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皮质网络重构与基底神经节和小脑影响的变化相一致。

Cortical network reconfiguration aligns with shifts of basal ganglia and cerebellar influence.

作者信息

Nestor Kimberly, Rasero Javier, Betzel Richard, Gianaros Peter J, Verstynen Timothy

机构信息

Department of Psychology, Carnegie Mellon University, Pittsburgh PA, USA.

Center for the Neural Basis of Cognition, Pittsburgh PA, USA.

出版信息

ArXiv. 2024 Aug 15:arXiv:2408.07977v1.

Abstract

Mammalian functional architecture flexibly adapts, transitioning from integration where information is distributed across the cortex, to segregation where information is focal in densely connected communities of brain regions. This flexibility in cortical brain networks is hypothesized to be driven by control signals originating from subcortical pathways, with the basal ganglia shifting the cortex towards integrated processing states and the cerebellum towards segregated states. In a sample of healthy human participants (N=242), we used fMRI to measure temporal variation in global brain networks while participants performed two tasks with similar cognitive demands (Stroop and Multi-Source Inference Task (MSIT)). Using the modularity index, we determined cortical networks shifted from integration (low modularity) at rest to high modularity during easier i.e. congruent (segregation). Increased task difficulty (incongruent) resulted in lower modularity in comparison to the easier counterpart indicating more integration of the cortical network. Influence of basal ganglia and cerebellum was measured using eigenvector centrality. Results correlated with decreases and increases in cortical modularity respectively, with only the basal ganglia influence preceding cortical integration. Our results support the theory the basal ganglia shifts cortical networks to integrated states due to environmental demand. Cerebellar influence correlates with shifts to segregated cortical states, though may not play a causal role.

摘要

哺乳动物的功能架构具有灵活的适应性,从信息分布于整个皮层的整合状态,转变为信息集中于紧密连接的脑区群落的分离状态。据推测,皮层脑网络的这种灵活性是由源自皮层下通路的控制信号驱动的,基底神经节使皮层向整合处理状态转变,而小脑则使其向分离状态转变。在一个健康人类参与者样本(N = 242)中,我们使用功能磁共振成像(fMRI)来测量全局脑网络的时间变化,同时参与者执行两项具有相似认知需求的任务(斯特鲁普任务和多源推理任务(MSIT))。使用模块化指数,我们确定皮层网络从静息时的整合状态(低模块化)转变为较容易的即一致状态(分离)时的高模块化。与较容易的对应任务相比,任务难度增加(不一致)导致模块化降低,表明皮层网络的整合程度更高。使用特征向量中心性来测量基底神经节和小脑的影响。结果分别与皮层模块化的降低和增加相关,只有基底神经节的影响先于皮层整合出现。我们的结果支持这样一种理论,即基底神经节由于环境需求将皮层网络转变为整合状态。小脑的影响与向分离的皮层状态的转变相关,尽管可能不发挥因果作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1954/12281889/fd3ca50fa0a2/nihpp-2408.07977v2-f0001.jpg

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