Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/126862
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Type: Journal article
Title: Intraindividual completion time modulates the prediction error negativity in a virtual 3D object selection task
Author: Singh, A.K.
Chen, H.T.
Gramann, K.
Lin, C.T.
Citation: IEEE Transactions on Cognitive and Developmental Systems, 2020; 12(2):354-360
Publisher: IEEE
Issue Date: 2020
ISSN: 2379-8920
2379-8939
Statement of
Responsibility: 
Avinash Kumar Singh, Hsiang-Ting Chen, Klaus Gramann and Chin-Teng Lin
Abstract: A prediction error negativity (PEN) can be observed in the human electroencephalogram when there is a mismatch between the predicted and the perceived changes in the environment. Our previous study using a virtual object selection task demonstrated an impact of the level of avatar realism on the PEN, reflecting a mismatch between visual and proprioceptive feedback about the object selection. To investigate the role of temporal integration of different sensory information on the PEN, this article investigated the impact of task completion times on the PEN amplitude, using the same virtual object selection task. Trials from each participant were divided into slow trials and fast trials based on the task completion time, and their associated PEN amplitudes were separately aggregated and analyzed. The result shows that PEN amplitudes are significantly more pronounced in slow trials than in fast trials. This finding suggests that task completion times modulate the PEN amplitude—a long task completion time allowed for a better integration of information from both visual and proprioceptive systems as the basis to detect a mismatch between the expected hand trajectory during a reaching motion and the perceived visual feedback in the virtual environment.
Keywords: Cognitive conflict; completion time; electroencephalogram (EEG); error-related positive potential (Pe); prediction error negativity (PEN); virtual reality (VR)
Rights: © 2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.
DOI: 10.1109/TCDS.2020.2991301
Grant ID: http://purl.org/au-research/grants/arc/DP180100670
http://purl.org/au-research/grants/arc/DP180100656
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Computer Science publications

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