Evidence map›Paper›PMID 27757062›Full record

ReviewDialogues in clinical neuroscience2016

Individual variation in functional brain connectivity: implications for personalized approaches to psychiatric disease.

Emily S Finn, R Todd Constable

Abstract readReview
In one paragraph

Review in Dialogues in clinical neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
–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

53 citing papers in PubMed.

  1. Article
  2. Article
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  4. Neural manifold connectomics reveals multiregime functional connectivity.bioRxiv : the preprint server for biology · 2026
    Article
  5. Article
  6. Article
  7. Article
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  12. The Beholder's Share: Bridging art and neuroscience to study individual differences in subjective experience.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  13. Article
  14. Comparing and scaling fMRI features for brain-behavior prediction.Imaging neuroscience (Cambridge, Mass.) · 2025
    Article
  15. Article
  16. Article
  17. Brain-Cognition Fingerprinting via Graph-GCCA with Contrastive Learning.Machine learning in clinical neuroimaging : 7th international workshop, MLCN 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, proceedings. MLCN (Workshop) (7th : 2024 : Marrakesh, Morocco) · 2025
    Article
  18. Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
    Review
  19. Consecutive-Contrastive Spherical U-Net: Enhancing Reliability of Individualized Functional Brain Parcellation for Short-Duration fMRI Scans.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2024
    Article
  20. Article
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

2 authors.

Emily S FinnInterdepartmental Neuroscience Program, Yale University, New Haven, Connecticut, USA.
R Todd ConstableInterdepartmental Neuroscience Program, Yale University, New Haven, Connecticut, USA; Department of Radiology and Bioimaging Sciences, Yale School of Medicine, New Haven, Connecticut, USA; Department of Neurosurgery, Yale School of Medicine, New Haven Connecticut, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Functional brain connectivity measured with functional magnetic resonance imaging (fMRI) is a popular technique for investigating neural organization in both healthy subjects and patients with mental illness. Despite a rapidly growing body of literature, however, functional connectivity research has yet to deliver biomarkers that can aid psychiatric diagnosis or prognosis at the single-subject level. One impediment to developing such practical tools has been uncertainty regarding the ratio of intra- to interindividual variability in functional connectivity; in other words, how much variance is state- versus trait-related. Here, we review recent evidence that functional connectivity profiles are both reliable within subjects and unique across subjects, and that features of these profiles relate to behavioral phenotypes. Together, these results suggest the potential to discover reliable correlates of present and future illness and/or response to treatment in the strength of an individual's functional brain connections. Ultimately, this work could help develop personalized approaches to psychiatric illness.

Indexed as

ConnectomeBehaviorHumansMental DisordersPrecision MedicinePrognosisbiomarkerfMRIfunctional connectivityindividual variationprediction

Identifiers

PMID27757062
PMCPMC5067145

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.