Defining functional areas in individual human brains using resting functional connectivity MRI
Open accessAbstract
The cerebral cortex is anatomically organized at many physical scales starting at the level of single neurons and extending up to functional systems. Current functional magnetic resonance imaging (fMRI) studies often focus at the level of areas, networks, and systems. Except in restricted domains, (e.g., topographically-organized sensory regions), it is difficult to determine area boundaries in the human brain using fMRI. The ability to delineate functional areas non-invasively would enhance the quality of many experimental analyses allowing more accurate across-subject comparisons of independently identified functional areas. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity (rs-fcMRI), are especially promising as a way to accurately localize differences in patterns of activity across large expanses of cortex. In the current report, we applied a novel set of image analysis tools to explore the utility of rs-fcMRI for defining wide-ranging functional area boundaries. We find that rs-fcMRI patterns show sharp transitions in correlation patterns and that these putative areal boundaries can be reliably detected in individual subjects as well as in group data. Additionally, combining surface-based analysis techniques with image processing algorithms allows automated mapping of putative areal boundaries across large expanses of cortex without the need for prior information about a region's function or topography. Our approach reliably produces maps of bounded regions appropriate in size and number for putative functional areas. These findings will hopefully stimulate further methodological refinements and validations.
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Each cortical area is thought to make a distinct contribution to information processing.
“each area is thought to make a distinct contribution to information processing (Cohen et al., 2008; Felleman and Van Essen, 1991; Fuster, 2002; O’Leary and Nakagawa, 2002; Sur and Rubenstein, 2005).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Cohen et al., 2008
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- Authors
- Cohen, A. L., Fair, D. A., Dosenbach, N. U. F., Miezin, F. M., Dierker, D., Van Essen, D. C., Schlaggar, B. L., & Petersen, S. E.
- Affiliations
- Washington University in St. Louis (US)
- Corresponding author
- Cohen, Alexander L.
- Petersen, Steven E.
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2008-05
- Volume
- 41
- Issue
- 1
- Pages
- 45-57
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2705206
- OpenAlex
- W2137240152
- Cited by
- 582
- References
- 76
- Citations by year
- 2026: 9 · 2025: 22 · 2024: 20 · 2023: 46 · 2022: 22 · 2021: 27 · 2020: 23 · 2019: 32 · 2018: 32 · 2017: 42 · 2016: 52 · 2015: 47 · 2014: 44 · 2013: 44 · 2012: 39
- FWCI
- 14.00
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Neurological Disorders and Stroke (R01NS046424, F30NS062489, NS46424, NS 41255, NS-32979, R01NS032979, R21NS041255, R21NS061144)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- resting-state functional connectivity, cortical organization, surface-based analysis
- MeSH terms
- Algorithms, Brain, Brain Mapping, Cerebral Cortex, Data Interpretation, Statistical, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Neural Pathways, Oxygen, Reproducibility of Results
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