abstracts book - contents 1 plenary session 1 2 2 plenary session 2 4 3 plenary session 3 7 4...

Download ABSTRACTS BOOK - contents 1 plenary session 1 2 2 plenary session 2 4 3 plenary session 3 7 4 plenary

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  • ABSTRACTS BOOK

  • Contents

    1 PLENARY SESSION 1 2

    2 PLENARY SESSION 2 4

    3 PLENARY SESSION 3 7

    4 PLENARY SESSION 4 10

    5 PLENARY SESSION 5 13

    6 PLENARY SESSION 6 16

    7 ORAL COMMUNICATIONS 1A 19

    8 ORAL COMMUNICATIONS 1B 25

    9 ORAL COMMUNICATIONS 2A 31

    10 ORAL COMMUNICATIONS 2B 37

    11 ORAL COMMUNICATIONS 3A 43

    12 ORAL COMMUNICATIONS 3B 49

    13 ORAL COMMUNICATIONS 4A 55

    14 ORAL COMMUNICATIONS 4B 61

    15 ORAL COMMUNICATIONS 5A 67

    16 ORAL COMMUNICATIONS 5B 73

    17 ORAL COMMUNICATIONS 6A 79

    18 ORAL COMMUNICATIONS 6B 85

    19 POSTER3 SESSION 1 91

    20 POSTERS SESSION 2 117

    21 POSTERS SESSION 3 146

    1

  • 1 PLENARY SESSION 1

    2

  • Encontro Nacional de Física Estatística / ID: 21-1 [FUNDA] 1

    Numerical calculation of granular entropy: counting the uncountable. Stefano Martiniani,Daan Frenkel

    U. Cambridge

    In 1989, Sir Sam Edwards introduced the concept of `granular entropy', de�ned as the logarithm of the number of distinct packings of N granular particles in a �xed volume V. The proposal was rather controversial but much of the debate was sterile because the granular entropy could not even be computed for systems as small as 20 particles - hardly a good approximation of the thermodynamic limit. In my talk I will describe how granular entropies of much larger systems can now be computed, using a novel algorithm. The algorithm makes use of tools from equilibrium statistical physics, even though granular media cannot be described in terms of a Gibbsian ensemble. Interestingly, it turns out the de�nition of granular entropy will have to be modi�ed to guarantee that granular entropy is extensive. Surprisingly, our studies on granular entropy allow us to make contact with the Gibbs Paradox and the exten- sivity of he thermodynamica entropy. References: N. Xu, D. Frenkel, A. J. Liu, Phys. Rev. Lett. 106, 245502 (2011). D. Asenjo, F. Paillusson, D. Frenkel, Phys. Rev. Lett. 112, 098002 (2014). S. Martiniani, K. J. Schrenk, J. D. Stevenson, D. J. Wales, D. Frenkel, Phys. Rev. E 93, 012906 (2016). Stefano Martiniani, K. Julian Schrenk,Kabir Ramola, Bulbul Chakraborty, and Daan Frenkel, Nature Physics (in press)

    3

  • 2 PLENARY SESSION 2

    4

  • Encontro Nacional de Física Estatística / ID: 5-1 [BIO] 1

    Critical dynamics on a large human Open Connectome network Géza Ódor

    MTA-EK-MFA, Research Center for Energy, Hungarian Academy of Sciences, P. O. Box 49, H-1525 Budapest, Hungary

    Michael Gastner Yale-NUS College, 16 College Avenue West, 01-220 Singapore 138527

    Extended numerical simulations of threshold models have been performed on a human brain network with N=836733 connected nodes available from the Open Connectome Project [1]. While in the case of simple spreading models like contact process, SIS or threshold model a sharp discontinuous phase transition, without any critical dynamics arises, variable threshold models exhibit extended power-law scaling regions. This is attributed to fact that Gri�ths e�ects, stemming from the topological or interaction heterogeneity of the network, can become relevant if the input sensitivity of nodes is equalized. Nonuniversal power-law avalanche size and time distributions have been found with exponents agreeing with the values obtained in electrode experiments of the human brain [2]. Power-law activity time dependences occur sub-critically in an extended control parameter space region without the assumption of self-organization. Probably the most important result of this study is that negative weights enable local sustained activity and promote strong rare-region e�ects without network fragmentation. Thus, connectomes with high graph dimensions can be subject to rare- region e�ects and can show measurable Gri�ths e�ects. Another important observation is that power-laws may occur in a single network, without sample averaging, due to the modular topological structure. E�ects of link directness, as well as the consequence of inhibitory connections is studied. Robustness with respect of random removal of links suggest that connectome generation errors do not modify the Gri�ths e�ects qualitatively. [1] M.T. Gastner and G. Ódor, Sci. Rep. 5 , 14451 (2015). [2] G. Ódor PRE 94, 062411 (2016).

