Moreno Cunha Gabriel, Corso Gilberto, Brasil de Sousa Matheus Phellipe, Dos Santos Lima Gustavo Zampier
Departamento de Física Teórica e Experimental, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil.
Laboratório de Simulação e Modelagem Neurodinâmica, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil.
PLoS One. 2024 Dec 5;19(12):e0310640. doi: 10.1371/journal.pone.0310640. eCollection 2024.
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, postulates the hypothesis that ephaptic communication, in addition to synaptic mediation's, may emerge as a prime candidate for unraveling optimal brain complexity. Ephaptic communication, hitherto little studied, refers to direct interactions of the electric field between adjacent neurons, without the mediation of traditional synapses (electrical or chemical). We propose that these electric field couplings may provide an additional layer of connectivity that facilitates the formation of complex patterns and emergent dynamics in the brain. 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.
对大脑复杂性起源的探究仍然是神经科学中的一个关键问题。虽然突触刺激被认为很重要,但其功效在解释大脑广泛的互连性和认知整合的细微层面时往往不足。神经科学的最新进展对产生高度复杂动态、涌现模式和复杂振荡信号的潜在机制提出了质疑。在此背景下,我们的研究与当前研究一致,提出了一个假设,即除了突触介导之外,电突触通信可能成为解开最佳大脑复杂性的主要候选因素。电突触通信迄今为止研究较少,它指的是相邻神经元之间电场的直接相互作用,无需传统突触(电突触或化学突触)的介导。我们提出,这些电场耦合可能提供额外的连接层,促进大脑中复杂模式和涌现动态的形成。在这项研究中,我们使用二次积分发放电突触模型(QIF-E)对两种类型的网络进行了比较分析:(I)一个小世界突触网络(无电突触)和(II)一个混合复合网络,该网络由一个小世界突触网络加上一个电突触网络组成(有电突触)。利用多尺度熵方法,我们对两种网络配置产生的响应进行了深入分析,通过在所有时间尺度上进行积分来评估复杂性。我们的研究结果表明,考虑到时间、空间尺度和突触强度等变量,电突触耦合在特定拓扑条件下会增强复杂性。这些结果为神经系统内的通信动态提供了新的见解,并强调了电突触在调节复杂大脑功能中的基本作用。