arXiv subjects

Marcelo H. R. Tragtenberg

Publications and source records attributed to Marcelo H. R. Tragtenberg.

5 recordsLinked to original sources

arXiv2018

Measuring neuronal avalanches in disordered systems with absorbing states

Power-law-shaped avalanche-size distributions are widely used to probe for critical behavior in many different systems, particularly in neural networks. The definition of avalanche is ambiguous. Usually, theoretical avalanches are defined as the activity between a stimulus and the relaxation to an inactive absorbing state. On the other hand, experimental neuronal avalanches are defined by the activity between consecutive silent states. We claim that the latter definition may be extended to some theoretical models to characterize their power-law avalanches and critical behavior. We study a system in which the separation of driving and relaxation time scales emerges from its structure. We apply both definitions of avalanche to our model. Both yield power-law-distributed avalanches that scale with system size in the critical point as expected. Nevertheless, we find restricted power-law-distributed avalanches outside of the critical region within the experimental procedure, which is not expected by the standard theoretical definition. We remark that these results are dependent on the model details.

physics.bio-ph↗

arXiv2017

Kinetic theory and Brazilian income distribution

We investigate the Brazilian personal income distribution using data from National Household Sample Survey (PNAD), an annual research available by the Brazilian Institute of Geography and Statistics (IBGE). It provides general characteristics of the country's population. Using PNAD data background we also confirm the effectiveness of a semi-empirical model that reconciles Pareto power-law for high-income people and Boltzmann- Gibbs distribution for the rest of population. We use three measures of income inequality: the Pareto index, the average income and the crossover income. In order to cope with many dimensions of the income inequality, we calculate these three indices and also the Gini coefficient for the general population as well as for two kinds of population dichotomies: black / indigenous / mixed race versus white / yellow; and men versus women. We also followed the time series of these indices for the period 2001-2014. The results suggest a decreasing of Brazilian income inequality over the selected period. Another important result is that historically-disadvantaged subgroups (Women and black / indigenous / mixed race),that are the majority of the population, have a more equalitarian income distribution. These groups have also a smaller monthly income than the others and this social structure remained virtually unchanged in the period of time.

q-fin.GN↗

arXiv2016

Griffiths phase and long-range correlations in a biologically motivated V1 model

Activity in the brain propagates as waves of firing neurons, namely avalanches. These waves' size and duration distributions have been experimentally shown to display a stable power-law profile, long-range correlations and $1/f^{b}$ power spectrum \textit{in vivo} and \textit{in vitro}. We study an avalanching biologically motivated model of mammals visual cortex and find an extended critical-like region -- a Griffiths phase -- characterized by divergent susceptibility and zero order parameter. This phase lies close to the expected experimental value of the \textit{excitatory postsynaptic potential} in the cortex suggesting that critical behavior may be found in the visual system. Avalanches are not perfectly power-law distributed, but it is possible to collapse the distributions and define a cutoff avalanche size that diverges as the network size is increased inside the critical region. The avalanches present long-range correlations and $1/f^{b}$ power spectrum, matching experiments. The phase transition is analytically determined by a mean-field approximation.

q-bio.NC↗

arXiv2013

Critical Avalanches and Subsampling in Map-based Neural Networks

We investigate the synaptic noise as a novel mechanism for creating critical avalanches in the activity of neural networks. We model neurons and chemical synapses by dynamical maps with a uniform noise term in the synaptic coupling. An advantage of utilizing maps is that the dynamical properties (action potential profile, excitability properties, post synaptic potential summation etc.) are not imposed to the system, but occur naturally by solving the system equations. We discuss the relevant neuronal and synaptic properties to achieve the critical state. We verify that networks of excitatory by rebound neurons with fast synapses present power law avalanches. We also discuss the measuring of neuronal avalanches by subsampling our data, shedding light on the experimental search for Self-Organized Criticality in neural networks.

cond-mat.dis-nn↗

arXiv2000

Strange nonchaotic attractor in a dynamical system under periodic forcing

We observe the occurrence of a strange nonchaotic attractor in a periodically driven two-dimensional map, formerly proposed as a neuron model and a sequence generator. We characterize this attractor through the study of the Lyapunov exponents, fractal dimension, autocorrelation function and power spectrum. The strange nonchaotic attractor in this model is a typical behavior, occupying a finite range of the parameter space.

cond-mat.stat-mech↗