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Updated: Jan 22, 2026

Revised and Neuroimaging-Compatible Versions of the Dual Task Screen
Published on: October 5, 2020
Cerebral cortical networking for mental workload assessment under various demands during dual-task walking
Emma P Shaw1,2,3, Jeremy C Rietschel2,4, Isabelle M Shuggi1,2
1Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA.
Abstract:
While several studies have examined attentional reserve (via event-related potentials) and mental effort (via EEG spectral content) from various cortical regions during dual-task walking, none have assessed changes in the magnitude of interregional (cortico-cortical) communication as a measure of mental workload. Therefore, by deploying a traditional montage of electrode sites centered over the motor planning region as well as a more comprehensive graph theory-based approach encompassing the entire scalp, this study aimed to systematically examine changes in the magnitude of functional connectivity underlying cortico-cortical communication to assess changes in mental workload under various levels of challenge. Specifically, the Weighted Phase Lag Index (WPLI) was computed to assess the changes in magnitude of functional connectivity as participants performed a cognitive task under two demands (low and high) and two conditions (seated and walking). The results revealed enhanced fronto-centro-temporo-parietal theta connectivity during dual-task walking relative to being seated as well as a reduced inhibition of fronto-centro-temporo-parieto-occipital alpha networking as the demand on the secondary cognitive task increased. Collectively, these findings may reflect greater recruitment of task relevant processes to respond to increased cognitive-motor demands and thus an elevation of mental workload in an effort to maintain performance under varying levels of challenge. This work has the potential to inform future mental workload assessment applications in patient populations, including those who employ prostheses during cognitive-motor performance under various task demands.
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