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, and Pedro V. Carelli
Phys. Rev. E 102, 012408 – Published 27 July 2020

Abstract

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 states, 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 numbers of neurons, we define a normalized distance to criticality that takes into account the peak and width of the specific heat curve. We found a 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.

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  • Received 29 January 2020
  • Accepted 1 July 2020

DOI:https://doi.org/10.1103/PhysRevE.102.012408

©2020 American Physical Society

Physics Subject Headings (PhySH)

Physics of Living SystemsStatistical Physics & Thermodynamics

Authors & Affiliations

Nastaran Lotfi1,*, Antonio J. Fontenele1, Thaís Feliciano1, Leandro A. A. Aguiar1, Nivaldo A. P. de Vasconcelos2,3, Carina Soares-Cunha2,3, Bárbara Coimbra2,3, Ana João Rodrigues2,3, Nuno Sousa2,3, Mauro Copelli1, and Pedro V. Carelli1,†

  • 1Departamento de Física, Universidade Federal de Pernambuco, Recife, PE 50670-901, Brazil
  • 2Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, 4710-057, Portugal
  • 3ICVS/3B's–PT Government Associate Laboratory, Braga/Guimarães, 4806-909, Portugal

  • *nastaran@df.ufpe.br
  • pedro.carelli@ufpe.br

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Vol. 102, Iss. 1 — July 2020

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