Evidence map›Paper›PMID 27687119›Full record

ReviewAnnual review of psychology2017

Learning, Reward, and Decision Making.

John P O'Doherty, Jeffrey Cockburn, Wolfgang M Pauli

Abstract readReview
In one paragraph

Review in Annual review of psychology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 174 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
174citing papers in PubMed, 3 pooled it
–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

174 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. How childhood adversity affects components of decision making.Neuroscience and biobehavioral reviews · 2025
    Pooled it
  2. Pooled it
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  4. The rise and fall of substance use during treatment: Applying recency and expectancy principles to daily substance use patterns.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2023
    Trial
  5. Trial
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  7. A Mouse-Tracking Paradigm for Value-Driven Attentional Capture.Behavioral sciences (Basel, Switzerland) · 2026
    Article
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  9. Review
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114 more citing papers are in PubMed but not listed here.

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.

John P O'DohertyDivision of Humanities and Social Sciences and Computation and Neural Systems Program, California Institute of Technology, Pasadena, California 91125; email: jdoherty@caltech.edu.
Jeffrey CockburnDivision of Humanities and Social Sciences and Computation and Neural Systems Program, California Institute of Technology, Pasadena, California 91125; email: jdoherty@caltech.edu.
Wolfgang M PauliDivision of Humanities and Social Sciences and Computation and Neural Systems Program, California Institute of Technology, Pasadena, California 91125; email: jdoherty@caltech.edu.

Funding

The Neurobiology of Social Decision-Making: Social Inference and ContextP50MH094258 · NIMH · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI O'DOHERTY, JOHN P · 2012 to 2021
$18.6M
Characterizing habitual and goal-directed behavioral control systems in the humanR01DA033077 · NIDA · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI O'DOHERTY, JOHN P · 2011 to 2014
$1.6M
NIDA NIH HHS R01 DA033077NIMH NIH HHS P50 MH094258
6 · The paper itself

Abstract

In this review, we summarize findings supporting the existence of multiple behavioral strategies for controlling reward-related behavior, including a dichotomy between the goal-directed or model-based system and the habitual or model-free system in the domain of instrumental conditioning and a similar dichotomy in the realm of Pavlovian conditioning. We evaluate evidence from neuroscience supporting the existence of at least partly distinct neuronal substrates contributing to the key computations necessary for the function of these different control systems. We consider the nature of the interactions between these systems and show how these interactions can lead to either adaptive or maladaptive behavioral outcomes. We then review evidence that an additional system guides inference concerning the hidden states of other agents, such as their beliefs, preferences, and intentions, in a social context. We also describe emerging evidence for an arbitration mechanism between model-based and model-free reinforcement learning, placing such a mechanism within the broader context of the hierarchical control of behavior.

Indexed as

RewardBrainConditioning, PsychologicalDecision MakingGoalsHumansLearningNeurosciencesReinforcement, Psychologycognitive mapinstrumentalmodel basedmodel freeoutcome valuationPavlovian

Identifiers

PMID27687119
PMCPMC6192677

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.