Single-subject detection of speech network activation using functional near-infrared spectroscopy.

Overview

1. New York University, Department of Communicative Sciences and Disorders, New York, New York, United States
2. New York University, Institute of Human Development and Social Change, New York, New York, United States
3. New York University, Department of Psychology, New York, New York, United States
4. Western University, Schulich School of Medicine and Dentistry, Department of Physiology and Pharmacology, London, Ontario, Canada
5. Synapse NeuroAnalytics Inc., London, Ontario, Canada
6. Georgetown University Medical Center, Department of Neuroscience, Washington, District of Columbia, United States
7. Columbia University, Department of Applied Physics and Applied Mathematics, New York, New York, United States

Abstract

Significance: Most neuroimaging studies rely on group-level analyses, yet many clinical and translational applications require reliable inference at the level of individual participants.

Aim: We evaluated whether functional near-infrared spectroscopy (fNIRS) can detect expected speech network related activation patterns at the single-subject level.

Approach: Twenty-seven adults completed simple listening and speaking tasks while fNIRS data were recorded over bilateral frontal, temporal, and parietal regions. Data were analyzed using general linear models with false discovery rate correction and physiologically informed criteria, including expected HbO/HbR directionality and cross-chromophore coupling.

Results: Group-level analyses revealed activation patterns consistent with prior literature, with widespread HbO increases and HbR decreases. At the single-subject level, most participants showed task-related activation within predefined cortical regions, although the number and spatial distribution of significant channels varied. Speaking elicited more robust and consistent activation than listening. HbO and HbR responses were positively associated across channels, indicating coherent neurovascular coupling.

Conclusions: fNIRS can detect physiologically plausible activation patterns at the individual level, even in brief paradigms. However, variability across participants highlights the need to optimize task design and signal quality for reliable single-subject inference.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Code and Data Availability

The data and code that support the findings of this study are available from the corresponding author upon reasonable request.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 5 authors, 5 keywords, 68 references.

Cite

This paper

Koch, C., Abdalmalak, A., Orpella, J., Rottenberg, J., & Jackson, E. S. (2026). Single-subject detection of speech network activation using functional near-infrared spectroscopy. Neurophotonics, 13(3), 035009. https://doi.org/10.1117/1.nph.13.3.035009

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