Evidence map›Paper›PMID 35802477›Full record

ArticleCerebral cortex (New York, N.Y. : 1991)2023

Masked features of task states found in individual brain networks.

Alexis Porter, Ashley Nielsen, Megan Dorn, Ally Dworetsky, Donnisa Edmonds, Caterina Gratton

Abstract read
In one paragraph

Article in Cerebral cortex (New York, N.Y. : 1991), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. The promise of precision functional mapping for neuroimaging in psychiatry.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
    Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. 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

6 authors.

Alexis PorterDepartment of Psychology, Northwestern University, 633 Clark St, Evanston, IL 60208, United States.ORCID 0000-0002-6636-1672
Ashley NielsenDepartment of Neurology, Washington University in St. Louis, 1 Brookings Dr, St. Louis, MO 63130, United States.
Megan DornDepartment of Psychology, Northwestern University, 633 Clark St, Evanston, IL 60208, United States.
Ally DworetskyDepartment of Psychology, Northwestern University, 633 Clark St, Evanston, IL 60208, United States.
Donnisa EdmondsDepartment of Psychology, Northwestern University, 633 Clark St, Evanston, IL 60208, United States.
Caterina GrattonDepartment of Psychology, Northwestern University, 633 Clark St, Evanston, IL 60208, United States.

Funding

Research Education Core FP30AG072977 · NIA · NORTHWESTERN UNIVERSITY AT CHICAGO · PI SANDRA WEINTRAUB · 2021 to 2026
$26.3M
Training Program in Neurobiology of Information StorageT32MH067564 · NIMH · NORTHWESTERN UNIVERSITY AT CHICAGO · PI Daniel A Dombeck · 2003 to 2026
$4.7M
Sources and Functional Consequences of Individual Differences in Human Functional Brain Networks Related to Controlled BehaviorR01MH118370 · NIMH · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI GRATTON, CATERINA · 2019 to 2023
$3.4M
NIA NIH HHS P30 AG072977NIMH NIH HHS R01 MH118370NIMH NIH HHS T32 MH067564
6 · The paper itself

Abstract

Completing complex tasks requires that we flexibly integrate information across brain areas. While studies have shown how functional networks are altered during different tasks, this work has generally focused on a cross-subject approach, emphasizing features that are common across people. Here we used extended sampling "precision" fMRI data to test the extent to which task states generalize across people or are individually specific. We trained classifiers to decode state using functional network data in single-person datasets across 5 diverse task states. Classifiers were then tested on either independent data from the same person or new individuals. Individualized classifiers were able to generalize to new participants. However, classification performance was significantly higher within a person, a pattern consistent across model types, people, tasks, feature subsets, and even for decoding very similar task conditions. Notably, these findings also replicated in a new independent dataset. These results suggest that individual-focused approaches can uncover robust features of brain states, including features obscured in cross-subject analyses. Individual-focused approaches have the potential to deepen our understanding of brain interactions during complex cognition.

Indexed as

BrainBrain MappingCognitionHumansMagnetic Resonance ImagingRestBOLD fMRIfunctional connectivityindividual differencesmachine learningtask states

Identifiers

PMID35802477
PMCPMC10016040

What OpenQuestion holds

Textmetadata
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.