Evidence for a Resting State Network Abnormality in Adults Who Stutter

Frontiers in Integrative Neuroscience
Amir Hossein GhaderiPaul F Sowman

Abstract

Neural network-based investigations of stuttering have begun to provide a possible integrative account for the large number of brain-based anomalies associated with stuttering. Here we used resting-state EEG to investigate functional brain networks in adults who stutter (AWS). Participants were 19 AWS and 52 age-, and gender-matched normally fluent speakers. EEGs were recorded and connectivity matrices were generated by LORETA in the theta (4-8 Hz), alpha (8-12 Hz), beta1 (12-20 Hz), and beta2 (20-30 Hz) bands. Small-world propensity (SWP), shortest path, and clustering coefficients were computed for weighted graphs. Minimum spanning tree analysis was also performed and measures were compared by non-parametric permutation test. The results show that small-world topology was evident in the functional networks of all participants. Three graph indices (diameter, clustering coefficient, and shortest path) exhibited significant differences between groups in the theta band and one [maximum betweenness centrality (BC)] measure was significantly different between groups in the beta2 band. AWS show higher BC than control in right temporal and inferior frontal areas and lower BC in the right primary motor cortex. Abnormal functional netw...Continue Reading

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Citations

Feb 24, 2019·The International Journal of Neuroscience·Amir Hossein GhaderiAmir Hossein Darooneh
Jan 7, 2020·The International Journal of Neuroscience·Mojtaba JouzizadehAmir Hossein Ghaderi
Sep 19, 2020·Neural Computation·Amir Hossein GhaderiFuat Balci
Dec 5, 2019·Frontiers in Human Neuroscience·Ranit SenguptaSazzad M Nasir

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Software Mentioned

AWS
LORETA
GTA
BrainNet viewer
biograph
MATLAB
NeuroGuide

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