Subject- and task-independent neural correlates and prediction of decision confidence in perceptual decision making
نویسندگان
چکیده
Abstract Objective. In many real-world decision tasks, the information available to maker is incomplete. To account for this uncertainty, we associate a degree of confidence every decision, representing likelihood that being correct. study, analyse electroencephalography (EEG) data from 68 participants undertaking eight different perceptual decision-making experiments. Our goals are investigate (1) whether subject- and task-independent neural correlates exist, (2) what it possible build brain computer interfaces can estimate on trial-by-trial basis. The experiments cover wide range which allowed separate task-related, features ones. Approach. systems train artificial networks predict in each EEG response times. We compare decoding performance with three training approaches: single subject, where both testing were acquired same person; multi-subject, all pertained task, but came users; (3) multi-task, tasks subjects. Finally, validated our multi-task approach using two additional experiments, was not reported. Main results. found significant differences levels stimulus-locked response-locked epochs. All approaches able between 15% 35% better than corresponding reference baselines. Significance. results suggest making could be reconstructed signals even when transfer learning approaches. These estimates based process rather just confidence-reporting process.
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ژورنال
عنوان ژورنال: Journal of Neural Engineering
سال: 2021
ISSN: ['1741-2560', '1741-2552']
DOI: https://doi.org/10.1088/1741-2552/abf2e4