Generation and Evaluation of a Cortical Area Parcellation from Resting-State Correlations

• Published in: Cerebral cortex (New York, N.Y. 1991) Vol. 26; no. 1; pp. 288 - 303
• Main Authors: Gordon, Evan M, Laumann, Timothy O, Adeyemo, Babatunde, Huckins, Jeremy F, Kelley, William M, Petersen, Steven E
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 01.01.2016
• Subjects: Adult; Brain Mapping; Cerebral Cortex - physiology; Female; Humans; Image Processing, Computer-Assisted - methods; Magnetic Resonance Imaging - methods; Male; Neural Pathways - physiology; Young Adult; parcellation; resting state; functional connectivity; cortical areas
• ISSN: 1047-3211; 1460-2199
• DOI: 10.1093/cercor/bhu239

The cortical surface is organized into a large number of cortical areas; however, these areas have not been comprehensively mapped in the human. Abrupt transitions in resting-state functional connectivity (RSFC) patterns can noninvasively identify locations of putative borders between cortical areas (RSFC-boundary mapping; Cohen et al. 2008). Here we describe a technique for using RSFC-boundary maps to define parcels that represent putative cortical areas. These parcels had highly homogenous RSFC patterns, indicating that they contained one unique RSFC signal; furthermore, the parcels were much more homogenous than a null model matched for parcel size when tested in two separate datasets. Several alternative parcellation schemes were tested this way, and no other parcellation was as homogenous as or had as large a difference compared with its null model. The boundary map-derived parcellation contained parcels that overlapped with architectonic mapping of areas 17, 2, 3, and 4. These parcels had a network structure similar to the known network structure of the brain, and their connectivity patterns were reliable across individual subjects. These observations suggest that RSFC-boundary map-derived parcels provide information about the location and extent of human cortical areas. A parcellation generated using this method is available at http://www.nil.wustl.edu/labs/petersen/Resources.html.