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.

In the past few years, several studies have been directed to understanding the complexity of functional interactions between different brain regions during various human behaviors. Among these, neuroimaging research installed the notion that speech and language require an orchestration of brain regions for comprehension, planning, and integration of a heard sound with a spoken word. However, these studies have been largely limited to mapping the neural correlates of separate speech elements and examining distinct cortical or subcortical circuits involved in different aspects of speech control. As a result, the complexity of the brain network machinery controlling speech and language remained largely unknown. Using graph theoretical analysis of functional MRI (fMRI) data in healthy subjects, we quantified the large-scale speech network topology by constructing functional brain networks of increasing hierarchy from the resting state to motor output of meaningless syllables to complex production of real-life speech as well as compared to non-speech-related sequential finger tapping and pure tone discrimination networks. We identified a segregated network of highly connected local neural communities (hubs) in the primary sensorimotor and parietal regions, which formed a commonly shared core hub network across the examined conditions, with the left area 4p playing an important role in speech network organization. These sensorimotor core hubs exhibited features of flexible hubs based on their participation in several functional domains across different networks and ability to adaptively switch long-range functional connectivity depending on task content, resulting in a distinct community structure of each examined network. Specifically, compared to other tasks, speech production was characterized by the formation of six distinct neural communities with specialized recruitment of the prefrontal cortex, insula, putamen, and thalamus, which collectively forged the formation of the functional speech connectome. In addition, the observed capacity of the primary sensorimotor cortex to exhibit operational heterogeneity challenged the established concept of unimodality of this region.

Background Spasmodic dysphonia (SD), or laryngeal dystonia, is a task-specific isolated focal dystonia of unknown causes and pathophysiology. Although functional and structural abnormalities have been described in this disorder, the influence of its different clinical phenotypes and genotypes remains scant, making it difficult to explain SD pathophysiology and to identify potential biomarkers. Methods We used a combination of independent component analysis and linear discriminant analysis of resting-state functional MRI data to investigate brain organization in different SD phenotypes (abductor vs. adductor type) and putative genotypes (familial vs. sporadic cases) and to characterize neural markers for genotype/phenotype categorization. Results We found abnormal functional connectivity within sensorimotor and frontoparietal networks in SD patients compared to healthy individuals as well as phenotype- and genotype-distinct alterations of these networks, involving primary somatosensory, premotor and parietal cortices. The linear discriminant analysis achieved 71% accuracy classifying SD and healthy individuals using connectivity measures in the left inferior parietal and sensorimotor cortex. When categorizing between different forms of SD, the combination of measures from left inferior parietal, premotor and right sensorimotor cortices achieved 81% discriminatory power between familial and sporadic SD cases, whereas the combination of measures from the right superior parietal, primary somatosensory and premotor cortices led to 71% accuracy in the classification of adductor and abductor SD forms. Conclusions Our findings present the first effort to identify and categorize isolated focal dystonia based on its brain functional connectivity profile, which may have a potential impact on the future development of biomarkers for this rare disorder.

Background Task‐specific focal dystonias selectively affect movements during the production of highly learned and complex motor behaviors. Manifestation of some task‐specific focal dystonias, such as musician's dystonia, has been associated with excessive practice and overuse, whereas the etiology of others remains largely unknown. Objectives In this study, we aimed to examine the neural correlates of task‐specific dystonias in order to determine their disorder‐specific pathophysiological traits. Methods Using multimodal neuroimaging analyses of resting‐state functional connectivity, voxel‐based morphometry and tract‐based spatial statistics, we examined functional and structural abnormalities that are both common to and distinct between four different forms of task‐specific focal dystonias. Results Compared to the normal state, all task‐specific focal dystonias were characterized by abnormal recruitment of parietal and premotor cortices that are necessary for both modality‐specific and heteromodal control of the sensorimotor network. Contrasting the laryngeal and hand forms of focal dystonia revealed distinct patterns of sensorimotor integration and planning, again involving parietal cortex in addition to inferior frontal gyrus and anterior insula. On the other hand, musician's dystonia compared to nonmusician's dystonia was shaped by alterations in primary and secondary sensorimotor cortices together with middle frontal gyrus, pointing to impairments of sensorimotor guidance and executive control. Conclusion Collectively, this study outlines a specialized footprint of functional and structural alterations in different forms of task‐specific focal dystonia, all of which also share a common pathophysiological framework involving premotor‐parietal aberrations. © 2019 International Parkinson and Movement Disorder Society

Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network.