Stability of dynamic functional architecture differs between brain networks and states

理论(学习稳定性) 默认模式网络 静息状态功能磁共振成像 视皮层 功能连接 动态功能连接 联想(心理学) 神经科学 功能集成 功能磁共振成像 计算机科学 感觉系统 心理学 模式识别(心理学) 人工智能 数学 机器学习 数学分析 心理治疗师 积分方程
作者
Le Li,Bin Lu,Chao‐Gan Yan
出处
期刊:NeuroImage [Elsevier BV]
卷期号:216: 116230-116230 被引量:57
标识
DOI:10.1016/j.neuroimage.2019.116230
摘要

Stable representation of information in distributed neural connectivity is critical to function effectively in the world. Despite the dynamic nature of the brain's functional architecture, characterizing its temporal stability within a continuous state has been largely neglected. Here we characterized stability of functional architecture at a dynamic timescale (~1 min) for each brain voxel by measuring the concordance of dynamic functional connectivity (DFC) over time, compared between association and unimodal regions, and established its reliability using test-retest resting-state fMRI data of adults from an open dataset. After the measure of functional stability was established, we further employed another fMRI open dataset which included movie-watching and resting-state data of children and adolescents, to explore how stability was modified by natural viewing from its intrinsic form, with specific focus on the associative and primary visual cortices. The results showed that high-order association regions, especially the default mode network, demonstrated high stability during resting-state scans, while primary sensory-motor cortices revealed relatively lower stability. During movie watching, stability in the primary visual cortex was decreased, which was associated with larger DFC variation with neighboring regions. By contrast, higher-order regions in the ventral and dorsal visual stream demonstrated increased stability. The distribution of functional stability and its modification describes a profile of the brain's stability property, which may be useful reference for examining distinct mental states and disorders.
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