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Information flow in neuronal networks of networks: oscillations, criticality and electrical synapses

Grant number: 19/15024-9
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): June 01, 2020
Effective date (End): May 31, 2022
Field of knowledge:Biological Sciences - Physiology - Physiology of Organs and Systems
Principal Investigator:Alexandre Hiroaki Kihara
Grantee:Mariana Sacrini Ayres Ferraz
Home Institution: Centro de Matemática, Computação e Cognição (CMCC). Universidade Federal do ABC (UFABC). Ministério da Educação (Brasil). Santo André , SP, Brazil
Associated research grant:15/50122-0 - Dynamic phenomena in complex networks: basics and applications, AP.TEM

Abstract

Complex network studies involve several areas of Science ranging from Physics to Neurobiology. Our brain is expected to compose one of the most complex known networks, with around 100 modules interconnected with each other, and with more than $10^{10}$ neurons. Given this high complexity, the understanding of its operation is extremely challenging. In this sense, it is known the fact that neuronal disorders affect individual neurons, which in turn influence the dynamics of neuronal networks. In fact, neuronal networks activity exhibits a complex behavior, often described as avalanches, whose spatial and temporal distributions are described by power laws, indicating that the system is in its critical state. Thus, it is hypothesized that a healthy brain would function near a phase transition, the ideal point for optimization of certain characteristics such as information storage and transmission. A relevant point in the context of neuroscience would be how neuronal signals are accessed and how they are addressed in the different functions required. Specifically, one question can be thought: what structural or dynamic parameters of the neural networks influence and provide the flow of information between them? In the present project we intend to investigate this issue with theoretical approach with network modeling of networks with neuronal dynamics, associated with experimental approach based on electrocorticographic measurements of rats during the performance of behavioral tasks. We intend to analyze the decision-making process, evaluating how memory recovery occurs and the transfer of information between the hippocampus and the prefrontal cortex. In addition, we will evaluate how these actions are affected by structural factors of the neural network, such as the electrical synapses. The analyzes will mainly involve spectral analyzes of Fourier, coherence, Granger causality, wavelet spectrum, Hurst exponent, among others. With this approach we intend to contribute to the understanding of the origins and consequences of hippocampal and prefrontal dysfunctions, as implicated in several neuropsychiatric disorders such as schizophrenia, autism and dementia. This project will count on the collaboration of researchers from UFABC and external groups, as well as being linked to a thematic project. (AU)