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Evidence for planning and motor subtypes of stuttering based on resting state functional connectivity.

Hannah P RoweJason A TourvilleAlfonso Nieto-CastanonEmily O GarnettHo Ming ChowSoo-Eun ChangFrank H Guenther
Published in: Brain and language (2024)
We tested the hypothesis, generated from the Gradient Order Directions Into Velocities of Articulators (GODIVA) model, that adults who stutter (AWS) may comprise subtypes based on differing connectivity within the cortico-basal ganglia planning or motor loop. Resting state functional connectivity from 91 AWS and 79 controls was measured for all GODIVA model connections. Based on a principal components analysis, two connections accounted for most of the connectivity variability in AWS: left thalamus - left posterior inferior frontal sulcus (planning loop component) and left supplementary motor area - left ventral premotor cortex (motor loop component). A k-means clustering algorithm using the two connections revealed three clusters of AWS. Cluster 1 was significantly different from controls in both connections; Cluster 2 was significantly different in only the planning loop; and Cluster 3 was significantly different in only the motor loop. These findings suggest the presence of planning and motor subtypes of stuttering.
Keyphrases
  • functional connectivity
  • resting state
  • transcription factor
  • machine learning
  • single cell
  • multiple sclerosis
  • spinal cord injury