Characterizing developmental changes in infant habituation using functional change point detection

Habituation is an early-developing cognitive process linked to learning, typically reflected in functional near-infrared spectroscopy (fNIRS) studies as a reduction in evoked hemodynamic response amplitude. Conventional fNIRS analyses rely on linear time-invariance assumptions, potentially limiting insight into how responses evolve across repeated stimulus presentations.

To determine whether functional change point (FCPt) detection can characterize trial-specific changes in the infant hemodynamic response and reveal developmental differences in habituation timing.

Functional data analysis (FDA) treats entire response curves as statistical objects. Within this framework, FCPt detection identifies statistically significant structural shifts in the mean response across trials. FCPt detection with wild binary segmentation was applied to group-level infant fNIRS data ( $n=204$ ) collected from infants living in rural Gambia at 5, 8, and 12 months of age during a habituation and novelty detection paradigm.

Significant changes were identified within auditory cortical regions. A high proportion of detected change points corresponded to decreases in response magnitude at 8 and 12 months. Weighted ordinal regression revealed an age-related shift toward earlier occurrence of decreasing change points, with older infants' change points detected earlier within the trial sequence.

FCPt detection provides temporal information on the infant hemodynamic response unavailable to conventional analysis. At the group level, this additional information has revealed an age-related difference in habituation timing during the first year of life, with older infants completing habituation sooner. This represents a previously overlooked developmental change in the habituation response. Future work on individual-level data may seek to investigate these findings with greater granularity.