Can Ephapticity Contributes to the Brain Complexity?

Fuente: arXiv
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Autores principales: Cunha, Gabriel Moreno, Corso, Gillberto, de Sousa, Matheus Phellipe Brasil, Lima, Gustavo Zampier dos Santos
Formato: Preprint
Publicado: 2024
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author Cunha, Gabriel Moreno
Corso, Gillberto
de Sousa, Matheus Phellipe Brasil
Lima, Gustavo Zampier dos Santos
author_facet Cunha, Gabriel Moreno
Corso, Gillberto
de Sousa, Matheus Phellipe Brasil
Lima, Gustavo Zampier dos Santos
contents The inquiry into the origin of brain complexity remains a pivotal question in neuroscience. While synaptic stimuli are acknowledged as significant, their efficacy often falls short in elucidating the extensive interconnections of the brain and nuanced levels of cognitive integration. Recent advances in neuroscience have brought the mechanisms underlying the generation of highly intricate dynamics, emergent patterns, and sophisticated oscillatory signals into question. Within this context, our study, in alignment with current research, posits the hypothesis that ephaptic communication may emerge as the primary candidate for unraveling optimal brain complexity. In this investigation, we conducted a comparative analysis between two types of networks utilizing the Quadratic Integrate-and-Fire Ephaptic model (QIF-E): (I) a small-world synaptic network (ephaptic-off) and (II) a mixed composite network comprising a small-world synaptic network with the addition of an ephaptic network (ephaptic-on). Utilizing the Multiscale Entropy methodology, we conducted an in-depth analysis of the responses generated by both network configurations, with complexity assessed by integrating across all temporal scales. Our findings demonstrate that ephaptic coupling enhances complexity under specific topological conditions, considering variables such as time, spatial scales, and synaptic intensity. These results offer fresh insights into the dynamics of communication within the nervous system and underscore the fundamental role of ephapticity in regulating complex brain functions.
format Preprint
id arxiv_https___arxiv_org_abs_2404_17073
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Can Ephapticity Contributes to the Brain Complexity?
Cunha, Gabriel Moreno
Corso, Gillberto
de Sousa, Matheus Phellipe Brasil
Lima, Gustavo Zampier dos Santos
Neurons and Cognition
Biological Physics
The inquiry into the origin of brain complexity remains a pivotal question in neuroscience. While synaptic stimuli are acknowledged as significant, their efficacy often falls short in elucidating the extensive interconnections of the brain and nuanced levels of cognitive integration. Recent advances in neuroscience have brought the mechanisms underlying the generation of highly intricate dynamics, emergent patterns, and sophisticated oscillatory signals into question. Within this context, our study, in alignment with current research, posits the hypothesis that ephaptic communication may emerge as the primary candidate for unraveling optimal brain complexity. In this investigation, we conducted a comparative analysis between two types of networks utilizing the Quadratic Integrate-and-Fire Ephaptic model (QIF-E): (I) a small-world synaptic network (ephaptic-off) and (II) a mixed composite network comprising a small-world synaptic network with the addition of an ephaptic network (ephaptic-on). Utilizing the Multiscale Entropy methodology, we conducted an in-depth analysis of the responses generated by both network configurations, with complexity assessed by integrating across all temporal scales. Our findings demonstrate that ephaptic coupling enhances complexity under specific topological conditions, considering variables such as time, spatial scales, and synaptic intensity. These results offer fresh insights into the dynamics of communication within the nervous system and underscore the fundamental role of ephapticity in regulating complex brain functions.
title Can Ephapticity Contributes to the Brain Complexity?
topic Neurons and Cognition
Biological Physics
url https://arxiv.org/abs/2404.17073