Longing to act: Bayesian inference as a framework for craving in behavioral addiction
Open accessAbstract
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.
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Both substance and behavioral addictions share common craving substrates which may lead to similar cognitive impairments.
“both substance and behavioral addictions share common craving substrates which may lead to similar cognitive impairments (Kulkarni et al., 2023).”
From Predictive coding in neuropsychiatric disorders: a systematic transdiagnostic review. (2025) · cites this paper as Kulkarni et al., 2023
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References 66 · Cited by 12
- Authors
- Kulkarni, K. R., O'Brien, M., & Gu, X.
- Affiliations
- Icahn School of Medicine at Mount Sinai (US)
- Corresponding author
- Gu, Xiaosi
- Venue
- Addictive Behaviors
- Publisher
- Elsevier BV
- Published
- 2023-09
- Volume
- 144
- Pages
- 107752
- ISSN
- 0306-4603 (ISSN-L)
- PMC
- PMC10330403
- OpenAlex
- W4376619755
- Cited by
- 12
- References
- 66
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 6 · 2023: 1
- FWCI
- 0.61
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (am, 259 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Addictive Behaviors (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (T32 GM007280)
- National Institute on Drug Abuse (R01DA043695, R21DA049243)
- Topics
- Social Sciences › Psychology › Clinical Psychology › Gambling Behavior and Treatments
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Keywords
- craving, behavioral addiction, gambling addiction, Bayesian inference, Bayesian brain hypothesis, interoceptive inference, drug addiction, substance use disorders
- MeSH terms
- Bayes Theorem, Gambling, Humans, Behavior, Addictive, Substance-Related Disorders, Craving
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