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

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.

Keywords: EEG; functional connectivity; graph theoretical analysis; lower alpha; mental fatigue; mid-task break; sustained attention.

Figure 1

Experiment protocol. The experiment contained two sessions, each of which consists of 7 blocks. A resting block was presented in the middle of task blocks in session 2, while task blocks in session 1 were all successive. The interval between two sessions was approximate 1 week. The detail of the task block is illustrated in the middle rectangle. Each task block comprised 150 trials, each of which lasted 2 seconds. One of four letters (“q,” “p,” “b,” “d”) was displayed in the first 200 ms, followed by a fixation cross presentation during the remaining 1800 ms.

Figure 2

Behavioral data. Inverse efficiency score is derived from that average reaction time within a task block is divided by response accuracy of that task block, which was calculated for each subject. Red bars represent average behavioral measures across subjects for session 1, while blue bars are for session 2 (light colors indicate the first task block and dark colors indicate the fourth task block). Gray error bars represent standard errors. Asterisks at the top indicate those pairs with statistically significant difference by the post-hoc t-test (^*p < 0.05, ^**p < 0.005, ^***p < 0.0005). The table at the bottom lists means and standard errors (SEM) of inverse efficiency score.

Figure 3

Means and standard errors of graph metrics of functional connectivity. Bars represent means averaged across subjects and error bars indicate corresponding standard errors. Asterisks are used to mark those pairs with statistically significant difference (^*p < 0.05, ^**p < 0.005).

Figure 4

Topographies of betweenness centrality and connectivity differences between the fourth task block (T4) and the first task block (T1). The left column of topographies shows the betweenness centrality differences on each node (T4−T1). Black dots indicate those nodes that have a significant block effect (LMM at the level of 0.05) and also have a significant difference between T4 and T1 (post-hoc two-tailed paired t-test at the level of 0.05). The right column shows average differences of synchrony connectivity between T4 and T1 (T4−T1) over subjects. The connectivity edges shown in the right topographies are the top 30% differences that present in more than half number of subjects (> 10). The width of lines encodes connectivity strength (the wider the line, the stronger the connectivity between them). Solid red lines indicate that connectivity in T4 was stronger than that in T1, while dashed blue lines indicate weaker connectivity in T4.