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Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2019

Characterizing Brain Network Topology in Cervical Dystonia Patients and Unaffected Relatives via Graph Theory.

СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Narasimham Shruti, Sundarajan Vikram, McGovern Eavan, Quinlivan Brendan, Killian Owen, O'Riordan Sean, Hutchinson Michael, Reilly Richard B

Аннотация

Cervical Dystonia (CD) is a neurological movement disorder characterized by intermittent muscle contractions in the head and neck. The pathophysiology and neural networks underpinning this condition are incompletely understood. There is increasing evidence that isolated focal dystonias are due to network-wide functional alterations. An abnormal temporal discrimination threshold (TDT) is believed to be a mediational endophenotype due to its prevalence in unaffected first-degree relatives as well as patients. However the neural correlates linking abnormal TDT and CD remain poorly understood. Probing changes in large-scale network topology via graph theory with resting state fMRI data from relatives and patients may provide further insight into the pathophysiology of CD. In this study, resting state fMRI data were acquired and analyzed from 16 CD patients with abnormal TDT, 32 unaffected first degree relatives (16 with normal TDT and 16 with abnormal TDT) and 16 healthy controls. Graph theory metrics demonstrating network topology were extracted. The results indicate large-scale functional reorganization of networks in relatives (with abnormal TDT) along with a manifestation of topological aberrations similar to patients.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты