Presentation
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Distinct functional connectivity patterns in stuttering and non-stuttering children: A confirmatory network analysis using CS-GIMME
Poster A60 in Poster Session A, Tuesday, October 24, 10:15 am - 12:00 pm CEST, Espace Vieux-Port
Soo-Eun Chang1, Yanni Liu1, Valeria Caruso1, Fiona Hobler1, Hannah Becker1, Mike Angstadt1; 1University of Michigan
Network-based analyses examining the functional architecture of brain connectivity have increased our understanding of complex neurodevelopmental and psychiatric disorders. Stuttering is a childhood-onset speech disorder that has been linked to deficits in major neural circuits including the basal ganglia thalamocortical network. One influential theoretical model (DIVA) posits that stuttering may arise due to deficits in the initiation circuit of the feedforward control system, leading stutterers to rely on a less efficient feedback control system that monitors sensory feedback for error-based processing - coordinated by the right ventral premotor cortex (RvPMC). Here we used a recent extension of a network-based analysis - Group Iterative Multiple Model Estimation (GIMME), with confirmatory subgrouping (CS-GIMME), to estimate subgroup-level connections for priori known groups (stuttering, control). Connectivity results are derived at the group as well as at the individual level, which allows for examining subject-specific heterogeneity in connectivity. CS-GIMME can detect paths between nodes (“edges”) that are consistently present for individuals within stuttering and control groups, thus facilitating our interpretation of the heterogeneous connectivity maps and allowing for subgroup-specific inferences. We hypothesized that the stuttering group would show increased connections involving the RvPMC while showing reduced connections in subcortical regions involved in initiating motor sequences. Resting-state fMRI (rsfMRI) 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 eligible to be 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 (164 functional volumes) from 17 regions of interest (ROIs) were extracted. The ROIs and their locations were selected according to regions defined in the DIVA model (Tourville & Guenther, 2011). CS-GIMME was run using a 75% threshold for both group and sub-group level edges. Results showed that for both groups, there were significant connections involving homologous regions in the two hemispheres as well as connections within subcortical regions (thalamus, globus pallidus (GP), putamen). Group-specific connectivity results showed that in the control group only, there were connections between the left thalamus and left GP and between the right SMA (initiation) and right M1 (larynx), whereas in the stuttering group only there were connections between the right SMA (initiation) and the left somatosensory cortex (larynx). Compared to controls, CWS showed heightened node degree involving the right vPMC and reduced density (number of connections) within left initiation-related regions (SMA, putamen, GP and Thalamus). These results show that CS-GIMME can derive functional connectivity results that differentiate stuttering from non-stuttering groups in pathways predicted by the DIVA model. 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, Computational Approaches