Signatures of brain criticality unveiled by maximum entropy analysis across cortical states

Nastaran Lotfi, Antonio J. Fontenele, Thaís Feliciano, Leandro A. A. Aguiar, Nivaldo A. P. de Vasconcelos, Carina Soares-Cunha, Bárbara Coimbra, Ana João Rodrigues, Nuno Sousa, Mauro Copelli, Pedro V. Carelli

It has recently been reported that statistical signatures of brain criticality, obtained from distributions of neuronal avalanches, can depend on the cortical state. We revisit these claims with a completely different and independent approach, employing a maximum entropy model to test whether signatures of criticality appear in urethane-anesthetized rats. To account for the spontaneous variation of cortical state, we parse the time series and perform the maximum entropy analysis as a function of the variability of the population spiking activity. To compare data sets with different number of neurons, we define a normalized distance to criticality that takes into account the peak and width of the specific heat curve. We found an universal collapse of the normalized distance to criticality dependence on the cortical state on an animal by animal basis. This indicates a universal dynamics and a critical point at an intermediate value of spiking variability.

Boundary solution based on rescaling method: recoup the first and second-order statistics of neuron network dynamics

Cecilia Romaro, Antonio Carlos Roque, Jose Roberto Castilho Piqueira

There is a strong nexus between the network size and the computational resources available, which may impede a neuroscience study. In the meantime, rescaling the network while maintaining its behavior is not a trivial mission. Additionally, modeling patterns of connections under topographic organization presents an extra challenge: to solve the network boundaries or mingled with an unwished behavior. This behavior, for example, could be an inset oscillation due to the torus solution; or a blend with/of unbalanced neurons due to a lack (or overdose) of connections. We detail the network rescaling method able to sustain behavior statistical utilized in Romaro et al. (2018) and present a boundary solution method based on the previous statistics recoup idea.

Postdoctoral Fellowships in Neuromathematics and Stochastic Modeling of the Brain, São Paulo, Brazil

The Research, Innovation and Dissemination Center for Neuromathematics (NeuroMat), hosted by the University of São Paulo, Brazil, and funded by the São Paulo Research Foundation (FAPESP), is offering several post-doctoral fellowships for recent PhDs with outstanding research potential.

An assessment of numeracy in Brazil: a NeuroMat op-ed

by Fernando Jorge da Paixão


The international assessment made in 2018, promoted by the OECD, PISA, was widely disseminated in December 2019. It is a three-year exam that consists of three subjects, reading, mathematics and science. 600,000 15-year-old participated, chosen as a sample representing the 32 million students from the 79 countries participating in the test.

NES is the subject of an article on Open Knowledge Foundation

Last month, Open Knowledge Foundation featured an article about the Neuroscience Experiments System Frictionless Tool, also known as NES, a tool developed by the Technology Transfer team of RIDC NeuroMat.

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