Cited by 1,463Functional Brain Connectivity StudiesAdvanced Neuroimaging Techniques and ApplicationsAdvanced MRI Techniques and Applications

Generation and evaluation of a cortical area parcellation from resting-state correlations

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Gordon, Evan M., Laumann, Timothy O., Adeyemo, Babatunde, Huckins, Jeremy F., Kelley, William M., Petersen, Steven E.·2016·Cerebral Cortex

Abstract

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.

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Authors
Gordon, E. M., Laumann, T. O., Adeyemo, B., Huckins, J. F., Kelley, W. M., & Petersen, S. E.
Affiliations
  • Dartmouth College (US)
  • Washington University in St. Louis (US)
Corresponding author
Gordon, Evan M.
Venue
Cerebral Cortex
Published
2014-10-14
Volume
26
Issue
1
Pages
288-303
ISSN
  • 1047-3211 (ISSN-L)
  • 1460-2199
OpenAlex
W2107499714
Cited by
1,463
References
81
Citations by year
2026: 107 · 2025: 182 · 2024: 185 · 2023: 151 · 2022: 155 · 2021: 165 · 2020: 141 · 2019: 110 · 2018: 101 · 2017: 76 · 2016: 61 · 2015: 28 · 2013: 1
FWCI
30.86
Type
journal article
Language
en
Open access
Locations
  • Cerebral Cortex (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Simons Foundation (95177)
  • James S. McDonnell Foundation
  • National Institutes of Health (5u54mh091657-05, MH091657)
  • National Institute on Alcohol Abuse and Alcoholism (AA021347, R01AA021347)
  • National Heart, Lung, and Blood Institute (R21HL114092, HL114092)
  • National Institute of Mental Health (F30MH100872, MH091657, MH100872, R01MH059282, MH059282)
  • National Institute on Drug Abuse (R01DA022582, DA022582)
  • National Institute of Neurological Disorders and Stroke (NS061144, R21NS061144)
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (U54HD087011)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Keywords
cortical parcellation, resting-state functional connectivity, human cortex, brain network structure
MeSH terms
Adult, Brain Mapping, Cerebral Cortex, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Neural Pathways, Young Adult

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