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Data-driven fMRI data analysis based on parcellation.

Summary: Data-driven fMRI data analysis based on
Yongnan Ji
Thesis submitted to The University of Nottingham
for the degree of Doctor of Philosophy
School of Computer Sciences
University of Nottingham
Oct 2010
Functional Magnetic Resonance Imaging (fMRI) is one of the most popular neu-
roimaging methods for investigating the activity of the human brain during cogni-
tive tasks. As with many other neuroimaging tools, the group analysis of fMRI data
often requires a transformation of the individual datasets to a common stereotaxic
space, where the different brains have a similar global shape and size. However, the
local inaccuracy of this procedure gives rise to a series of issues including a lack of
true anatomical correspondence and a loss of subject specific activations.
Inter-subject parcellation of fMRI data has been proposed as a means to alleviate
these problems. Within this frame, the inter-subject correspondence is achieved by
isolating homologous functional parcels across individuals, rather than by match-


Source: Aickelin, Uwe - School of Computer Science, University of Nottingham


Collections: Computer Technologies and Information Sciences