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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.)

Optimal Interplay between Synaptic Strengths and Network Structure Enhances Activity Fluctuations and Information Propagation in Hierarchical Modular Networks

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Pena, Rodrigo F. O. [1] ; Lima, Vinicius [1] ; O. Shimoura, Renan [1] ; Paulo Novato, Joao [1] ; Roque, Antonio C. [1]
Total Authors: 5
[1] Univ Sao Paulo, Fac Philosophy Sci & Letters Ribeirao Preto, Dept Phys, BR-14040901 Ribeirao Preto, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: BRAIN SCIENCES; v. 10, n. 4 APR 2020.
Web of Science Citations: 0

In network models of spiking neurons, the joint impact of network structure and synaptic parameters on activity propagation is still an open problem. Here, we use an information-theoretical approach to investigate activity propagation in spiking networks with a hierarchical modular topology. We observe that optimized pairwise information propagation emerges due to the increase of either (i) the global synaptic strength parameter or (ii) the number of modules in the network, while the network size remains constant. At the population level, information propagation of activity among adjacent modules is enhanced as the number of modules increases until a maximum value is reached and then decreases, showing that there is an optimal interplay between synaptic strength and modularity for population information flow. This is in contrast to information propagation evaluated among pairs of neurons, which attains maximum value at the maximum values of these two parameter ranges. By examining the network behavior under the increase of synaptic strength and the number of modules, we find that these increases are associated with two different effects: (i) the increase of autocorrelations among individual neurons and (ii) the increase of cross-correlations among pairs of neurons. The second effect is associated with better information propagation in the network. Our results suggest roles that link topological features and synaptic strength levels to the transmission of information in cortical networks. (AU)

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: 15/50122-0 - Dynamic phenomena in complex networks: basics and applications
Grantee:Elbert Einstein Nehrer Macau
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 17/07688-9 - Computational study of hippocampal-cortical-thalamic interactions: simulating patterns of synaptic plasticity and oscillatory activity
Grantee:Renan Oliveira Shimoura
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 18/20277-0 - Computational and systems neuroscience
Grantee:Antonio Carlos Roque da Silva Filho
Support Opportunities: Regular Research Grants
FAPESP's process: 17/05874-0 - Models of neural networks with stochastic neurons and different topologies: construction and analysis
Grantee:Vinícius Lima Cordeiro
Support Opportunities: Scholarships in Brazil - Master
FAPESP's process: 13/25667-8 - Mechanisms of propagation of epileptiform activity in a large-scale cortical model
Grantee:Rodrigo Felipe de Oliveira Pena
Support Opportunities: Scholarships in Brazil - Doctorate (Direct)