Evidence map›Paper›PMID 38079351›Full record

ArticleeLife2023

A neural network model of hippocampal contributions to category learning.

Jelena Sučević, Anna C Schapiro

Abstract read
In one paragraph

Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Distinct Hippocampal Mechanisms Support Concept Formation and Updating.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  3. Article
  4. Article
  5. Sharpened Visual Memory Representations Are Reflected in Inferotemporal Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  6. Distinct contributions of hippocampal pathways in learning regularities and exceptions revealed by functional footprints.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Evidence for shallow cognitive maps in schizophrenia.Cognitive, affective & behavioral neuroscience · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Object Feature Memory Is Distorted by Category Structure.Open mind : discoveries in cognitive science · 2024
    Article
  16. Article
  17. Article
  18. Adult neurogenesis acts as a neural regularizer.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  19. A model of autonomous interactions between hippocampus and neocortex driving sleep-dependent memory consolidation.Proceedings of the National Academy of Sciences of the United States of America · 2022
    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.

Jelena SučevićDepartment of Experimental Psychology, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-5091-5434
Anna C SchapiroDepartment of Psychology, University of Pennsylvania, Philadelphia, United States.ORCID 0000-0001-8086-0331

Funding

Charles E. Kaufman Foundation KA2020-114800University of Oxford St Hugh's College Travel Grant
6 · The paper itself

Abstract

In addition to its critical role in encoding individual episodes, the hippocampus is capable of extracting regularities across experiences. This ability is central to category learning, and a growing literature indicates that the hippocampus indeed makes important contributions to this form of learning. Using a neural network model that mirrors the anatomy of the hippocampus, we investigated the mechanisms by which the hippocampus may support novel category learning. We simulated three category learning paradigms and evaluated the network's ability to categorize and recognize specific exemplars in each. We found that the trisynaptic pathway within the hippocampus-connecting entorhinal cortex to dentate gyrus, CA3, and CA1-was critical for remembering exemplar-specific information, reflecting the rapid binding and pattern separation capabilities of this circuit. The monosynaptic pathway from entorhinal cortex to CA1, in contrast, specialized in detecting the regularities that define category structure across exemplars, supported by the use of distributed representations and a relatively slower learning rate. Together, the simulations provide an account of how the hippocampus and its constituent pathways support novel category learning.

Indexed as

HippocampusLearningEntorhinal CortexMental RecallNeural Networks, ComputerNeural Pathwayscategory learninghippocampusneural network modelneurosciencenone

Identifiers

PMID38079351
PMCPMC10712951

What OpenQuestion holds

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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.