Fronto‐Parietal Subnetworks Flexibility Compensates For Cognitive Decline Due To Mental Fatigue

Abstract

Fronto-parietal subnetworks were revealed to compensate for cognitive decline due to mental fatigue by community structure analysis. Here, we investigate changes in topology of subnetworks of resting-state fMRI networks due to mental fatigue induced by prolonged performance of a cognitively demanding task, and their associations with cognitive decline. As it is well established that brain networks have modular organization, community structure analyses can provide valuable information about mesoscale network organization and serve as a bridge between standard fMRI approaches and brain connectomics that quantify the topology of whole brain networks. We developed inter- and intramodule network metrics to quantify topological characteristics of subnetworks, based on our hypothesis that mental fatigue would impact on functional relationships of subnetworks. Functional networks were constructed with wavelet correlation and a data-driven thresholding scheme based on orthogonal minimum spanning trees, which allowed detection of communities with weak connections. A change from pre- to posttask runs was found for the intermodule density between the frontal and the temporal subnetworks. Seven inter- or intramodule network metrics, mostly at the frontal or the parietal subnetworks, showed significant predictive power of individual cognitive decline, while the network metrics for the whole network were less effective in the predictions. Our results suggest that the control-type fronto-parietal networks have a flexible topological architecture to compensate for declining cognitive ability due to mental fatigue. This community structure analysis provides valuable insight into connectivity dynamics under different cognitive states including mental fatigue.

Spatiotemporal Dynamical Analysis of Brain Activity During Mental Fatigue Process

“…Concurring with previous studies focusing specifically on each functional subsystem [8], [51]- [61], [66], our results indicated that ACC, PCG, and PPC served as the pivotal nodes engaged in the fatigue modulation. Through community structure analyses, the fMRI study [66] reported that fronto-parietal network compensated with cognitive decline due to mental fatigue. That may explain the strong synchronized deactivation of the fronto-parietal regions in this study.…”

Frontal EEG-Based Multi-Level Attention States Recognition Using Dynamical Complexity and Extreme Gradient Boosting

“…The dynamical analysis is an extension of the EEG measures with a focus on the time sequence of EEG index or functional connectivity networks (Bola and Sabel, 2015;Pagnotta et al, 2020). Previous studies based on perfusion functional magnetic resonance imaging found that the connectivity strength of frontal-parietal network represented by topological characteristics dynamically changes to compensate the cognitive decline during long-term sustained attention task (Taya et al, 2018). The dynamical analysis represents the evolution of neural activity, mostly used is dynamic functional connectivity.…”

Mental Fatigue Has Great Impact on the Fractal Dimension of Brain Functional Network

“…Mental fatigue has become a widespread subhealthy condition in nowadays society [ 1 ]. Many researchers are dedicated to the studies of detection methods [ 2 ], neural mechanisms [ 3 ], and mitigation methods [ 4 ] of the mental fatigue, owing to the negative effects of mental fatigue on the human cognitive functions [ 5 ], especially serious in driving fatigue [ 6 ].…”