Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making

Perceptual decision-making requires transforming sensory information into decisions. An ambiguity of sensory input affects perceptual decisions inducing specific time-frequency patterns on EEG (electroencephalogram) signals. This paper uses a wavelet-based method to analyze how ambiguity affects EEG features during a perceptual decision-making task. We observe that parietal and temporal beta-band wavelet power monotonically increases throughout the perceptual process. Ambiguity induces high frontal beta-band power at 0.3-0.6 s post-stimulus onset. It may reflect the increasing reliance on the top-down mechanisms to facilitate accumulating decision-relevant sensory features. Finally, this study analyzes the perceptual process using mixed within-trial and within-subject design. First, we found significant percept-related changes in each subject and then test their significance at the group level. Thus, observed beta-band biomarkers are pronounced in single EEG trials and may serve as control commands for brain-computer interface (BCI).

Automated summary

This study investigates the impact of ambiguity on EEG features during a perceptual decision-making task using a wavelet-based method, revealing changes in specific time-frequency patterns. It shows a monotonic increase in beta-band power throughout the perceptual process, with ambiguity leading to increased beta-band power in the frontal region, possibly reflecting greater reliance on top-down mechanisms. The observed beta-band biomarkers are significant in single EEG trials and could potentially be used as control commands for brain-computer interfaces (BCI).