Abstract #3968
Hierarchical parcellation using discrete Morse theory of whole-brain high-resolution resting-state 7T fMRI data
Afonso Dias 1 , Marta Bianciardi 2 , Sandro Nunes 1 , Rodolfo Abreu 1 , Juliana Rodrigues 1 , L. Miguel Silveira 3 , Lawrence L. Wald 2 , and Patricia Figueiredo 1
1
Institute for Systems and Robotics and
Department of Bioengineering, Instituto Superior
Tcnico, Universidade de Lisboa, Lisbon, Lisbon,
Portugal,
2
Department
of Radiology, A.A. Martinos Center for Biomedical
Imaging, MGH and Harvard Medical School, Boston, MA,
United States,
3
INESC-ID
and Department of Electrical and Computer Engineering,
Instituto Superior Tcnico, Universidade de Lisboa,
Lisbon, Lisbon, Portugal
Parcellation of the brain into functionally meaningful
regions is a crucial step in studies of brain
connectivity using complex network analysis methods
based on resting-state fMRI (rs-fMRI). With the recent
development of fast acquisition sequences at
ultra-high-field (7T), high-spatial-resolution rs-fMRI
can now be collected from the whole-brain with
sufficient temporal resolution to capture the slow
haemodynamic fluctuations underlying functional brain
connectivity. We present a modification based on
discrete Morse theory of a previously proposed method of
hierarchical brain parcellation with rs-fMRI. We show
that the method is able to produce parcellations at high
levels of detail, with good intra-subject
reproducibility.
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