Brain signaling becomes less integrated and more segregated with age.

IF 3.6 3区 医学 Q2 NEUROSCIENCES
Network Neuroscience Pub Date : 2024-12-10 eCollection Date: 2024-01-01 DOI:10.1162/netn_a_00389
Rostam M Razban, Botond B Antal, Ken A Dill, Lilianne R Mujica-Parodi
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引用次数: 0

Abstract

The integration-segregation framework is a popular first step to understand brain dynamics because it simplifies brain dynamics into two states based on global versus local signaling patterns. However, there is no consensus for how to best define the two states. Here, we map integration and segregation to order and disorder states from the Ising model in physics to calculate state probabilities, P int and P seg, from functional MRI data. We find that integration decreases and segregation increases with age across three databases. Changes are consistent with weakened connection strength among regions rather than topological connectivity based on structural and diffusion MRI data.

随着年龄的增长,大脑信号变得越来越不整合,越来越分离。
整合-分离框架是理解大脑动力学的一个流行的第一步,因为它将大脑动力学简化为基于全局和局部信号模式的两种状态。然而,对于如何最好地定义这两种状态并没有达成共识。在这里,我们将整合和分离映射到物理中的Ising模型中的有序和无序状态,以从功能MRI数据中计算状态概率,P int和P seg。我们发现,在三个数据库中,随着年龄的增长,集成减少,隔离增加。这些变化与基于结构和扩散MRI数据的区域间连接强度减弱而不是拓扑连接相一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Network Neuroscience
Network Neuroscience NEUROSCIENCES-
CiteScore
6.40
自引率
6.40%
发文量
68
审稿时长
16 weeks
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