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

机译:当工作记忆负荷达到容量时,网络化的大脑如何变化?

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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)中存在一种能力。由于脑网络中的功能连通性已被引入WM机制的研究领域,因此本研究的目的是研究在WM负载达到容量时网络连接的大脑中的功能连通性和因果流中发生了什么。记录了8位健康受试者在负荷为1-6时执行视觉工作记忆任务时的32通道脑电图(EEG)。短时傅立叶变换用于确定WM期间的主频率范围(theta)。 EEG的theta组件之间的功能连接性是通过有向变换函数(DTF)估算的。信息转换通过因果关系来描述。在10个试验中平均每个受试者的结果表明,连接强度随载荷从1增加到4而增加,在载荷4时达到峰值,在载荷达到4后下降。与源Fz的因果流显示出与DTF类似的趋势。从网络大脑中的功能连接和因果关系的角度来看,这些发现可能有助于增进对WM中与能力相关的神经机制的理解。

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