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

Abstract

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.