Isolated Focal Dystonia as a Disorder of Large-Scale Functional Networks

Abstract

Isolated focal dystonias are a group of disorders with diverse symptomatology but unknown pathophysiology. Although recent neuroimaging studies demonstrated regional changes in brain connectivity, it remains unclear whether focal dystonia may be considered a disorder of abnormal networks. We examined topology as well as the global and local features of large-scale functional brain networks across different forms of isolated focal dystonia, including patients with task-specific (TSD) and nontask-specific (NTSD) dystonias. Compared with healthy participants, all patients showed altered network architecture characterized by abnormal expansion or shrinkage of neural communities, such as breakdown of basal ganglia-cerebellar community, loss of a pivotal region of information transfer (hub) in the premotor cortex, and pronounced connectivity reduction within the sensorimotor and frontoparietal regions. TSD were further characterized by significant connectivity changes in the primary sensorimotor and inferior parietal cortices and abnormal hub formation in insula and superior temporal cortex, whereas NTSD exhibited abnormal strength and number of regional connections. We suggest that isolated focal dystonias likely represent a disorder of large-scale functional networks, where abnormal regional interactions contribute to network-wide functional alterations and may underline the pathophysiology of isolated focal dystonia. Distinct symptomatology in TSD and NTSD may be linked to disorder-specific network aberrations.

Keywords: community structure; dystonia; graph theory; independent component analysis; resting-state fMRI.

© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Figures

Figure 1.

Large-scale community architecture derived from modular decomposition of the group-averaged networks in (A) healthy participants, (B) patients with task-specific dystonia, and (C) patients with nontask-specific dystonia. Left panel shows 212 × 212 connectivity matrices averaged across each group with the corresponding community partitions. The color bar representsrvalues based on Pearson's correlation coefficients between each pair of regions. The right panel shows the regional distribution of neural communities on a standard brain in the Talairach–Tournoux space. The 5 network modules are color-coded as follows: yellow = Module I, green = Module II, red = Module III, purple = Module IV, blue = Module V.

Figure 2.

Distribution of shared and distinct hubs. High-strength/high-degree hubs common to healthy participants (HP), patients with task-specific dystonia (TSD), and nontask-specific dystonia (NTSD) are shown in red; hubs unique to TSD patients are shown in blue; hubs unique to NTSD patients are shown in green, and hubs unique to HP are shown in orange. Brain sections are shown as a series of axial slices of a standard brain in the Talairach–Tournoux space.

Figure 3.

Resting-state functional network alteration assessed using ICA. Panels (A-I) and (B-I) represent the extracted components relevant to dystonia across all patients and healthy participants (A-Ifor the sensorimotor andB-Ifor frontoparietal independent components). For each component, voxel-based inferential statistics were used to compare (II) all patients vs. healthy participants, and (III) TSD vs. NTSD groups. Statistical maps are superimposed on axial and sagittal sections of a standard brain in Talairach–Tournoux space. The color bars representZ-scores for independent components andtscores for group statistical comparisons (P≤ 0.05, FWE-corrected). The corresponding bar graphs of the group-averaged resting-state connectivity in the significant clusters are shown in the bottom row of the figure. SMC, sensorimotor cortex; STG, superior temporal gyrus; INS, insula; SSC, somatosensory cortex; PFC, prefrontal cortex; MTG, middle temporal gyrus; IPC, inferior parietal cortex.

Figure 4.

Overlapping alterations in functional connectivity identified with the use of ICA and graph theoretical analysis and their correlates with clinical features of dystonia. (A) The brain regions of overlapping alterations between the significant clusters in the patients vs. healthy participants ICA contrast and the significant hubs in graph analysis (see Figs  2 and 3 for reference) are shown on a series of axial brain slices in the standard Talairach–Tournoux space. For the statistical threshold of the voxels, refer to Figure  3 . (B) Scatterplot shows the significant positive correlation between the meanZ-score values in the SMA cluster identified in (A) and dystonia duration in years. (C) Bar graphs show meanZ-score values in the same SMA cluster in all healthy participants (HP), patients with nontask-specific dystonia (NTSD), and patients with task-specific dystonia (TSD). The black line indicates the median of meanZ-score values in the healthy participant group; red lines indicate the median of meanZ-score values in the patient groups.