Alterations of resting‐state fMRI measurements in individuals with cervical dystonia. Issue 8 (15th May 2017)

• Record Type: Journal Article
• Authors: Li, Zhihao; Prudente, Cecília N.; Stilla, Randall; Sathian, K.; Jinnah, H. A.; Hu, Xiaoping
• Is Part Of: Human brain mapping. Volume 38:Issue 8(2017)
• Page Start: 4098
• Page End: 4108
• Publication Date: 2017-05-15
• Subjects: cervical dystonia -- resting‐state fMRI -- functional connectivity -- fractional amplitude of low‐frequency fluctuation -- regional homogeneity -- support vector machine; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.23651
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: Cervical dystonia (CD) is a neurological disorder with typical symptoms of involuntary and abnormal movements and postures of the head. CD‐associated alterations of functional brain networks have not been well characterized. Previous studies of CD using resting‐state functional MRI (rfMRI) are limited in two aspects: (i) the analyses were not directly focused on the functional brain network related to head movement and (ii) rfMRI measurements other than functional connectivity (FC) were not investigated. The present study examined alterations of FC in CD by capitalizing on newly identified brain regions supporting isometric head rotation (Prudente et al.: J Neurosci 35 (2015) 9163–9172). In addition to FC, which only reflects inter‐regional signal synchronization, local, or intraregional alterations were also examined using rfMRI measurements of the fractional amplitude of low‐frequency fluctuations and regional homogeneity (ReHo). Finally, with alterations of different rfMRI measures identified, a support vector machine (SVM) learning algorithm was implemented for group classification. The results revealed both inter‐ (FC) and intra‐regional (ReHo) alterations extensively distributed in both cortical and subcortical structures; and common alterations of these measures were identified bilaterally in the postcentral gyrus as well as in the basal ganglia and thalamus. Of the rfMRI features examined, seven of them (four FC and three ReHo measures) survived the SVM procedure of recursive feature elimination and together provided the highest group classification accuracy of 90.6%. The present findings extend previous studies of rfMRI in CD and offer insight into the underlying pathophysiology of the disorder in relation to network dysfunction and somatosensory disturbances. Hum Brain Mapp 38:4098–4108, 2017 . © 2017 Wiley Periodicals, Inc.