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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Synaptic balance due to homeostatically self-organized quasicritical dynamics

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Girardi-Schappo, Mauricio [1] ; Brochini, Ludmila [2] ; Costa, Ariadne A. [3] ; Carvalho, Tawan T. A. [4] ; Kinouchi, Osame [1]
Total Authors: 5
[1] Univ Sao Paulo, Dept Fis, FFCLRP, BR-14040901 Ribeirao Preto, SP - Brazil
[2] Univ Sao Paulo, Inst Matemat & Estat, BR-05508090 Sao Paulo, SP - Brazil
[3] Univ Fed Goias Reg Jatai, Unidade Acad Especial Ciencias Exatas, BR-75801615 Jatai, Go - Brazil
[4] Univ Fed Pernambuco, Dept Fis, BR-50670901 Recife, PE - Brazil
Total Affiliations: 4
Document type: Journal article
Source: PHYSICAL REVIEW RESEARCH; v. 2, n. 1 FEB 20 2020.
Web of Science Citations: 4

Recent experiments suggested that a homeostatic regulation of synaptic balance leads the visual system to recover and maintain a regime of power-law avalanches. Here we study an excitatory/inhibitory (E/I) mean-field neuronal network that has a critical point with power-law avalanches and synaptic balance. When short-term depression in inhibitory synapses and firing threshold adaptation are added, the system hovers around the critical point. This homeostatically self-organized quasicritical (SOqC) dynamics generates E/I synaptic current cancellation in fast timescales, causing fluctuation-driven asynchronous-irregular (AI) firing. We present the full phase diagram of the model without adaptation varying external input versus synaptic coupling. This system has a rich dynamical repertoire of spiking patterns: synchronous regular (SR), asynchronous regular (AR), synchronous irregular (SI), slow oscillations (SO), and AI. It also presents dynamic balance of synaptic currents, since inhibitory currents try and compensate excitatory currents over time, resulting in both of them scaling linearly with external input. Our model thus unifies two different perspectives on cortical spontaneous activity: both critical avalanches and fluctuation-driven AI firing arise from SOqC homeostatic adaptation and are indeed two sides of the same coin. (AU)

FAPESP's process: 16/24676-1 - Context trees applied to the statistical modeling of neural spike trains
Grantee:Ludmila Brochini Rodrigues
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat
Grantee:Oswaldo Baffa Filho
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 19/12746-3 - Phase transitions in neuroscience
Grantee:Osame Kinouchi Filho
Support Opportunities: Scholarships abroad - Research
FAPESP's process: 16/00430-3 - Computational simulations of stochastic integrate-and-fire neurons balanced networks
Grantee:Ariadne de Andrade Costa
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 18/09150-9 - Stochastic and/or computational modeling of the brain functioning
Grantee:Mauricio Girardi Schappo
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 16/20945-8 - Impact of Connection Topology on the Dynamics of Stochastic Integrate-and-Fire Neuronal Network
Grantee:Ariadne de Andrade Costa
Support Opportunities: Scholarships abroad - Research Internship - Post-doctor