Abstract
Functional near infrared spectroscopy (fNIRS) delivers a flexible, portable, and wearable technique for monitoring brain function in situations where fMRI is not feasible, not suitable, or inaccessible. However, variations in optode locations and head shapes and sizes throughout development lead to considerable challenges in group-based and longitudinal studies that generally use either channel-focused analyses or image reconstruction techniques that require strong participant-atlas correspondence. We present a scalp-based parcellation technique that compensates for variation in optode array placement and general head morphology and accounts for fNIRS spatial sampling with minimal assumptions about the underlying head and brain structure to support robust statistical analyses.
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