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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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