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Abstract #0310

­A cortical and sub-cortical parcellation clustering by intrinsic functional connectivity

Ying-Chia Lin1, Tommaso Gili2,3, Sotirios A. Tsaftaris 1,4, Andrea Gabrielli5, Mariangela Iorio3, Gianfranco Spalletta3, and Guido Caldarelli1

1IMT Institute for Advanced Studies Lucca, Lucca, Italy, 2Enrico Fermi Centre, Rome, Italy, 3IRCCS Fondazione Santa Lucia, Rome, Italy, 4Institute of Digital Communications, School of Engineering, The University of Edinburgh, Edinburgh, United Kingdom, 5ISC-CNR, UOS Sapienza, Dipartimento di Fisica, Universita Sapienza, Rome, Italy

Network analysis of resting-state fMRI (rsfMRI) has been widely utilized to investigate the functional architecture of the whole brain. Here we propose a robust parcellation method that first divides cortical and sub-cortical regions into sub-regions by clustering the rsfMRI data for each subject independently, and then merges those individual parcellations to obtain a global whole brain parcellation. To do so our method relies on majority voting (to merge parcellations of multiple subjects) and enforces spatial constraints within a hierarchical agglomerative clustering framework to define parcels that are spatially homogeneous.

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