Effective connectivity of mental fatigue: Dynamic causal modeling of EEG data

Ghazaleh Sadat Hosseini | Ali Motie-Nasrabadi

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URL :   http://research.shahed.ac.ir/WSR/WebPages/Report/PaperView.aspx?PaperID=116921
Date :  2019/07/23
Publish in :    Technology and Health Care
DOI :  https://doi.org/ 10.3233/THC-181480
Link :  http://dx.doi.org/ 10.3233/THC-181480
Keywords :Dynamic causal modeling, effective connectivity, active cortical regions, mental fatigue

Abstract :

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Recognition of sources in the brain and their interaction with mental fatigue states are interesting subjects for researchers. OBJECTIVE: The aim of this study was to investigate the mental fatigue effects on brain areas by dynamic causal modeling (DCM) parameters that are extracted from event-related potential (ERP) signals which were then estimated based on mental fatigue data with visual stimulation. METHODS: ERP were recorded based on a Continuous Performance Task in four consecutive trials. Active regions and brain sources were extracted by a Multiple Sparse Priors algorithm. RESULTS: Four models are proposed for DCM. The parameters and the structure of the best model were obtained by SPM software for ERP in each of the four trials. CONCLUSION: The results illustrate that an increase in mental fatigue through trials leads to the increased likelihood of choosing forward models.