Evidence map›Paper›PMID 41151586›Full record

ReviewNeuron2025

Between planning and map building: Prioritizing replay when future goals are uncertain.

Yotam Sagiv, Thomas Akam, Ilana B Witten, Nathaniel D Daw

Abstract readReview
In one paragraph

Review in Neuron, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. The hippocampus as a generative model.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026
    Review
  2. Planning in the Brain: It's Not What You Think It Is.Annual review of neuroscience · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Proactive and reactive construction of memory-based preferences.bioRxiv : the preprint server for biology · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Yotam SagivPrinceton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA. Electronic address: ysagiv@princeton.edu.
Thomas AkamDepartment of Experimental Psychology, University of Oxford, Oxford OX1 3EL, UK; Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London W1T 4JG, UK.
Ilana B WittenPrinceton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA.
Nathaniel D DawPrinceton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA; Department of Psychology, Princeton University, Princeton, NJ 08544, USA. Electronic address: ndaw@princeton.edu.

Funding

P5: Mechanistic Multi-Region Brain ModelsU19NS132720 · NINDS · PRINCETON UNIVERSITY · PI Carlos D Brody, Ila R. Fiete · 2023 to 2026
$21.5M
State-dependent Decision-making in Brainwide Neural CircuitsU19NS123716 · NINDS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI PANINSKI, LIAM M · 2021 to 2025
$18.2M
NRSA Training Grant in Quantitative NeuroscienceT32MH065214 · NIMH · PRINCETON UNIVERSITY · PI Nathaniel Douglass Daw, KENNETH A NORMAN · 2002 to 2026
$7.9M
Individual differences through self-reinforcement of suboptimal strategiesDP1MH136573 · NIMH · PRINCETON UNIVERSITY · PI Ilana Witten · 2023 to 2026
$5.7M
Value networks and hippocampal non-local representationsR01MH136875 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JOSHUA D BERKE, Nathaniel Douglass Daw · 2024 to 2026
$2.4M
Differentiating reward seeking and loss avoidance with reference-dependent learning modelsR01MH121093 · NIMH · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI DAW, NATHANIEL DOUGLASS, SHOHAMY, DAPHNA · 2019 to 2022
$2.1M
CRCNS: Theory and Experiments to Elucidate Neural Coding in the Reward CircuitR01DA047869 · NIDA · UNIVERSITY OF WASHINGTON · PI WITTEN, DANIELA, WITTEN, ILANA · 2018 to 2021
$1.0M
CRCNS: Computational Foundations for Externalizing/Internalizing PsychopathologyR01MH135587 · NIMH · PRINCETON UNIVERSITY · PI DAW, NATHANIEL DOUGLASS · 2023 to 2025
$613k
NIDA NIH HHS R01 DA047869NIMH NIH HHS DP1 MH136573NIMH NIH HHS R01 MH121093NIMH NIH HHS R01 MH135587NIMH NIH HHS R01 MH136875NIMH NIH HHS T32 MH065214NINDS NIH HHS U19 NS123716NINDS NIH HHS U19 NS132720Wellcome Trust
6 · The paper itself

Abstract

Despite many empirical results about hippocampal replay, its computational function remains controversial. The "value" hypothesis contends that replay plans routes to current goals, while the "map" hypothesis holds that replay builds an abstract environmental representation, distinct from immediate goals. Data appear to support either view, though the planning hypothesis is particularly challenged by recent observations of replay lagging, rather than leading, animals learning to reach current goals. However, differentiating these ideas is difficult due to a lack of formal specificity, especially about the map hypothesis. We address these gaps by extending a prominent theory of planning to include routes to future as well as current goals: effectively a map. Whether replay prefers current goals, like planning, or others, like maps, then depends on their estimated likelihood of future relevance. This account reconciles both views with one another and with much data, revealing a deep relationship between the seemingly distinct hypotheses.

Indexed as

GoalsHippocampusAnimalsHumansLearningModels, NeurologicalUncertaintygeodesic representationhippocampal replayreinforcement learning

Identifiers

PMID41151586
PMCPMC12633763

What OpenQuestion holds

Textmetadata
LicenceTDM
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.