Dystonia related disease pattern using ICA and resting state fMRI
An Vo 1 , Wataru Sako 1 , David Eidelberg 1 , and Aziz M Uluğ 1
Center for Neurosciences, Feinstein
Institute For Medical Research, Manhasset, NY, United
The purpose of this study is using rsfMRI to determine
affected brain networks in dystonia. rsfMRI were
analyzed using spatial group independent component
analysis. Four ICs representing independent
contributions from cerebellar, thalamic and premotor/prefrontal
regions achieved maximum between-group separation.
Dystonia pattern was obtained by a linear combination of
these four components using estimated parameters of
nominal logistic model. Subject scores representing the
mean expression of the dystonia-related pattern were
abnormally elevated in the DYT1 and DYT6 patients and
the sporadic patients as well. The topography of the
rsfMRI-based network closely resembled that previously
described in the resting state with FDG PET.
This abstract and the presentation materials are available to members only;
a login is required.