Statistical complexity is maximized close to criticality in cortical dynamics

被引：14

作者：

Lotfi, Nastaran ^{[1
]}

Feliciano, Thais ^{[1
]}

Aguiar, Leandro A. A. ^{[2
]}

Lima Silva, Thais Priscila ^{[1
]}

Carvalho, Tawan T. A. ^{[1
]}

Rosso, Osvaldo A. ^{[3
]}

Copelli, Mauro ^{[1
]}

Matias, Fernanda S. ^{[3
]}

Carelli, Pedro, V ^{[1
]}

机构：

[1] Univ Fed Pernambuco, Dept Fis, BR-50670901 Recife, PE, Brazil

[2] Univ Fed Paraiba, Dept Ciencias Fundamentais & Sociais, BR-58397000 Areia, PB, Brazil

[3] Univ Fed Alagoas, Inst Fis, BR-57072970 Maceio, Alagoas, Brazil

来源：

PHYSICAL REVIEW E | 2021年 / 103卷 / 01期

基金：

巴西圣保罗研究基金会;

关键词：

D O I：

10.1103/PhysRevE.103.012415

中图分类号：

O35 [流体力学]; O53 [等离子体物理学];

学科分类号：

070204 ; 080103 ; 080704 ;

摘要：

Complex systems are typically characterized as an intermediate situation between a complete regular structure and a random system. Brain signals can be studied as a striking example of such systems: cortical states can range from highly synchronous and ordered neuronal activity (with higher spiking variability) to desynchronized and disordered regimes (with lower spiking variability). It has been recently shown, by testing independent signatures of criticality, that a phase transition occurs in a cortical state of intermediate spiking variability. Here we use a symbolic information approach to show that, despite the monotonical increase of the Shannon entropy between ordered and disordered regimes, we can determine an intermediate state of maximum complexity based on the Jensen disequilibrium measure. More specifically, we show that statistical complexity is maximized close to criticality for cortical spiking data of urethane-anesthetized rats, as well as for a network model of excitable elements that presents a critical point of a nonequilibrium phase transition.

引用

页数：7

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