Evidence map›Paper›PMID 35142289›Full record

ArticleeLife2022

A neural network model of when to retrieve and encode episodic memories.

Qihong Lu, Uri Hasson, Kenneth A Norman

Abstract read
In one paragraph

Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Learning to select computations in recurrent neural circuits.bioRxiv : the preprint server for biology · 2026
    Article
  5. The active construction of past episodes.Translational neuroscience · 2026
    Article
  6. Article
  7. Stability through plasticity: Finding robust memories through representational drift.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  8. Article
  9. Hippocampal mismatch signals are based on episodic memories and not schematic knowledge.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  10. Article
  11. Event Segmentation Interventions Improve Memory for Naturalistic Events.Current directions in psychological science · 2025
    Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. The Role of Event Number and Duration in Time-Compressed Memory Replay.Open mind : discoveries in cognitive science · 2025
    Article
  19. Review
  20. Schema-driven prediction effects on episodic memory across the lifespan.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    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

3 authors.

Qihong LuDepartment of Psychology, Princeton University, Princeton, United States.ORCID 0000-0002-0730-5240
Uri HassonDepartment of Psychology, Princeton University, Princeton, United States.
Kenneth A NormanDepartment of Psychology, Princeton University, Princeton, United States.ORCID 0000-0002-5887-9682

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent human behavioral and neuroimaging results suggest that people are selective in when they encode and retrieve episodic memories. To explain these findings, we trained a memory-augmented neural network to use its episodic memory to support prediction of upcoming states in an environment where past situations sometimes reoccur. We found that the network learned to retrieve selectively as a function of several factors, including its uncertainty about the upcoming state. Additionally, we found that selectively encoding episodic memories at the end of an event (but not mid-event) led to better subsequent prediction performance. In all of these cases, the benefits of selective retrieval and encoding can be explained in terms of reducing the risk of retrieving irrelevant memories. Overall, these modeling results provide a resource-rational account of why episodic retrieval and encoding should be selective and lead to several testable predictions.

Indexed as

Memory, EpisodicHumansMental RecallNeural Networks, ComputerNeuroimagingepisodic memoryevent cognitionneural networkneurosciencenone

Identifiers

PMID35142289
PMCPMC9000961

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.