Abstract

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

Highlights

  • The results of the study are reported. These are divided into three areas: Neural correlates of confidence decision, in which we analysed the neural correlates of confidence in a large dataset of eight different experiments and 68 participants

  • Neural correlates of decision confidence As we have seen in figures 2 and 3 different event-related potentials (ERP) are associated with different levels of confidence

  • In this study we have shown that there is a difference in the ERPs elicited during the decision-making process for different confidence values

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Summary

Introduction

Decision-making A decision is the result of a process that integrates contextual cues and pre-existing knowledge to commit to a categorical choice to achieve a particular goal. It has been shown that during the decision-making process the human brain weighs and integrates multiple noisy sources of information over time [1,2,3,4,5]. A meta-cognitive evaluation of the decision is generated: the confidence [6,7,8], which reflects the perceived probability of being correct and is generally correlated with the accuracy, to other behavioural and physiological measures, such as the response time (RT) [9,10,11,12,13,14,15]. The activity in the pre-frontal [21, 22] and parietal [23, 24] cortices correlates with the confidence reported by human participants

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