Peripheral physiological decoding of arousal in a boundary-avoidance task: signal validity and individualized control

OBJECTIVE: Scoring well on a task-demand label does not show that a decoder measures arousal. We ask whether peripheral physiology decodes demand better than EEG, whether the index behaves like graded arousal rather than a clock, and what a controller could do with it. Approach. We re-analysed a public boundary-avoidance flight task in which sixteen participants received EEG neurofeedback, half-sham feedback or silence. A decoder trained on peripheral signals (cardiac, respiratory, electrodermal, pupillometric) from an open-loop calibration block was compared with a retrained EEG decoder, filter-bank common spatial patterns, and motor-only and shuffled-label controls. All analyses are offline; the decoder was never in the loop. Main results. The peripheral decoder reached 93.0% within-subject AUC against 85.2% for EEG. Ring size shrinks on a fixed schedule, so accuracy alone cannot separate arousal from trial position. Three tests did: 48.6% of hard-course trials ended below the scale midpoint; the index separated the courses at matched elapsed time (p= 1.4 ×10-31), where EEG did not; and it tracked the autonomic channels. Only the peripheral index recovered an inverted-U with performance, robust in a duration-safe hazard analysis (p= 3.5 ×10-10). Arousal rose 14.1 points in the 10 s before failure; sustained between-condition differences above 7.5 points are excluded. Subjects varied reliably in how strongly excess arousal predicted failure, predictably from pre-loop calibration. Personalised control bands gave the best held-out discrimination, though at N = 16 indistinguishable from a retuned universal band. Significance. Arousal is a state of the whole body, and here the body reads it better than the scalp. The results separate three often-conflated requirements: accuracy on a demand label, validity as an arousal signal, and usefulness for control. The signal that added information over a fixed rule was distance above a band set by each subject's recent variability.

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Publication Details

Journal
Journal of Neural Engineering
Published
2026-10-15
DOI
https://doi.org/10.1088/1741-2552/aeb4ec
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00

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article

Peripheral physiological decoding of arousal in a boundary-avoidance task: signal validity and individualized control

Paul Sajda, Anirudh Meyyappan Natarajan
Journal of Neural Engineering
EEG and Brain-Computer Interfaces
article

Peripheral physiological decoding of arousal in a boundary-avoidance task: signal validity and individualized control

Paul Sajda, Anirudh Meyyappan Natarajan
article en

Abstract

OBJECTIVE: Scoring well on a task-demand label does not show that a decoder measures arousal. We ask whether peripheral physiology decodes demand better than EEG, whether the index behaves like graded arousal rather than a clock, and what a controller could do with it. Approach. We re-analysed a public boundary-avoidance flight task in which sixteen participants received EEG neurofeedback, half-sham feedback or silence. A decoder trained on peripheral signals (cardiac, respiratory, electrodermal, pupillometric) from an open-loop calibration block was compared with a retrained EEG decoder, filter-bank common spatial patterns, and motor-only and shuffled-label controls. All analyses are offline; the decoder was never in the loop. Main results. The peripheral decoder reached 93.0% within-subject AUC against 85.2% for EEG. Ring size shrinks on a fixed schedule, so accuracy alone cannot separate arousal from trial position. Three tests did: 48.6% of hard-course trials ended below the scale midpoint; the index separated the courses at matched elapsed time (p= 1.4 ×10-31), where EEG did not; and it tracked the autonomic channels. Only the peripheral index recovered an inverted-U with performance, robust in a duration-safe hazard analysis (p= 3.5 ×10-10). Arousal rose 14.1 points in the 10 s before failure; sustained between-condition differences above 7.5 points are excluded. Subjects varied reliably in how strongly excess arousal predicted failure, predictably from pre-loop calibration. Personalised control bands gave the best held-out discrimination, though at N = 16 indistinguishable from a retuned universal band. Significance. Arousal is a state of the whole body, and here the body reads it better than the scalp. The results separate three often-conflated requirements: accuracy on a demand label, validity as an arousal signal, and usefulness for control. The signal that added information over a fixed rule was distance above a band set by each subject's recent variability.

Journal of Neural Engineering
Columbia University (US)
U.S. Department of Defense, Strong, Air Force Office of Scientific Research, Army Research Laboratory
Good health and well-being
Openalex Percentile: Top 14%
EEG and Brain-Computer Interfaces
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