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Pupil responses during n‑back show high test–retest reliability, authors report

Gergely L. Bényei and Péter Pajkossy report in Scientific Reports (2026) that pupil-size responses during the n‑back working memory task exhibit substantial test–retest reliability and track task difficulty and behavioral performance.

The authors measured pupil diameter with high-resolution eye tracking while participants performed n‑back blocks at multiple memory loads across repeated sessions. They compared physiological traces to reaction times and accuracy and used intraclass correlation coefficients (ICC) to quantify stability across sessions.

Higher working-memory load produced larger, time-locked pupil dilations, and those dilation patterns showed high ICC values at the individual level, the paper states. The study also reports correlations between pupil dynamics and behavioral measures, suggesting the pupil signal reflects both momentary cognitive effort and consistent individual differences in load-related arousal.

Bényei and Pajkossy applied baseline correction, artifact rejection and controlled for known confounds including ambient lighting, fatigue and circadian factors to reduce non-task noise. They discuss the pupil signal in the context of locus coeruleus–norepinephrine modulation, linking the physiological measure to a putative neuromodulatory mechanism.

The authors note limits on generalisability and call for larger, more diverse samples and additional task paradigms. They also provide methodological details intended to help standardise pupillometry preprocessing and reliability reporting across labs. The paper is available at https://doi.org/10.1038/s41598-026-46731-3.

For neurotechnology and applied monitoring, the study strengthens the case for using pupil metrics as a repeatable index of cognitive load, while stressing that broader validation is still needed before clinical or real-world deployment.

Photo credit: bioengineer.org

Tags: pupillometry, n-back task, working memory, test–retest reliability

Topics: Wearable neurotech, EEG & neuro-sensing headsets, Neuroscience & neuroplasticity