Title
Clustering probabilistic tractograms using independent component analysis applied to the thalamus.
Abstract
The connectivity information contained in diffusion tensor imaging (DTI) has previously been used to parcellate cortical and subcortical regions based on their connectivity profiles. The aim of the current study is to investigate the utility of a novel approach to connectivity based parcellation of the thalamus using probabilistic tractography and independent component analysis (ICA). We use ICA to identify spatially coherent tractograms as well as their underlying seed regions, in a single step. We compare this to seed-based tractography results and to an established and reliable approach to parcellating the thalamus based on the dominant cortical connection from each thalamic voxel (Behrens et al., 2003a,b). The ICA approach identifies thalamo-cortical pathways that correspond to known anatomical connections, as well as parcellating the underlying thalamus in a spatially similar way to the connectivity based parcellation. We believe that the use of such a multivariate method to interpret the complex datasets created by probabilistic tractography may be better suited than other approaches to parcellating brain regions.
Year
DOI
Venue
2011
10.1016/j.neuroimage.2010.09.054
NeuroImage
Keywords
Field
DocType
principal component analysis,young adult,cluster analysis,diffusion tensor imaging,independent component analysis,brain mapping,probability
Brain mapping,Voxel,Developmental psychology,Diffusion MRI,Psychology,Independent component analysis,Probabilistic logic,Cluster analysis,Tractography,Mixture model
Journal
Volume
Issue
ISSN
54
3
1053-8119
Citations 
PageRank 
References 
15
0.71
9
Authors
10
Name
Order
Citations
PageRank
Jonathan O'Muircheartaigh11309.35
C Vollmar2454.08
Catherine R. Traynor3221.15
Gareth J Barker429936.37
Veena Kumari5597.10
M Symms615617.45
P J Thompson7382.22
J S Duncan836838.49
M Koepp9757.40
Mark P Richardson101047.85