Fronto‐Parietal Subnetworks Flexibility Compensates For Cognitive Decline Due To Mental Fatigue |
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Authors: | Fumihiko Taya Stavros I Dimitriadis Andrei Dragomir Julian Lim Yu Sun Kian Foong Wong Nitish V Thakor Anastasios Bezerianos |
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Institution: | 1. Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore;2. Singapore Institute for Neurotechnology (SINAPSE), Centre for Life Sciences, National University of Singapore, Singapore;3. Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, United Kingdom;4. Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom;5. Neuroinformatics Group, (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom;6. Neuroscience and Behavioral Disorders Program, Duke‐NUS Graduate Medical School, Singapore;7. Department of Electrical & Computer Engineering, National University of Singapore, Singapore;8. Department of Biomedical Engineering, National University of Singapore, Singapore;9. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland;10. School of Medicine, University of Patras, Greece |
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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. |
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Keywords: | community structure analysis functional brain network graph theory intermodule network metrics intramodule network metrics modular organization resting‐state fMRI |
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