Abstract #0310

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

Ying-Chia Lin¹, Tommaso Gili^2,3, 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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­A cortical and sub-cortical parcellation clustering by intrinsic functional connectivity

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