Clinical applications of the functional connectome
Open accessAbstract
Central to the development of clinical applications of functional connectomics for neurology and psychiatry is the discovery and validation of biomarkers. Resting state fMRI (R-fMRI) is emerging as a mainstream approach for imaging-based biomarker identification, detecting variations in the functional connectome that can be attributed to clinical variables (e.g., diagnostic status). Despite growing enthusiasm, many challenges remain. Here, we assess evidence of the readiness of R-fMRI based functional connectomics to lead to clinically meaningful biomarker identification through the lens of the criteria used to evaluate clinical tests (i.e., validity, reliability, sensitivity, specificity, and applicability). We focus on current R-fMRI-based prediction efforts, and survey R-fMRI used for neurosurgical planning. We identify gaps and needs for R-fMRI-based biomarker identification, highlighting the potential of emerging conceptual, analytical and cultural innovations (e.g., the Research Domain Criteria Project (RDoC), open science initiatives, and Big Data) to address them. Additionally, we note the need to expand future efforts beyond identification of biomarkers for disease status alone to include clinical variables related to risk, expected treatment response and prognosis.
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The study of resting-state networks has potential clinical value, providing rich and sensitive markers of disease.
“the study of RSNs has already been shown to have potential clinical value, providing rich and sensitive markers of disease [8]”
From Functional connectomics from resting-state fMRI (2013) · cites this paper as [8]
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Special Surgical Considerations for Functional Brain Mapping
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fcMRI—Mapping functional connectivity or correlating cardiac‐induced noise?
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Flagged first, then by citations
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- Authors
- Castellanos, F. X., Di Martino, A., Craddock, R. C., Mehta, A. D., & Milham, M. P.
- Affiliations
- Nathan Kline Institute for Psychiatric Research (US)
- Feinstein Institute for Medical Research (US)
- Corresponding author
- Castellanos, F. Xavier
- Milham, Michael P.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 80
- Pages
- 527-540
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3809093
- OpenAlex
- W2145642814
- Cited by
- 312
- References
- 212
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 14 · 2023: 15 · 2022: 19 · 2021: 23 · 2020: 28 · 2019: 27 · 2018: 32 · 2017: 22 · 2016: 42 · 2015: 39 · 2014: 26 · 2013: 6 · 2012: 1
- FWCI
- 20.58
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (K23MH087770, R01MH094639, R03MH096321)
- Brain & Behavior Research Foundation
- 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
- functional connectomics, resting-state fMRI, biomarker discovery, clinical validation, neurosurgical planning, Research Domain Criteria, open science, big data, treatment response prediction, prognosis
- MeSH terms
- Animals, Brain, Brain Diseases, Humans, Magnetic Resonance Imaging, Models, Neurological, Nerve Net, Evidence-Based Medicine, Connectome
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.
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