Evidence map›Paper›PMID 26100524›Full record

ArticleLearning & behavior2015

Individual differences in learning predict the return of fear.

Samuel J Gershman, Catherine A Hartley

Abstract read
PubMed Publisher
In one paragraph

Article in Learning & behavior, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Computational perspectives on human fear and anxiety.Neuroscience and biobehavioral reviews · 2023
    Review
  12. Article
  13. Article
  14. Neural Computations of Threat.Trends in cognitive sciences · 2021
    Review
  15. Article
  16. Article
  17. Article
  18. Network architectures supporting learnability.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020
    Article
  19. Article
  20. Learning task-state representations.Nature neuroscience · 2019
    Review
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.

Samuel J GershmanDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA, sjgershm@mit.edu.
Catherine A Hartley

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Using a laboratory analogue of learned fear (Pavlovian fear conditioning), we show that there is substantial heterogeneity across individuals in spontaneous recovery of fear following extinction training. We propose that this heterogeneity might stem from qualitative individual differences in the nature of extinction learning. Whereas some individuals tend to form a new memory during extinction, leaving their fear memory intact, others update the original threat association with new safety information, effectively unlearning the fear memory. We formalize this account in a computational model of fear learning and show that individuals who, according to the model, are more likely to form new extinction memories tend to show greater spontaneous recovery compared to individuals who appear to only update a single memory. This qualitative variation in fear and extinction learning may have important implications for understanding vulnerability and resilience to fear-related psychiatric disorders.

Indexed as

Extinction, PsychologicalFearIndividualityLearningAdolescentAdultConditioning, ClassicalFemaleHumansMaleModels, PsychologicalYoung Adult

Identifiers

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.