Induced synchronization by endogenous noise modulation in finite-size random neural networks: A stochastic mean-field study

被引：4

作者：

Lefebvre, J. ^{[1
,2
,3
]}

Hutt, A. ^{[4
]}

机构：

[1] Univ Hlth Network, Krembil Brain Inst, Toronto, ON M5T 0S8, Canada

[2] Univ Ottawa, Dept Biol, Ottawa, ON K1N 6N5, Canada

[3] Univ Toronto, Dept Math, Toronto, ON M5S 2E4, Canada

[4] Univ Strasbourg, MIMESIS Team, ICube, MLMS,Inria Nancy Grand Est, F-67000 Strasbourg, France

来源：

CHAOS | 2023年 / 33卷 / 12期

基金：

加拿大自然科学与工程研究理事会;

关键词：

ALPHA OSCILLATIONS; SINGLE NEURONS; BRAIN; COHERENCE; DESYNCHRONIZATION; INHIBITION; WAVES; FLUCTUATIONS; ORGANIZATION; VARIABILITY;

D O I：

10.1063/5.0167771

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Event-related synchronization and desynchronization (ERS/ERD) are well-known features found experimentally in brain signals during cognitive tasks. Their understanding promises to have much better insights into neural information processes in cognition. Under the hypothesis that neural information affects the endogenous neural noise level in populations, we propose to employ a stochastic mean-field model to explain ERS/ERD in the gamma-frequency range. The work extends previous mean-field studies by deriving novel effects from finite network size. Moreover, numerical simulations of ERS/ERD and their analytical explanation by the mean-field model suggest several endogenous noise modulation schemes, which may modulate the system's synchronization.

引用

页数：12

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