Frontiers in Biomedical Technologies (Jun 2022)
Time-frequency Analysis of Electroencephalogram Signals in a Perceptual Decision-Making Task of Random Dot Kinematograms
Abstract
Purpose: Perceptual decision-making is the act of choosing one option from a set of alternatives based on available sensory information. Regarding the serious role of this act in human personal and social lives, the neurophysiological analysis of the brain during this type of decision is of great interest. In this research, the underlying neural mechanism of these decisions is investigated using a perceptual decision-making Electroencephalogram (EEG) dataset with a perceptual discrimination task. Materials and Methods: An online available dataset containing the pre-processed EEG signals of 24 healthy participants during the perceptual decision-making task of Random Dot Kinematograms was used. After a secondary pre-processing stage, clean EEG signal was divided into 1.3-second segments and averaged for Event-Related Potential (ERP) and Event-Related Spectral Perturbation (ERSP) calculations. The task engagement index was also calculated and averaged among all participants. Results: According to the results, the amplitude of the N200 component in O1 and O2 channels was larger for correct choices than incorrect ones. Furthermore, in the O2 channel, it was observed that the average alpha power near 200 milli-seconds after stimulus onset was slightly higher in high and low confidence choices than medium confidence choices. The beta band power in the PO2 channel was also higher for correct choices rather than incorrect ones in this interval. Moreover, the results represented that the task engagement index was higher in medium confidence choices, especially in occipital and parieto-occipital channels. Conclusion: The larger N200 amplitude and the higher beta power for correct choices, and the lower alpha power for medium confidence choices may be due to more attention of the individuals to the stimuli. This phenomenon can be observed in the task engagement indices as well. This could be because the user expended more efforts in medium confidence to bring one of the choices to the decision threshold.
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