Structural Brain Correlates of Speech Disfluency in Early Childhood: A Dimensional Analysis in a Non-Clinical Cohort

Most neuroimaging studies of speech disfluency have compared individuals who stutter with fluent controls. However, treating speech disfluency as a continuous, dimensional trait offers new insights into the neural basis of fluency during early childhood. This study aimed to investigate whether naturally occurring variation in speech disfluency is associated with grey matter structure in a non-clinical, population-based sample of 5-year-old children. The study included 120 participants (65M, 55F) from the FinnBrain Birth Cohort study. Speech disfluency was evaluated as a continuous measure from audiovisual speech samples, with transcription and analysis conducted using the SALT software. Ambrose & Yairi (1999) classification system was used to categorize speech disfluencies into stuttering-like (SLD) and other disfluency types. T1-weighted images obtained through magnetic resonance imaging were analyzed using voxel-based morphometry (VBM) with the CAT12 toolbox and complemented by surface-based morphometry with FreeSurfer. Whole-brain statistical analysis was employed to examine the association between grey matter metrics and speech disfluency. We found that VBM-derived proportional grey matter volume in the left middle frontal gyrus, left posterior cerebellum, and right superior frontal gyrus was positively associated with speech disfluency, specifically SLD, in children (p <.001; p=.002; p <.001, FDR corrected). No significant associations were found for cortical thickness or surface area. Additionally, no notable sex differences were observed. Our findings suggest that speech disfluency in early childhood is linked to localized structural differences in regions supporting motor planning and cognitive control, without broader changes in cortical thickness or surface area. Importantly, similar brain regions have been implicated in studies comparing children who stutter to those who do not, suggesting that normal variation in disfluency captures meaningful neurobiological differences even in non-clinical populations. This supports the value of treating speech disfluency as a spectrum and underscores the importance of longitudinal, multimodal research to clarify how these structural features evolve and influence later fluency outcomes.