    5

  • Encontro Nacional de Física Estatística / ID: 175-1 [BIO] 1

    Correlations and complexity: characterizing neural code dynamics Fernando Montani

    IFLYSIB, Universidad Nacional de La Plata, CONICET CCT-La Plata, Argentina

    To understand how sensory information is processed in the brain, we need to investigate how information is represented by the activity of a population of neurons. At the level of how individual neurons process sensory information, it is necessary to develop suitable stochastic models to describe the enormous variability of trains of action potentials. For this, we use the path integral method to determine the analytical solution of the Hodgkin and Huxley equation by considering a non-Gaussian color noise to represent possible feedbacks due to the surrounding network. However at the collective level information can be carried not only on spike �ring rates, but also for the temporal structure of the series of shots, and correlations of spikes through neurons. In particular the correlations across neurons are widely found in the cortex, and the evidence shows that the correlations of pairs by themselves are not su�cient to explain the patterns of multi-neuronal �ring. We then analyze how the input statistics of neurons can lead to higher order correlations in a neuronal population de�ning a new scenario for possible synergistic or redundant states in the neural code. Finally we analyzed human recordings during di�erent motor-type activities and quanti�ed the complexity according to the di�erent dynamics.

    6

  • 3 PLENARY SESSION 3

    7

  • Encontro Nacional de Física Estatística / ID: 10-1 [BIO] 1

    A dynamical system's approach to birdsong Gabriel B. Mindlin

    universidad de buenos aires

    Birdsong production is a complex behavior that emerges when a highly specialized peripheral vocal organ, the syrinx, is driven by a set of well-coordinated physiological instructions. These are generated by a neural circuitry, which is reasonably well characterized. In this presentation, I will present a computational model whose variables are the average activities of di�erent neural nuclei of the song system of oscine birds. Two of the variables are linked to the air sac pressure and the tension of the labia during canary song production. I will show that these time dependent gestures are capable of driving a model of the vocal organ to synthesize realistic canary like songs. I will also discuss a road map for extending this research program to the problem of human voice production. x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x

    8

  • Encontro Nacional de Física Estatística / ID: 43-1 [BIO] 1

    The evolution of multicellularity and complexity Paulo Campos

    Departamento de Física, Universidade Federal de Pernambuco

    The formation of new and higher levels of biological organization is a common place in evolution. The appearance of multicellularity is considered to be one of the major evolutionary transitions. Multicellularity has evolved in many distinct occasions and through di�erent mechanisms and modes of development, making use of di�erent aspects of cellular biology. The emergence of multicellularity was pivotal towards the development of complex organisms. However, the de�nition of complexity is quite ambiguous, which helps to hinder empirical treatments of complexity in the evolutionary biology literature and also our understanding of the key processes determining its trend. A possible de�nition for complexity is to relate it to the number of distinct functions that be performed by an organism, e.g., the number of specialized cell types in such organism. Though it is well established that larger organisms are usually more complex, the so-called size-complexity rule. The fact is that the formation of larger organisms creates new possibilities for evolving division of labor. The emergence of multicellularity and the further increase of complexity will be discussed in the light of the existence of incompatibilities and tradeo�s. These problems have been investigated in our group through two distinct approaches: resource based-modeling and mechanistic models. The former has been used to address the existing tradeo� between the rate of resource uptake and yield in the process of energy conversion. It is conjectured that multicellularity has become possible due to the spread of the e�cient mode of metabolism, respiration. In this earlier stage of the evolutionary process, the �rst multicellular organisms were possibly undi�erentiated. In the second approach, we thus address the next stage of the evolutionary process, that is, the increase of complexity due to specialization of cells. We aim to present a theoretical approach to the size-complexity rule.

    9

  • 4 PLENARY SESSION 4

    10

  • Encontro Nacional de Física Estatística / ID: 8-1 [NEQUI] 1

    Dynamical Properties of Isolated Many-Body Quantum Systems Lea F. Santos

    Yeshiva University

    Results are presented for the short- and long-time dynamics of isolated many-body quantum sy

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