific splice variants of the drug-metabolizing enzyme,

Cytochrome P450

Reddy P. Kommaddi, Harish V. Pai, Shankar J. Chinta and Vijayalakshmi Ravindranath

Division of Molecular and Cellular Neuroscience,National Brain Research Centre, Manesar, Gurgaon- 122050, Haryana, India

Cytochromes P450 (P450) is a family of heme proteins that functions as mono-oxygenase and metabolizes a variety of xenobiotics, including drugs. Liver is quantitatively the major organ involved in P450 mediated metabolism. However, presence of P450 and associated mono-oxygenase activities in extrahepatic tissues such as lung, kidney and brain has been demonstrated. P450-mediated metabolism of psychoactive drugs in brain leads to pharmacological modulation at site of action and results in variable drug response. A frame-shift mutation 138delT generated an open reading frame in the pseudogene, CYP2D7 and an alternate spliced functional transcript of CYP2D7 containing partial inclusion of intron 6 was identified in human brain but not in liver or kidney from the same individual. The mRNA and protein of the brain variant CYP2D7 was detected in 6 out of 12 human autopsy brains. Genotyping revealed the presence of the frame-shift mutation 138delT only in those human subjects who expressed the brain variant CYP2D7. Thus, genotyping revealed the presence of frame shift mutation 138delT only in those human subjects who expressed the brain variant CYP2D7, which demethylates codeine to morphine. CYP1A1, a P450 enzyme bioactivates polycyclic aromatic hydrocarbons to reactive metabolites, which bind to DNA and initiate carcinogenesis. RT-PCR analyses using autopsy human brain samples demonstrated the presence of a splice variant of CYP1A1 in human brain with exon-6 deletion. This splice variant present in all 23 human brain samples that were examined could potentially biotransform drugs by pathways that are different from the wild type enzyme. We demonstrate the presence of unique P450 enzymes in human brain that are generated by alternate splicing and mediate biotransformation reactions that are dissimilar from known pathways in liver.