Post-stimulus encoding of decision confidence in EEG: toward a brain-computer interface for decision making.
Nitin Sadras1, Omid G Sani1, Parima Ahmadipour1
1Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States of America.
Journal of Neural Engineering
|July 31, 2023
Summary
Researchers decoded human decision confidence from brain activity using electroencephalography (EEG). This finding supports brain-computer interfaces (BCIs) that can enhance decision-making by providing timely assistance based on confidence levels.
Area of Science:
- Neuroscience
- Cognitive Science
- Biomedical Engineering
Background:
- Humans assess their decision accuracy, a trait known as subjective confidence.
- Decoding confidence from brain activity could enable brain-computer interfaces (BCIs) to improve decision performance.
- Prior research indicates confidence is encoded in brain signals, but its timing (stimulus-locked vs. response-locked) and pre-response decodability remain unclear.
Purpose of the Study:
- To determine if subjective confidence can be decoded from stimulus-locked, pre-response electroencephalography (EEG) signals.
- To investigate the temporal characteristics of neural correlates of confidence.
- To assess the feasibility of using decoded confidence for a BCI to enhance decision-making.
Main Methods:
- Collected high-density EEG data during a perceptual decision task with realistic stimuli.
- Implemented a task design with a post-stimulus gap to differentiate stimulus-locked from response-locked neural activity.
- Employed event-related potential and source-localization analyses, alongside a comparison of classification algorithms.
Main Results:
- Neural correlates of confidence were found to be stimulus-locked.
- The absence of a post-stimulus gap could lead to misinterpreting confidence correlates as response-locked.
- Single-trial, stimulus-locked, pre-response EEG allowed reliable decoding of confidence.
- A simulated BCI framework demonstrated that decoded confidence can improve decision performance, especially in challenging tasks.
Conclusions:
- Subjective confidence is reliably encoded in stimulus-locked, pre-response EEG signals.
- Non-invasive EEG-based BCIs are feasible for real-time decision support.
- This technology has the potential to enhance human decision-making accuracy and efficiency.
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