Neural subtypes in developmental stuttering
Nanda, S.; Gervino, G.; Pang, C. Y.; Garnett, E. O.; Usler, E.; Chugani, D. C.; Chang, S.-E.; Chow, H. M.
Show abstract
Developmental stuttering is a complex neurodevelopmental disorder characterized by disfluent speech. At the individual level, the behavioral manifestations of stuttering vary considerably, likely reflecting heterogeneity in underlying neural mechanisms. In this study, we examined individual-specific differences in the brains of children who stutter (CWS), by implementing normative modeling, a framework that quantifies how an individual deviates from an age- and sex-matched reference population. We applied this approach to identify individual-specific structural brain atypicalities using gray and white matter volumes. These volumes were derived from MRI scans from a large mixed-longitudinal dataset of 235 and 240 scans from CWS and fluent controls respectively, aged between 3 and 12 years. Individual deviation maps capturing these atypicalities were then used to cluster CWS into subtypes based on similarities in their neuroanatomical profiles. This analysis identified four neural subtypes with distinct neuroanatomical atypicalities relative to fluent controls. The key findings were a basal ganglia-thalamo-cerebellar subtype associated with higher stuttering severity and lower rates of recovery, and a white matter subtype characterized by mild severity and a higher likelihood of recovery. The remaining two subtypes showed cerebellar differences alongside alterations in brain regions involved in sensorimotor integration. Moreover, cerebellar volume atypicalities were present in all four subtypes, indicating that cerebellar alterations were present across otherwise distinct neural profiles and may represent a shared neuroanatomical feature of stuttering. These findings indicate that examining individual-specific neural differences and subtyping based on patterns of neural atypicalities provides valuable insight into the heterogeneity of developmental stuttering and represents a promising direction for improving our understanding of the disorder.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.