Paper Info
Title
Clinical applications of the functional connectome.
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.
Year
DOI
Venue
2013
10.1016/j.neuroimage.2013.04.083
NeuroImage
Keywords
Field
DocType
Validity,Reliability,Sensitivity,Specificity,Functional connectome,Predictive modeling
Data science,Neuroscience,Connectomics,Connectome,Resting state fMRI,Cognitive psychology,Psychology,Biomarker (medicine),Open science,Big data,Evidence-based medicine,Research Domain Criteria
Journal
Volume
ISSN
Citations 
80
1053-8119
39
PageRank 
References 
Authors
1.36
52
5
Name
Order
Citations
PageRank
F Xavier Castellanos183444.64
Adriana Di Martino243318.80
R. Cameron Craddock343419.21
Ashesh D. Mehta4685.31
Michael P Milham588448.19