Mid-Task Break Improves Global Integration of Functional Connectivity in Lower Alpha Band.

Junhua Li,Yu Sun,Julian Lim,Anastasios Bezerianos,Yu Chen,Kianfoong Wong,Nitish Thakor

doi:10.3389/fnhum.2016.00304

Junhua Li, Yu Sun + Show 5 more

Open Access

https://doi.org/10.3389/fnhum.2016.00304

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Abstract

Numerous efforts have been devoted to revealing neurophysiological mechanisms of mental fatigue, aiming to find an effective way to reduce the undesirable fatigue-related outcomes. Until recently, mental fatigue is thought to be related to functional dysconnectivity among brain regions. However, the topological representation of brain functional connectivity altered by mental fatigue is only beginning to be revealed. In the current study, we applied a graph theoretical approach to analyse such topological alterations in the lower alpha band (8~10 Hz) of EEG data from 20 subjects undergoing a two-session experiment, in which one session includes four successive blocks with visual oddball tasks (session 1) whereas a mid-task break was introduced in the middle of four task blocks in the other session (session 2). Phase lag index (PLI) was then employed to measure functional connectivity strengths for all pairs of EEG channels. Behavior and connectivity maps were compared between the first and last task blocks in both sessions. Inverse efficiency scores (IES = reaction time/response accuracy) were significantly increased in the last task block, showing a clear effect of time-on-task in participants. Furthermore, a significant block-by-session interaction was revealed in the IES, suggesting the effectiveness of the mid-task break on maintaining task performance. More importantly, a significant session-independent deficit of global integration and an increase of local segregation were found in the last task block across both sessions, providing further support for the presence of a reshaped topology in functional brain connectivity networks under fatigue state. Moreover, a significant block-by-session interaction was revealed in the characteristic path length, small-worldness, and global efficiency, attributing to the significantly disrupted network topology in session 1 in comparison of the maintained network structure in session 2. Specifically, we found increased nodal betweenness centrality in several channels resided in frontal regions in session 1, resembling the observations of more segregated global architecture under fatigue state. Taken together, our findings provide insights into the substrates of brain functional dysconnectivity patterns for mental fatigue and reiterate the effectiveness of the mid-task break on maintaining brain network efficiency.

Highlights

Mental fatigue commonly occurs after a prolonged period engaging in a cognitive task (Boksem and Tops, 2008), especially in a boring and repetitive task
Betweenness centrality results showed that important nodes were localized in frontal cortex under fatigue state whereas this localization was not appeared when the midtask break interrupted the task blocks
We designed a visual oddball task experiment to investigate the connectivity topology associated with mental fatigue and the effect of a mid-task break on topology alteration of mental fatigue

Summary

Introduction

Mental fatigue commonly occurs after a prolonged period engaging in a cognitive task (Boksem and Tops, 2008), especially in a boring and repetitive task. Much effort has been devoted to investigating the neurophysiological mechanism of mental fatigue (Boksem et al, 2005; Simon et al, 2011; Craig et al, 2012; Käthner et al, 2014; Sun et al, 2014) In these studies, a diversity of paradigms, ranging from trial-based sustained attention tasks, e.g., psychomotor vigilance test (Lim et al, 2012; Sun et al, 2014) to more realistic scenario, e.g., car-driving simulation (Lin et al, 2010), were employed to induce mental fatigue. In our previous neuroimaging study of sustained attention (Lim et al, 2010), we found that cerebral blood flow in the fronto-parietal regions tends to decrease as time-ontask (TOT) increases, possibly reflecting a depletion of neural resources, or an inability to retrieve these resources (Langner et al, 2010)

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