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Probabilistic reward- and punishment-based learning in opioid addiction: Experimental and computational data.
Myers, Catherine E; Sheynin, Jony; Balsdon, Tarryn; Luzardo, Andre; Beck, Kevin D; Hogarth, Lee; Haber, Paul; Moustafa, Ahmed A.
Afiliación
  • Myers CE; Department of Veterans Affairs, New Jersey Health Care System, East Orange, NJ, USA; Department of Pharmacology, Physiology & Neuroscience, New Jersey Medical School, Rutgers, The State University of New Jersey, Newark, NJ, USA. Electronic address: Catherine.Myers2@va.gov.
  • Sheynin J; Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI, USA; Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
  • Balsdon T; School of Social Sciences and Psychology, University of Western Sydney, Sydney, NSW, Australia.
  • Luzardo A; School of Mathematics, Computing Sciences & Engineering at City University London, UK.
  • Beck KD; Department of Veterans Affairs, New Jersey Health Care System, East Orange, NJ, USA; Department of Pharmacology, Physiology & Neuroscience, New Jersey Medical School, Rutgers, The State University of New Jersey, Newark, NJ, USA.
  • Hogarth L; School of Psychology, University of New South Wales, Sydney, NSW, Australia; School of Psychology, University of Exeter, Exeter, UK.
  • Haber P; Drug Health Services, Addiction Medicine, Central Clinical School, Royal Prince Alfred Hospital, The University of Sydney, Sydney, NSW, Australia.
  • Moustafa AA; School of Social Sciences and Psychology, University of Western Sydney, Sydney, NSW, Australia; Marcs Institute for Brain and Behaviour, University of Western Sydney, Sydney, NSW, Australia. Electronic address: a.moustafa@uws.edu.au.
Behav Brain Res ; 296: 240-248, 2016 Jan 01.
Article en En | MEDLINE | ID: mdl-26381438
Addiction is the continuation of a habit in spite of negative consequences. A vast literature gives evidence that this poor decision-making behavior in individuals addicted to drugs also generalizes to laboratory decision making tasks, suggesting that the impairment in decision-making is not limited to decisions about taking drugs. In the current experiment, opioid-addicted individuals and matched controls with no history of illicit drug use were administered a probabilistic classification task that embeds both reward-based and punishment-based learning trials, and a computational model of decision making was applied to understand the mechanisms describing individuals' performance on the task. Although behavioral results showed that opioid-addicted individuals performed as well as controls on both reward- and punishment-based learning, the modeling results suggested subtle differences in how decisions were made between the two groups. Specifically, the opioid-addicted group showed decreased tendency to repeat prior responses, meaning that they were more likely to "chase reward" when expectancies were violated, whereas controls were more likely to stick with a previously-successful response rule, despite occasional expectancy violations. This tendency to chase short-term reward, potentially at the expense of developing rules that maximize reward over the long term, may be a contributing factor to opioid addiction. Further work is indicated to better understand whether this tendency arises as a result of brain changes in the wake of continued opioid use/abuse, or might be a pre-existing factor that may contribute to risk for addiction.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje por Probabilidad / Castigo / Recompensa / Toma de Decisiones / Trastornos Relacionados con Opioides Tipo de estudio: Prognostic_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Behav Brain Res Año: 2016 Tipo del documento: Article Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
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XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje por Probabilidad / Castigo / Recompensa / Toma de Decisiones / Trastornos Relacionados con Opioides Tipo de estudio: Prognostic_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Behav Brain Res Año: 2016 Tipo del documento: Article Pais de publicación: Países Bajos