Dataset Information

Reward/Punishment reversal learning in older suicide attempters.

ABSTRACT: Suicide rates are high in old age, and the contribution of cognitive risk factors remains poorly understood. Suicide may be viewed as an outcome of an altered decision process. The authors hypothesized that impairment in reward/punishment-based learning, a component of affective decision making, is associated with attempted suicide in late-life depression. They expected that suicide attempters would discount past reward/punishment history, focusing excessively on the most recent rewards and punishments. The authors further hypothesized that this impairment could be dissociated from executive abilities, such as forward planning.The authors assessed reward/punishment-based learning using the probabilistic reversal learning task in 65 individuals age 60 and older: suicide attempters, suicide ideators, nonsuicidal depressed elderly, and nondepressed comparison subjects. The authors used a reinforcement learning computational model to decompose reward/punishment processing over time. The Stockings of Cambridge test served as a control measure of executive function.Suicide attempters but not suicide ideators showed impaired probabilistic reversal learning compared to both nonsuicidal depressed elderly and nondepressed comparison subjects, after controlling for effects of education, global cognitive function, and substance use. Model-based analyses revealed that suicide attempters discounted previous history to a higher degree relative to comparison subjects, basing their choice largely on reward/punishment received on the last trial. Groups did not differ in their performance on the Stockings of Cambridge test.Older suicide attempters display impaired reward/punishment-based learning. The authors propose a hypothesis that older suicide attempters make overly present-focused decisions, ignoring past experiences. Modification of this "myopia for the past" may have therapeutic potential.

SUBMITTER: Dombrovski AY

PROVIDER: S-EPMC3020386 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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Reward/Punishment reversal learning in older suicide attempters.

Dombrovski Alexandre Y AY Clark Luke L Siegle Greg J GJ Butters Meryl A MA Ichikawa Naho N Sahakian Barbara J BJ Szanto Katalin K

The American journal of psychiatry 20100315 6

<h4>Objective</h4>Suicide rates are high in old age, and the contribution of cognitive risk factors remains poorly understood. Suicide may be viewed as an outcome of an altered decision process. The authors hypothesized that impairment in reward/punishment-based learning, a component of affective decision making, is associated with attempted suicide in late-life depression. They expected that suicide attempters would discount past reward/punishment history, focusing excessively on the most recen ...[more]

PMID: 20231320

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Project description:In the DSM-5, psychiatric diagnoses are made based on self-reported symptoms and clinician-identified signs. Though helpful in choosing potential interventions based on the available regimens, this conceptualization of psychiatric diseases can limit basic science investigation into their underlying causes. The reward prediction error (RPE) hypothesis of dopamine neuron function posits that phasic dopamine signals encode the difference between the rewards a person expects and experiences. The computational framework from which this hypothesis was derived, temporal difference reinforcement learning (TDRL), is largely focused on reward processing rather than punishment learning. Many psychiatric disorders are characterized by aberrant behaviors, expectations, reward processing, and hypothesized dopaminergic signaling, but also characterized by suffering and the inability to change one's behavior despite negative consequences. In this review, we provide an overview of the RPE theory of phasic dopamine neuron activity and review the gains that have been made through the use of computational reinforcement learning theory as a framework for understanding changes in reward processing. The relative dearth of explicit accounts of punishment learning in computational reinforcement learning theory and its application in neuroscience is highlighted as a significant gap in current computational psychiatric research. Four disorders comprise the main focus of this review: two disorders of traditionally hypothesized hyperdopaminergic function, addiction and schizophrenia, followed by two disorders of traditionally hypothesized hypodopaminergic function, depression and post-traumatic stress disorder (PTSD). Insights gained from a reward processing based reinforcement learning framework about underlying dopaminergic mechanisms and the role of punishment learning (when available) are explored in each disorder. Concluding remarks focus on the future directions required to characterize neuropsychiatric disorders with a hypothesized cause of underlying dopaminergic transmission.

Dataset Information

Reward/Punishment reversal learning in older suicide attempters.

Publications

Reward/Punishment reversal learning in older suicide attempters.

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