Evidence map›Paper›PMID 23631991›Full record

ArticleNeuroImage2013

Clinical applications of the functional connectome.

F Xavier Castellanos, Adriana Di Martino, R Cameron Craddock, Ashesh D Mehta, Michael P Milham

Abstract read
In one paragraph

Article in NeuroImage, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 151 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
151citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

151 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Trial
  6. Neural manifold connectomics reveals multiregime functional connectivity.bioRxiv : the preprint server for biology · 2026
    Article
  7. Review
  8. Article
  9. A complex network perspective on brain disease.Biological reviews of the Cambridge Philosophical Society · 2026
    Review
  10. Quantifying the compressibility of the human brain.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
    Review
  17. Article
  18. Review
  19. Article
  20. Article

91 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

F Xavier CastellanosPhyllis Green and Randolph Cowen Institute for Pediatric Neuroscience, New York University Child Study Center, New York, NY 10016, USA. Francisco.Castellanos@nyumc.org
Adriana Di Martino
R Cameron Craddock
Ashesh D Mehta
Michael P Milham

Funding

Discovery Science of Human Brain Function Across the LifespanR01MH094639 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI MILHAM, MICHAEL PETER · 2011 to 2014
$2.7M
Translational Developmental Neuroscience of AutismK23MH087770 · NIMH · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI DI MARTINO, ADRIANA · 2010 to 2013
$644k
Enhancement of the 1000 Functional Connectome ProjectR03MH096321 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI BISWAL, BHARAT BHUSAN, MILHAM, MICHAEL PETER · 2012 to 2013
$158k
NIMH NIH HHS K23 MH087770NIMH NIH HHS K23MH087770NIMH NIH HHS R01 MH094639NIMH NIH HHS R01MH094639NIMH NIH HHS R03 MH096321NIMH NIH HHS R03MH096321
6 · The paper itself

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.

Indexed as

Evidence-Based MedicineAnimalsBrainBrain DiseasesConnectomeHumansMagnetic Resonance ImagingModels, NeurologicalNerve NetFunctional connectomePredictive modelingReliabilitySensitivitySpecificityValidity

Identifiers

PMID23631991
PMCPMC3809093

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.