Evidence map›Paper›PMID 39606951›Full record

ArticleeLife2024

Evaluating hippocampal replay without a ground truth.

Masahiro Takigawa, Marta Huelin Gorriz, Margot Tirole, Daniel Bendor

Abstract read
In one paragraph

Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Drift-diffusion dynamics of hippocampal replay.PLoS computational biology · 2026
    Article
  2. Article
  3. 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

4 authors.

Masahiro TakigawaInstitute of Behavioural Neuroscience (IBN), University College London (UCL), London, United Kingdom.ORCID https://orcid.org/0000-0002-0162-9017
Marta Huelin GorrizInstitute of Behavioural Neuroscience (IBN), University College London (UCL), London, United Kingdom.ORCID https://orcid.org/0000-0002-0281-0627
Margot TiroleInstitute of Behavioural Neuroscience (IBN), University College London (UCL), London, United Kingdom.ORCID https://orcid.org/0000-0003-0674-6690
Daniel BendorInstitute of Behavioural Neuroscience (IBN), University College London (UCL), London, United Kingdom.ORCID https://orcid.org/0000-0001-6621-793X

Funding

Biotechnology and Biological Sciences Research Council Research Grant BB/T005475/1Biotechnology and Biological Sciences Research Council Research Grant,BB/T005475/1European Research Council Starter Grant CHIMEEuropean Research Council Starter Grant,CHIMEHuman Frontier Science Program Young Investigator Award RGY0067/2016Human Frontier Science Program Young Investigator Award,RGY0067/2016Medical Research Council Graduate student scholarship MR/N013867/1Medical Research Council Graduate student scholarship,MR/N013867/1
6 · The paper itself

Abstract

During rest and sleep, memory traces replay in the brain. The dialogue between brain regions during replay is thought to stabilize labile memory traces for long-term storage. However, because replay is an internally driven, spontaneous phenomenon, it does not have a ground truth - an external reference that can validate whether a memory has truly been replayed. Instead, replay detection is based on the similarity between the sequential neural activity comprising the replay event and the corresponding template of neural activity generated during active locomotion. If the statistical likelihood of observing such a match by chance is sufficiently low, the candidate replay event is inferred to be replaying that specific memory. However, without the ability to evaluate whether replay detection methods are successfully detecting true events and correctly rejecting non-events, the evaluation and comparison of different replay methods is challenging. To circumvent this problem, we present a new framework for evaluating replay, tested using hippocampal neural recordings from rats exploring two novel linear tracks. Using this two-track paradigm, our framework selects replay events based on their temporal fidelity (sequence-based detection), and evaluates the detection performance using each event's track discriminability, where sequenceless decoding across both tracks is used to quantify whether the track replaying is also the most likely track being reactivated.

Indexed as

HippocampusAnimalsLocomotionMaleMemoryNeuronsRatsSleephippocampusmemoryneural decodingneuroscienceplace cellratreplaysleep

Identifiers

PMID39606951
PMCPMC11666237

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.