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How networked brain changes when working memory load reaches the capacity?

机译:网络后脑如何在工作内存负荷达到容量时发生变化?

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Evidence from behavioral studies has suggested a capacity existed in working memory (WM). As functional connectivity in brain network has been introduced into research field of WM mechanism, the aim of this study is to investigate what happens in functional connectivity and causal flow in networked brain while WM load reaches the capacity. 32-channel electroencephalography (EEGs) was recorded from 8 healthy subjects while they performed a visual working memory task with load 1-6. Short-time Fourier transform was used to determine the principal frequency range (theta) during WM. Functional connectivity among theta components of EEGs was estimated by directed transform function (DTF). Information transform was described by causal flow. The results averaged in 10 trials for each subject show that the connectivity strength increased with load increasing from 1 to 4, peaked at load 4, and decreased after the load reached 4. The causal flow with source Fz showed the similar tendency as DTF. These findings could lead to improve understanding the capacity-related neural mechanism in WM from the view of functional connection and causal flow in the networked brain.
机译:行为研究的证据表明,工作记忆(WM)中存在容量。随着脑网络中的功能连接已被引入WM机制的研究领域,本研究的目的是调查网络大脑中功能连通性和因果流量的影响,而WM负荷达到容量。 32通道脑电图(EEGS)从8个健康的受试者记录,同时使用负载1-6进行可视工作存储器任务。短时傅里叶变换用于在WM期间确定主频率范围(θ)。通过定向变换函数(DTF)估计EEG的θ组件之间的功能连接。通过因果流来描述信息变换。每个主题的10个试验中平均的结果表明,连接强度随着载荷的增加而增加,在载荷4处达到峰值,并且在达到的负荷达到后降低4.与源FZ的因果流量显示出类似的DTF趋势。这些发现可能导致从网络大脑中的功能连接和因果流程看,改善了WM的能力相关的神经机制。

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