Parcellating cortical functional networks in individuals
Open accessAbstract
The capacity to identify the unique functional architecture of an individual's brain is a crucial step toward personalized medicine and understanding the neural basis of variation in human cognition and behavior. Here we developed a cortical parcellation approach to accurately map functional organization at the individual level using resting-state functional magnetic resonance imaging (fMRI). A population-based functional atlas and a map of inter-individual variability were employed to guide the iterative search for functional networks in individual subjects. Functional networks mapped by this approach were highly reproducible within subjects and effectively captured the variability across subjects, including individual differences in brain lateralization. The algorithm performed well across different subject populations and data types, including task fMRI data. The approach was then validated by invasive cortical stimulation mapping in surgical patients, suggesting potential for use in clinical applications.
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It has become possible to construct a resting-state fMRI-based connectome map with high test-retest reliability in an individual subject.
“In recent years, it has become possible to construct a resting-state functional magnetic resonance imaging (rsfMRI)-based connectome map with high test–retest reliability in an individual subject (36, 37).”
Precision brain-mapping has shown individual differences in the organization of functional networks across the cerebral cortex and in subcortical structures such as the amygdala.
“Precision brain-mapping, which involves the collection of several hours of imaging data from individual patients, has shown individual differences in the organization of functional networks across the cerebral cortex,104–107 as well as in subcortical structures such as the amygdala.108”
From Precision clinical trials: a framework for getting to precision medicine for neurobehavioural disorders (2021) · cites this paper as [105]
Studies with long scan times have revealed that both task-based and resting-state brain activity measures can be obtained with high reliability and precision, allowing researchers to focus on individuals rather than groups.
“Studies with these long scan times have revealed that both task-based and resting-state brain activity measures can be obtained with high reliability and precision, allowing researchers to focus on individuals rather than on groups.”
From Precision clinical trials: a framework for getting to precision medicine for neurobehavioural disorders (2021) · cites this paper as [105]
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- Authors
- Wang, D., Buckner, R. L., Fox, M. D., Holt, D. J., Holmes, A. J., Stoecklein, S., Langs, G., Pan, R., Qian, T., Li, K., Baker, J. T., Stufflebeam, S. M., Wang, K., Wang, X., Hong, B., & Liu, H.
- Affiliations
- Harvard University (US)
- Beth Israel Deaconess Medical Center (US)
- Massachusetts Institute of Technology (US)
- Capital Medical University (CN)
- First Affiliated Hospital of Anhui Medical University (CN)
- Beijing Institute for Brain Disorders (CN)
- Tsinghua University (CN)
- Corresponding author
- Hong, Bo
- Liu, Hesheng
- ORCID
- Venue
- Nature Neuroscience
- Published
- 2015-11-09
- Volume
- 18
- Issue
- 12
- Pages
- 1853-1860
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC4661084
- OpenAlex
- W2212967118
- Cited by
- 527
- References
- 67
- Citations by year
- 2026: 42 · 2025: 47 · 2024: 54 · 2023: 48 · 2022: 52 · 2021: 65 · 2020: 44 · 2019: 44 · 2018: 46 · 2017: 51 · 2016: 33 · 2015: 1
- FWCI
- 26.24
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Funders
- National Institutes of Health (5u54mh091657-05, 5k23mh104515-05)
- National Institute of Mental Health (1U54 MH091657, U54-MH091657, K23-MH104515, K01MH099232, P50MH106435)
- National Institute of Neurological Disorders and Stroke (K23NS083741, K25NS069805, R01NS091604, R01NS069696)
- National Institute of Biomedical Imaging and Bioengineering (P41EB015902)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD067312)
- 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 networks, interindividual variability, hemispheric lateralization, personalized medicine, task-based fMRI, reproducibility
- MeSH terms
- Adolescent, Adult, Brain Mapping, Cerebral Cortex, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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