Source Localization Algorithms to Determine Feedback Effect on the Neural Sources of P300 Component

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

The P300 event-related potentials (ERPs) has implicated in outcome evaluation and reward processing. It is controversial how reward processing affects the neural sources of P300. We try to investigate the effect of feedback on the neural sources of P300 component. Thirty healthy subjects were participated and their EEG signals were recorded by thirty channels through the start (30 minutes), feedback (60-90 minutes) and last (30 minutes) segments. We analyzed feedback segment where an equal number of audio and visual stimulus were applied to the participants to perform audio and visual recognition tasks. We punished participants for wrong answers where each wrong answer adds four more tests to this segment. The P300 component was extracted from the background EEG at all channels using the conventional time-locked synchronous grand averaging over all time frames and subjects. Next, two well-known source localization algorithms including standardize low resolution electromagnetic tomography (sLORETA) and shrinking sLORETA were applied to the P300 waveforms for estimating the activity of the P300 sources. Our finding show a significant increase in the activation of P300 sources in the feedback-locked compared to the stimulus-locked over right tempo-parieto-occipital areas (secondary association area) in visual recognition task, but difference of P300 sources is not significant in audio recognition task. The discrepancy between the audio and visual task confirms the hypothesis that our participants considered more probability of wrong answers in the audio task, but they respond to visual test with more confidence.

Language:
Persian
Published:
Iranian Journal of Biomedical Engineering, Volume:13 Issue: 4, 2019
Pages:
301 to 312
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