White matter correlates of sensorimotor synchronization in persistent developmental stuttering.

INTRODUCTION: Individuals with persistent developmental stuttering display deficits in aligning motor actions to external cues (i.e., sensorimotor synchronization). Diffusion imaging studies point to stuttering-associated differences in dorsal, not ventral, white matter pathways, and in the cerebellar peduncles. Here, we studied microstructural white matter differences between adults who stutter (AWS) and fluent speakers using two complementary approaches to: (a) assess previously reported group differences in white matter diffusivity, and (b) evaluate the relationship between white matter diffusivity and sensorimotor synchronization in each group. METHODS: Participants completed a sensorimotor synchronization task and a diffusion MRI scan. We identified the cerebellar peduncles and major dorsal- and ventral-stream language pathways in each individual and assessed correlations between sensorimotor synchronization and diffusion measures along the tracts. RESULTS: The results demonstrated group differences in dorsal, not ventral, language tracts, in alignment with prior reports. Specifically, AWS had significantly lower fractional anisotropy (FA) in the left arcuate fasciculus, and significantly higher mean diffusivity (MD) in the bilateral frontal aslant tract compared to fluent speakers, while no significant group difference was detected in the inferior fronto-occipital fasciculus. We also found significant group differences in both FA and MD of the left middle cerebellar peduncle. Comparing patterns of association with sensorimotor synchronization revealed a novel double dissociation: MD within the left inferior cerebellar peduncle was significantly correlated with mean asynchrony in AWS but not in fluent speakers, while FA within the left arcuate fasciculus was significantly correlated with mean asynchrony in fluent speakers, but not in AWS. CONCLUSIONS: Our results support the view that stuttering involves altered connectivity in dorsal tracts and that AWS may rely more heavily on cerebellar tracts to process timing information. Evaluating microstructural associations with sensitive behavioral measures provides a powerful tool for discovering additional functional differences in the underlying connectivity in AWS.

Speech rate association with cerebellar white-matter diffusivity in adults with persistent developmental stuttering.

Speech rate is a basic characteristic of language production, which affects the speaker's intelligibility and communication efficiency. Various speech disorders, including persistent developmental stuttering, present altered speech rate. Specifically, adults who stutter (AWS) typically exhibit a slower speech rate compared to fluent speakers. Evidence from imaging studies suggests that the cerebellum contributes to the paced production of speech. People who stutter show structural and functional abnormalities in the cerebellum. However, the involvement of the cerebellar pathways in controlling speech rate remains unexplored. Here, we assess the association of the cerebellar peduncles with speech rate in AWS and control speakers. Diffusion MRI and speech-rate data were collected in 42 participants (23 AWS, 19 controls). We used deterministic tractography with Automatic Fiber segmentation and Quantification (AFQ) to identify the superior, middle, and inferior cerebellar peduncles (SCP, MCP, ICP) bilaterally, and quantified fractional anisotropy (FA) and mean diffusivity (MD) along each tract. No significant differences were observed between AWS and controls in the diffusivity values of the cerebellar peduncles. However, AWS demonstrated a significant negative association between speech rate and FA within the left ICP, a major cerebellar pathway that transmits sensory feedback signals from the olivary nucleus into the cerebellum. The involvement of the ICP in controlling speech production in AWS is compatible with the view that stuttering stems from hyperactive speech monitoring, where even minor deviations from the speech plan are considered as errors. In conclusion, our findings suggest a plausible neural mechanism for speech rate reduction observed in AWS.