Evidence map›Paper›PMID 26074792›Full record

ArticleFrontiers in behavioral neuroscience2015

A Bayesian context fear learning algorithm/automaton.

Franklin B Krasne, Jesse D Cushman, Michael S Fanselow

Abstract read
In one paragraph

Article in Frontiers in behavioral neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Hippocampal Engrams and Contextual Memory.Advances in neurobiology · 2024
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Engram Size Varies with Learning and Reflects Memory Content and Precision.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021
    Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. The Neurobiology of Fear Generalization.Frontiers in behavioral neuroscience · 2018
    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

3 authors.

Franklin B KrasneDepartment of Psychology, University of California Los Angeles Los Angeles, CA, USA ; Brain Research Institute, University of California Los Angeles Los Angeles, CA, USA.
Jesse D CushmanDepartment of Psychology, University of California Los Angeles Los Angeles, CA, USA ; Brain Research Institute, University of California Los Angeles Los Angeles, CA, USA.
Michael S FanselowDepartment of Psychology, University of California Los Angeles Los Angeles, CA, USA ; Brain Research Institute, University of California Los Angeles Los Angeles, CA, USA ; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles Los Angeles, CA, USA.

Funding

Contextual Fear Differentiation, Sex Differences and AcetylcholineR01MH062122 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI FANSELOW, MICHAEL S · 2001 to 2021
$7.3M
NIMH NIH HHS R01 MH062122
6 · The paper itself

Abstract

Contextual fear conditioning is thought to involve the synaptic plasticity-dependent establishment in hippocampus of representations of to-be-conditioned contexts which can then become associated with USs in the amygdala. A conceptual and computational model of this process is proposed in which contextual attributes are assumed to be sampled serially and randomly during contextual exposures. Given this assumption, moment-to-moment information about such attributes will often be quite different from one exposure to another and, in particular, between exposures during which representations are created, exposures during which conditioning occurs, and during recall sessions. This presents challenges to current conceptual models of hippocampal function. In order to meet these challenges, our model's hippocampus was made to operate in different modes during representation creation and recall, and non-hippocampal machinery was constructed that controlled these hippocampal modes. This machinery uses a comparison between contextual information currently observed and information associated with existing hippocampal representations of familiar contexts to compute the Bayesian Weight of Evidence that the current context is (or is not) a known one, and it uses this value to assess the appropriateness of creation or recall modes. The model predicts a number of known phenomena such as the immediate shock deficit, spurious fear conditioning to contexts that are absent but similar to actually present ones, and modulation of conditioning by pre-familiarization with contexts. It also predicts a number of as yet unknown phenomena.

Indexed as

amygdalaBayesiancomputational neurosciencecontextfear conditioninghippocampusmodel

Identifiers

PMID26074792
PMCPMC4445248

What OpenQuestion holds

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Registered trials

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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.