Clustering probabilistic tractograms using independent component analysis applied to the thalamus.
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.
O'Muircheartaigh
Jonathan
J
Department of Clinical Neuroscience, Institute of Psychiatry, King's College London, London, UK.
Vollmar
Christian
C
Traynor
Catherine
C
Barker
Gareth J
GJ
Kumari
Veena
V
Symms
Mark R
MR
Thompson
Pam
P
Duncan
John S
JS
Koepp
Matthias J
MJ
Richardson
Mark P
MP
D000328:Adult; D001931:Brain Mapping; D016000:Cluster Analysis; D056324:Diffusion Tensor Imaging; D005260:Female; D007839:Functional Laterality / Q000502:physiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D025341:Principal Component Analysis; D011336:Probability; D013133:Spinothalamic Tracts / Q000033:anatomy & histology*; D013788:Thalamus / Q000033:anatomy & histology*; D055815:Young Adult