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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 |
Published version: | http://dx.doi.org/10.1109/tcds.2020.2991301 |
Appears in Collections: | Aurora harvest 4 Computer Science publications |
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