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Subgroup-level functional connectivity of the M1 inter-effector areas differentiating stuttering and non-stuttering children
Poster D9 in Poster Session D, Saturday, October 26, 10:30 am - 12:00 pm, Great Hall 4
Soo-Eun Chang1, Yanni Liu1, Fiona Hobler1, Hannah Becker1, Mike Angstadt1, Adriene Beltz1; 1University of Michigan
Motor cortical circuit function and anatomy have been a focus in studying the neural bases of stuttering. Recently, strong evidence supported the discovery of three “inter-effector” areas (IEAs) along the M1, interleaved between effector-specific regions (e.g., tongue, hand, feet). These IEAs are more active during action planning than movement execution and display distinct morphology and greater connectivity to brain regions involved in cognitive control, sensory processing, and movement intention. These IEAs likely support integrative functions for complex actions, with particular relevance for speech production and speech “motor” pathology like stuttering. In this study, we examined functional connectivity patterns of the three IEA areas using Group Iterative Multiple Model Estimation (GIMME), which derives group- and individual-level connectivity measures. We hypothesized that GIMME-detected connectivity would show distinct subgroup-level differences between stuttering and control groups in the (i) mid-IEA and (ii) inferior-IEA. These areas overlap with dorsal and ventral laryngeal motor cortices, respectively, which previous studies have shown to differentiate stuttering speakers from controls at baseline and change in response to intervention in terms of functional connectivity. We used CS-GIMME (Confirmatory Subgrouping GIMME), to estimate subgroup-level connections for priori known groups (stuttering, control). Connectivity results are derived at both the group and individual level, allowing us to examine subject-specific heterogeneity. CS-GIMME can detect paths between nodes (“edges”) that are consistently present for individuals within stuttering and control groups, thus facilitating our interpretation of heterogeneous connectivity maps and allowing for subgroup-specific inferences. Resting-state fMRI data were acquired from 73 children who stutter (CWS) and 76 age- and gender-matched children who do not stutter (CNS) (mean age=72 ± 22 months, age range from 38-129 months, 34 CWS girls, 40 CNS girls). Stuttering severity (SSI) range was 2-37 (17.8±6.3) (very mild ~ very severe). Data were processed using standard methods in SPM12. Subjects were included if they had at least 4 minutes of useable data (after motion censoring at FD>0.5mm) and a usable T1 image. Participant-specific time series from 8 regions of interest (ROIs) were extracted. The ROIs and their locations were selected according to average IEA coordinates reported in Gordon et al. (2023). CS-GIMME was run using a 75% threshold for group-level and 50% for sub-group-level edges. Group-level analysis revealed IEA connections with the supplementary motor cortex (SMA) and putamen (present in both groups). Subgroup-specific connections were also detected: CNS showed connections between the mid-IEA and the dorsal cerebellum, while CWS showed connections between the inferior IEA and SMA. Additionally, node centrality (number of the modeled connections involving the node) differed significantly for the mid and inferior IEAs between the groups, with CWS presenting lower centrality in the mid-IEA but higher in the inferior IEA. These results suggest that the middle and inferior IEAs develop differently in CWS, with implications for speech motor planning affected in stuttering. In future research, we will further apply GIMME to derive data-driven subgroups within the group of children who stutter to examine whether this method can help predict specific subtypes, or eventual persistence and recovery in developmental stuttering.
Topic Areas: Disorders: Developmental, Speech Motor Control