Evidence map›Paper›PMID 37201396›Full record

ReviewAddictive behaviors2023

Longing to act: Bayesian inference as a framework for craving in behavioral addiction.

Kaustubh R Kulkarni, Madeline O'Brien, Xiaosi Gu

Abstract readReview
In one paragraph

Review in Addictive behaviors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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.

Kaustubh R KulkarniDepartment of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Madeline O'BrienDepartment of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Xiaosi GuDepartment of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States. Electronic address: xiaosi.gu@mssm.edu.

Funding

MOUNT SINAI MEDICAL SCIENTIST TRAINING PROGRAMT32GM007280 · NIGMS · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI BARON, MARGARET H · 1985 to 2021
$22.8M
Computational and Neural Modeling of Cue Reactivity in AddictionR01DA043695 · NIDA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI GU, XIAOSI · 2018 to 2022
$2.9M
Neurocomputational Mechanisms for Addiction Heterogeneity, Impulsivity and PerseveranceR21DA049243 · NIDA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI GU, XIAOSI · 2019 to 2020
$466k
NIDA NIH HHS R01 DA043695NIDA NIH HHS R21 DA049243NIGMS NIH HHS T32 GM007280
6 · The paper itself

Abstract

Traditionally, craving is considered a defining feature of drug addiction. Accumulating evidence suggests that craving can also exist in behavioral addictions (e.g., gambling disorder) without drug-induced effects. However, the degree to which mechanisms of craving overlap between classic substance use disorders and behavioral addictions remains unclear. There is, therefore, an urgent need to develop an overarching theory of craving that conceptually integrates findings across behavioral and drug addictions. In this review, we will first synthesize existing theories and empirical findings related to craving in both drug-dependent and -independent addictive disorders. Building on the Bayesian brain hypothesis and previous work on interoceptive inference, we will then propose a computational theory for craving in behavioral addiction, where the target of craving is execution of an action (e.g., gambling) rather than a drug. Specifically, we conceptualize craving in behavioral addiction as a subjective belief about physiological states of the body associated with action completion and is updated based on both a prior belief ("I need to act to feel good") and sensory evidence ("I cannot act"). We conclude by briefly discussing the therapeutic implications of this framework. In summary, this unified Bayesian computational framework for craving generalizes across addictive disorders, provides explanatory power for ostensibly conflicting empirical findings, and generates strong hypotheses for future empirical studies. The disambiguation of the computational components underlying domain-general craving using this framework will lead to a deeper understanding of, and effective treatment targets for, behavioral and drug addictions.

Indexed as

Behavior, AddictiveGamblingSubstance-Related DisordersBayes TheoremCravingHumansBayesian inferenceBehavioral addictionCravingDopamineInteroceptionPrior beliefsRewardSubstance use disorder

Identifiers

PMID37201396
PMCPMC10330403

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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.