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Neuroimage. 2013 Oct 15;80:527-40. doi: 10.1016/j.neuroimage.2013.04.083. Epub 2013 Apr 28.

Clinical applications of the functional connectome.

Author information

1
Phyllis Green and Randolph Cowen Institute for Pediatric Neuroscience, New York University Child Study Center, New York, NY 10016, USA. Francisco.Castellanos@nyumc.org

Abstract

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.

KEYWORDS:

Functional connectome; Predictive modeling; Reliability; Sensitivity; Specificity; Validity

PMID:
23631991
PMCID:
PMC3809093
DOI:
10.1016/j.neuroimage.2013.04.083
[Indexed for MEDLINE]
Free PMC Article

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