1 research outputs found
Connectivity-Based Parcellation of Functional SubROIs in Putamen using A Sparse Spatially Regularized Regression Model
In this paper, we present a novel framework for parcellation of a brain region into
functional subROIs (Sub-Region-of-Interest) based on their connectivity pat-
terns with other brain regions. By utilising previously established neuroanatomy
information, the proposed method aims at nding spatially-continuous, func-
tionally consistent subROIs in a given brain region. The proposed framework
relies on 1) a sparse spatially-regularized fused lasso regression model for en-
couraging spatially and functionally adjacent voxels to share similar regression
coe cients; 2) an iterative merging and adaptive parameter tuning process; 3) a
Graph-Cut optimization algorithm for assigning overlapped voxels into separate
subROIs. Our simulation results demonstrate that the proposed method could
reliably yield spatially continuous and functionally consistent subROIs. We
applied the method to resting-state fMRI data obtained from normal subjects
and explored connectivity to the putamen. Two distinct functional subROIs
could be parcellated out in the putamen region in all subjects. This approach
provides a way to extract functional subROIs that can then be investigated
for alterations in connectivity in diseases of the basal ganglia, for example in Parkinson's disease.Applied Science, Faculty ofMedicine, Faculty ofOther UBCNon UBCElectrical and Computer Engineering, Department ofNeurology, Division ofMedicine, Department ofReviewedFacultyGraduateUnknow