NeurophotonicsBioengineeringPeer-reviewed journal article
High-Density Multi-Distance fNIRS Enhances Detection of Brain Activity during a Word-Color Stroop Task
Jessica E. AndersoniD, Laura B. CarltoniD, Sreekanth KuraiD, Walker Joseph O’BrieniD, De’Ja RogersiD, Parisa Hajirahimi, Parya Y. Farzam, MH Zaman, David A. BoasiD, Meryem A. YüceliD
Abstract
STRUCTURED ABSTRACTO_ST_ABSSignificanceC_ST_ABSFunctional Near-Infrared Spectroscopy (fNIRS) enables neuroimaging in scenarios where other modalities are less suitable, such as during motion tasks or in low-resource environments. Sparse fNIRS arrays with 30mm channel spacing are widely used but have limited spatial resolution. High-density (HD) arrays with overlapping, multi-distance channels improve sensitivity and localization but increase costs and setup times. A statistical comparison of HD and sparse arrays is needed for evaluating the benefits and trade-offs of HD arrays. AimThis study provides a statistical comparison of HD and sparse fNIRS performance to inform array selection in future research. ApproachWe measured prefrontal cortex (PFC) activation during congruent and incongruent Word-Color Stroop (WCS) tasks using both Sparse and HD arrays for 17 healthy adult participants, comparing dorsolateral PFC channel and image results at the group level. ResultsWhile both arrays detected activation in channel space during incongruent WCS, channel and image space results demonstrated superior localization and sensitivity with the HD array for all WCS. ConclusionsSparse channel data may suitably detect activation from cognitively demanding tasks, like incongruent WCS. However, the HD array outperformed Sparse in detecting and localizing brain activity in image space, particularly during lower cognitive load tasks, making them more suitable for neuroimaging applications.
- organism: human
- assay: imaging
- research focus: host-pathogen & immune response
- research focus: cancer & tumor microenvironment
- research focus: development & morphogenesis
- research focus: metabolism & bioenergetics
- approach: statistical model
- Citations
- 7
- FWCI
- 4.03
- Field percentile
- top 5%
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