The large-scale structural connectome of task-specific focal dystonia

Sandra Hanekamp, Kristina Simonyan, Sandra Hanekamp, Kristina Simonyan

Abstract

The emerging view of dystonia is that of a large-scale functional network disorder, in which the communication is disrupted between sensorimotor cortical areas, basal ganglia, thalamus, and cerebellum. The structural underpinnings of functional alterations in dystonia are, however, poorly understood. Notably, it is unclear whether structural changes form a larger-scale dystonic network or rather remain focal to isolated brain regions, merely underlying their functional abnormalities. Using diffusion-weighted imaging and graph theoretical analysis, we examined inter-regional white matter connectivity of the whole-brain structural network in two different forms of task-specific focal dystonia, writer's cramp and laryngeal dystonia, compared to healthy individuals. We show that, in addition to profoundly altered functional network in focal dystonia, its structural connectome is characterized by large-scale aberrations due to abnormal transfer of prefrontal and parietal nodes between neural communities and the reorganization of normal hub architecture, commonly involving the insula and superior frontal gyrus in patients compared to controls. Other prominent common changes involved the basal ganglia, parietal and cingulate cortical regions, whereas premotor and occipital abnormalities distinctly characterized the two forms of dystonia. We propose a revised pathophysiological model of focal dystonia as a disorder of both functional and structural connectomes, where dystonia form-specific abnormalities underlie the divergent mechanisms in the development of distinct clinical symptomatology. These findings may guide the development of novel therapeutic strategies directed at targeted neuromodulation of pathophysiological brain regions for the restoration of their structural and functional connectivity.

Keywords: DWI; focal hand dystonia; laryngeal dystonia; motor control.

Conflict of interest statement

The authors declare no conflicts of interest.

© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.

Figures

FIGURE 1
FIGURE 1
An overview of the imaging processing pipeline. (1) The uniform T1‐weighted image was skull‐stripped by segmenting gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF), multiplying the resulting whole‐brain mask to the image; (2) the anatomical scan was transformed to match the AFNI standard reference template in Talairach‐Tournoux space; (3) motion and eddy current distortions were corrected for both the anterior–posterior (AP) and posterior–anterior (PA) diffusion‐weighted imaging (DWI) data sets using a T2‐weighted imitation image. AP and PA were combined to generate the final DWI reconstruction; (4) the diffusion ellipsoids and parameters were calculated using a nonlinear fitting method; (5) whole‐brain coverage with 116 anatomical regions of interest (ROIs) based on the macrolabel atlas was transferred into individual DWI space; (6) deterministic fiber tracking was performed in the native space between all pairs of ROIs; (7) a 116 × 116 adjacency matrix for each subject was created based on the normalized number of streamlines, thresholded, and used as the measure of structural pairwise connectivity between all ROI pairs (i.e., the nodes of the network)
FIGURE 2
FIGURE 2
Overall structural neural community architecture. (a) The 116 × 116 matrices show averaged number of streamlines between each pair of brain regions in healthy controls, patients with laryngeal dystonia and writer's cramp, respectively. The neural community partition is based on the normalized number of streamlines between each pair of regions. The modules of the network are ordered and visualized according to the community structure. (b) The connectograms shows the same modules as in (a), with nodes (circles) labeled according to their regions and the degree/strength hubs (larger circles, bold labels) distributed within each module. 3D brain view in the center of the connectograms shows the spatial distribution of neural communities, with spheres representing hubs in each module. The modules are color‐coded as follows: red—Module I, yellow—Module II, green—Module III, blue—Module IV, purple—Module V. Results were visualized with BrainNet Viewer, NeuroMArVL, and MATLAB scripts. ACC, anterior cingulate cortex; AG, angular gyrus; Amy, amygdala; Calc, calcarine gyrus; Cau, caudate nucleus; Cbl, cerebellum; Cun, cuneus; FG, fusiform gyrus; Hip, hippocampus; HG, Heschl's gyrus; Ins, insula; IOG, inferior occipital gyrus; IPL, inferior parietal lobule; ITG, inferior temp gyrus; LG, lingual gyrus; MCC, middle cingulate; MFG, middle frontal gyrus; moG, middle orbital gyrus; MOG, middle occipital gyrus; MoG, medial orbital gyrus; MTG, middle temporal gyrus; mTP, medial temp pole; OG, olfactory gyrus; OP, operculum; Pal, pallidum; PCG, postcentral gyrus; PCC, posterior cingulate cortex; PCL, paracentral lobule; PCN, precuneus; pHC, parahippocampal; pOp, pars opercularis; pOr, pars orbitalis; PrCG, precentral gyrus; pTri, pars triangularis; Put, putamen; RG, rectal gyrus; SFG, superior frontal gyrus; SMA, supplementary motor area; SmG, superior medial gyrus; SMG, supramarginal gyrus; SOG, superior occipital gyrus; SoG, superior orbital gyrus; SPL, superior parietal lobule; STG, superior temporal gyrus; Tha, thalamus; TP, temporal pole; Ver, cerebellar vermis
FIGURE 3
FIGURE 3
Hub abnormalities and clinical correlates of network‐wide alterations. (a) The 3D brain views show common and distinct abnormalities in hub formation in patients with laryngeal dystonia and writer's cramp compared to healthy controls, respectively. Larger circles depict hubs gained within the respective module; smaller circles represent hubs lost within the respective module; hubs are color‐coded based on their modular affiliation. (b) The scatterplot shows the correlation between the clinical characteristics of dystonia and altered nodal measures within the respective networks. The duration and age of dystonia onset were established as part of neurological/laryngological evaluation; dystonia severity was assessed using the Burke–Fahn–Marsden Dystonia Rating Scale (BFM), including the movement and disability scores
FIGURE 4
FIGURE 4
Significant regional alterations of the structural connectome of dystonia patients compared to healthy controls. 3D brain renderings and bar graphs show significant regional changes in nodal degree, nodal strength, and betweenness centrality in (a) patients with laryngeal dystonia and (b) patients with writer's cramp compared to healthy controls, respectively. Error bars show SD; red bars indicate increases in nodal measures in patients compared to controls; blue bars depict decreases in nodal measures in patients compared controls; gray bars show the normative values in healthy controls. ACC, anterior cingulate cortex; HC, healthy controls; Ins, insula; L, left; PCL, paracentral lobule; R, right; SMA, supplementary motor area; SPL, superior parietal lobule; TSFD, task‐specific focal dystonia

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