Evidence map›Paper›PMID 31381985›Full record

ReviewBehavioural processes2019

Uncovering the 'state': Tracing the hidden state representations that structure learning and decision-making.

Angela J Langdon, Mingyu Song, Yael Niv

Abstract readReview
In one paragraph

Review in Behavioural processes, 2019. 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. Article
  2. Orbitofrontal-Hippocampal State Coding Dynamics during Reversal Learning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. Context-sensitive valuation and learning.Current opinion in behavioral sciences · 2021
    Article
  7. Learning task-state representations.Nature neuroscience · 2019
    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.

Angela J LangdonPrinceton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, 08544, United States. Electronic address: alangdon@princeton.edu.
Mingyu SongPrinceton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, 08544, United States.
Yael NivPrinceton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, 08544, United States. Electronic address: yael@princeton.edu.

Funding

Orbitofrontal cortex as a cognitive map of task statesR01DA042065 · NIDA · PRINCETON UNIVERSITY · PI NIV, YAEL · 2016 to 2020
$1.8M
NIDA NIH HHS R01 DA042065
6 · The paper itself

Abstract

We review the abstract concept of a 'state' - an internal representation posited by reinforcement learning theories to be used by an agent, whether animal, human or artificial, to summarize the features of the external and internal environment that are relevant for future behavior on a particular task. Armed with this summary representation, an agent can make decisions and perform actions to interact effectively with the world. Here, we review recent findings from the neurobiological and behavioral literature to ask: 'what is a state?' with respect to the internal representations that organize learning and decision making across a range of tasks. We find that state representations include information beyond a straightforward summary of the immediate cues in the environment, providing timing or contextual information from the recent or more distant past, which allows these additional factors to influence decision making and other goal-directed behaviors in complex and perhaps unexpected ways.

Indexed as

Decision MakingLearningReinforcement, PsychologyAnimalsCuesHumansPsychological TheoryRewardDecision makingDopamineLearningRewardTiming

Identifiers

PMID31381985
PMCPMC7388561

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.