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2014 journal original-research Front Hum Neurosci

Diffusion imaging of cerebral white matter in persons who stutter: evidence for network-level anomalies

Cai S, Tourville JA, Beal DS, Perkell JS, Guenther FH, Ghosh SS

Identifiers and access

DOI
10.3389/fnhum.2014.00054
PubMed
24611042
PMC
PMC3920071
PDF
Open-access copy →
Cited by
105

Key findings

Probabilistic tractography across 28 bilateral speech-cortex ROIs showed that persons who stutter had weaker network-level cortico-cortical connectivity than fluent speakers, with components — particularly left ventral premotor and middle primary motor cortex — negatively correlated with stuttering severity.

Abstract

Source: pubmed

Deficits in brain white matter have been a main focus of recent neuroimaging studies on stuttering. However, no prior study has examined brain connectivity on the global level of the cerebral cortex in persons who stutter (PWS). In the current study, we analyzed the results from probabilistic tractography between regions comprising the cortical speech network. An anatomical parcellation scheme was used to define 28 speech production-related ROIs in each hemisphere. We used network-based statistic (NBS) and graph theory to analyze the connectivity patterns obtained from tractography. At the network-level, the probabilistic corticocortical connectivity from the PWS group were significantly weaker than that from persons with fluent speech (PFS). NBS analysis revealed significant components in the bilateral speech networks with negative correlations with stuttering severity. To facilitate comparison with previous studies, we also performed tract-based spatial statistics (TBSS) and regional fractional anisotropy (FA) averaging. Results from tractography, TBSS and regional FA averaging jointly highlight the importance of several regions in the left peri-Rolandic sensorimotor and premotor areas, most notably the left ventral premotor cortex (vPMC) and middle primary motor cortex, in the neuroanatomical basis of stuttering.

Topics

  • speech-voice-biomarkers
  • connectomics-circuits

Lab authors

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