Dataset Information

Network localization of cervical dystonia based on causal brain lesions.

ABSTRACT: Cervical dystonia is a neurological disorder characterized by sustained, involuntary movements of the head and neck. Most cases of cervical dystonia are idiopathic, with no obvious cause, yet some cases are acquired, secondary to focal brain lesions. These latter cases are valuable as they establish a causal link between neuroanatomy and resultant symptoms, lending insight into the brain regions causing cervical dystonia and possible treatment targets. However, lesions causing cervical dystonia can occur in multiple different brain locations, leaving localization unclear. Here, we use a technique termed 'lesion network mapping', which uses connectome data from a large cohort of healthy subjects (resting state functional MRI, n = 1000) to test whether lesion locations causing cervical dystonia map to a common brain network. We then test whether this network, derived from brain lesions, is abnormal in patients with idiopathic cervical dystonia (n = 39) versus matched controls (n = 37). A systematic literature search identified 25 cases of lesion-induced cervical dystonia. Lesion locations were heterogeneous, with lesions scattered throughout the cerebellum, brainstem, and basal ganglia. However, these heterogeneous lesion locations were all part of a single functionally connected brain network. Positive connectivity to the cerebellum and negative connectivity to the somatosensory cortex were specific markers for cervical dystonia compared to lesions causing other neurological symptoms. Connectivity with these two regions defined a single brain network that encompassed the heterogeneous lesion locations causing cervical dystonia. These cerebellar and somatosensory regions also showed abnormal connectivity in patients with idiopathic cervical dystonia. Finally, the most effective deep brain stimulation sites for treating dystonia were connected to these same cerebellar and somatosensory regions identified using lesion network mapping. These results lend insight into the causal neuroanatomical substrate of cervical dystonia, demonstrate convergence across idiopathic and acquired dystonia, and identify a network target for dystonia treatment.

SUBMITTER: Corp DT

PROVIDER: S-EPMC6536848 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Network localization of cervical dystonia based on causal brain lesions.

Corp Daniel T DT Joutsa Juho J Darby R Ryan RR Delnooz Cathérine C S CCS van de Warrenburg Bart P C BPC Cooke Danielle D Prudente Cecília N CN Ren Jianxun J Reich Martin M MM Batla Amit A Bhatia Kailash P KP Jinnah Hyder A HA Liu Hesheng H Fox Michael D MD

Brain : a journal of neurology 20190601 6

Cervical dystonia is a neurological disorder characterized by sustained, involuntary movements of the head and neck. Most cases of cervical dystonia are idiopathic, with no obvious cause, yet some cases are acquired, secondary to focal brain lesions. These latter cases are valuable as they establish a causal link between neuroanatomy and resultant symptoms, lending insight into the brain regions causing cervical dystonia and possible treatment targets. However, lesions causing cervical dystonia ...[more]

PMID: 31099831

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Project description:A traditional and widely used approach for linking neurological symptoms to specific brain regions involves identifying overlap in lesion location across patients with similar symptoms, termed lesion mapping. This approach is powerful and broadly applicable, but has limitations when symptoms do not localize to a single region or stem from dysfunction in regions connected to the lesion site rather than the site itself. A newer approach sensitive to such network effects involves functional neuroimaging of patients, but this requires specialized brain scans beyond routine clinical data, making it less versatile and difficult to apply when symptoms are rare or transient. In this article we show that the traditional approach to lesion mapping can be expanded to incorporate network effects into symptom localization without the need for specialized neuroimaging of patients. Our approach involves three steps: (i) transferring the three-dimensional volume of a brain lesion onto a reference brain; (ii) assessing the intrinsic functional connectivity of the lesion volume with the rest of the brain using normative connectome data; and (iii) overlapping lesion-associated networks to identify regions common to a clinical syndrome. We first tested our approach in peduncular hallucinosis, a syndrome of visual hallucinations following subcortical lesions long hypothesized to be due to network effects on extrastriate visual cortex. While the lesions themselves were heterogeneously distributed with little overlap in lesion location, 22 of 23 lesions were negatively correlated with extrastriate visual cortex. This network overlap was specific compared to other subcortical lesions (P < 10(-5)) and relative to other cortical regions (P < 0.01). Next, we tested for generalizability of our technique by applying it to three additional lesion syndromes: central post-stroke pain, auditory hallucinosis, and subcortical aphasia. In each syndrome, heterogeneous lesions that themselves had little overlap showed significant network overlap in cortical areas previously implicated in symptom expression (P < 10(-4)). These results suggest that (i) heterogeneous lesions producing similar symptoms share functional connectivity to specific brain regions involved in symptom expression; and (ii) publically available human connectome data can be used to incorporate these network effects into traditional lesion mapping approaches. Because the current technique requires no specialized imaging of patients it may prove a versatile and broadly applicable approach for localizing neurological symptoms in the setting of brain lesions.

Project description:Background:Focal dystonias are severe and disabling movement disorders of a still unclear origin. The structural brain networks associated with focal dystonia have not been well characterized. Here, we investigated structural brain network fingerprints in patients with blepharospasm (BSP) compared with those with hemifacial spasm (HFS), and healthy controls (HC). The patients were also examined following treatment with botulinum neurotoxin (BoNT). Methods:This study included matched groups of 13 BSP patients, 13 HFS patients, and 13 HC. We measured patients using structural-magnetic resonance imaging (MRI) at baseline and after one month BoNT treatment, at time points of maximal and minimal clinical symptom representation, and HC at baseline. Group regional cross-correlation matrices calculated based on grey matter volume were included in graph-based network analysis. We used these to quantify global network measures of segregation and integration, and also looked at local connectivity properties of different brain regions. Results:The networks in patients with BSP were more segregated than in patients with HFS and HC (p?<?0.001). BSP patients had increased connectivity in frontal and temporal cortices, including sensorimotor cortex, and reduced connectivity in the cerebellum, relative to both HFS patients and HC (p?<?0.05). Compared with HC, HFS patients showed increased connectivity in temporal and parietal cortices and a decreased connectivity in the frontal cortex (p?<?0.05). In BSP patients, the connectivity of the frontal cortex diminished after BoNT treatment (p?<?0.05). In contrast, HFS patients showed increased connectivity in the temporal cortex and reduced connectivity in cerebellum after BoNT treatment (p?<?0.05). Conclusions:Our results show that BSP patients display alterations in both segregation and integration in the brain at the network level. The regional differences identified in the sensorimotor cortex and cerebellum of these patients may play a role in the pathophysiology of focal dystonia. Moreover, symptomatic reduction of hyperkinesia by BoNT treatment was associated with different brain network fingerprints in both BSP and HFS patients.

Dataset Information

Network localization of cervical dystonia based on causal brain lesions.

Publications

Network localization of cervical dystonia based on causal brain lesions.

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