Probabilistic classification and gambling in patients with schizophrenia receiving medication: comparison of risperidone, olanzapine, clozapine and typical antipsychotics

Wasserman, James I.; Barry, Rebecca; Bradford, L. DiAnne; Delva, Nicholas J.; Beninger, Richard J.

doi:10.1007/s00213-011-2634-4

Cited by 11 publications

(9 citation statements)

References 48 publications

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“…First, the patients were receiving antipsychotic medications at clinicallydetermined dosages, which could have impacted performance on the PRL task. 47,48 However, we did not find any association between PRL task performance and dose or type of antipsychotic medication dose (expressed in oral-chlorpromazine-equivalent units). Further, reversal learning deficits and reduced reward-related striatal activation have been found in unmedicated and first-episode schizophrenia patients.…”

Section: F Reddy Et Alcontrasting

confidence: 37%

Probabilistic Reversal Learning in Schizophrenia: Stability of Deficits and Potential Causal Mechanisms

Reddy¹,

Waltz

Green³

et al. 2016

SCHBUL

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Although individuals with schizophrenia show impaired feedback-driven learning on probabilistic reversal learning (PRL) tasks, the specific factors that contribute to these deficits remain unknown. Recent work has suggested several potential causes including neurocognitive impairments, clinical symptoms, and specific types of feedback-related errors. To examine this issue, we administered a PRL task to 126 stable schizophrenia outpatients and 72 matched controls, and patients were retested 4 weeks later. The task involved an initial probabilistic discrimination learning phase and subsequent reversal phases in which subjects had to adjust their responses to sudden shifts in the reinforcement contingencies. Patients showed poorer performance than controls for both the initial discrimination and reversal learning phases of the task, and performance overall showed good test-retest reliability among patients. A subgroup analysis of patients (n = 64) and controls (n = 49) with good initial discrimination learning revealed no between-group differences in reversal learning, indicating that the patients who were able to achieve all of the initial probabilistic discriminations were not impaired in reversal learning. Regarding potential contributors to impaired discrimination learning, several factors were associated with poor PRL, including higher levels of neurocognitive impairment, poor learning from both positive and negative feedback, and higher levels of indiscriminate response shifting. The results suggest that poor PRL performance in schizophrenia can be the product of multiple mechanisms.

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Section: F Reddy Et Alcontrasting

confidence: 37%

Probabilistic Reversal Learning in Schizophrenia: Stability of Deficits and Potential Causal Mechanisms

Reddy¹,

Waltz

Green³

et al. 2016

SCHBUL

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“…Impaired decision-making on the IGT has also been observed in people with binge eating disorder and sufferers of alcoholism (Danner et al, 2012;Le Berre et al, 2014). Similarly, patients with schizophrenia also exhibit deficient IGT performance (Kim et al, 2009;Wasserman et al, 2012;Brambilla et al, 2013;Fond et al, 2013), although this finding has not been consistently observed (Turnbull et al, 2006). The IGT deficits of patients with schizophrenia appeared to be driven by altered learning of reward and punishment contingencies associated with different choices as they did show improved performance over the course of learning but at a slower rate (Kim et al, 2009;Brambilla et al, 2013;Fond et al, 2013).…”

Section: Impaired Decision-making Across Neuropsychiatric Populationsmentioning

confidence: 86%

Neural mechanisms regulating different forms of risk-related decision-making: Insights from animal models

Orsini

Moorman

Young

et al. 2015

Neuroscience & Biobehavioral Reviews

128

110

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Over the past 20 years there has been a growing interest in the neural underpinnings of cost/benefit decision-making. Recent studies with animal models have made considerable advances in our understanding of how different prefrontal, striatal, limbic and monoaminergic circuits interact to promote efficient risk/reward decision-making, and how dysfunction in these circuits underlies aberrant decision-making observed in numerous psychiatric disorders. This review will highlight recent findings from studies exploring these questions using a variety of behavioral assays, as well as molecular, pharmacological, neurophysiological, and translational approaches. We begin with a discussion of how neural systems related to decision subcomponents may interact to generate more complex decisions involving risk and uncertainty. This is followed by an overview of interactions between prefrontal-amygdala-dopamine and habenular circuits in regulating choice between certain and uncertain rewards and how different modes of dopamine transmission may contribute to these processes. These data will be compared with results from other studies investigating the contribution of some of these systems to guiding decision-making related to rewards vs. punishment. Lastly, we provide a brief summary of impairments in risk-related decision-making associated with psychiatric disorders, highlighting recent translational studies in laboratory animals.

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“…Recent studies suggest that initial deck preferences are driven towards decks with a high probability (0.9) of reward (bad deck B and good deck D) compared to decks with a lower probability (0.5) of reward (bad deck A and good deck C) [2] , [3] , [4] . Thus, advantageous decision-making relies on shifting choice away from bad deck B and replacing choices with good decks C and/or D [5] , [6] .…”

Section: Introductionmentioning

confidence: 99%

“…The major questions addressed were: 1) are deck choices initially driven toward decks with high reward frequency, 2) how do individual deck choices shift as learning occurs, and 3) does intervening sleep between sessions enhance performance? Given previous work, we hypothesized that there would be an initial preference for deck B and D [2] , [3] , [4] and that learning would reflect a decrease in choices from bad deck B and increase in choices from good decks C and/or D [5] , [6] . We expected that those who engaged in post-learning sleep would show greater overall improvement than those in the post-learning wake condition.…”

Section: Introductionmentioning

confidence: 99%

Post Learning Sleep Improves Cognitive-Emotional Decision-Making: Evidence for a ‘Deck B Sleep Effect’ in the Iowa Gambling Task

2014

Self Cite

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The Iowa Gambling Task (IGT) is widely used to assess real life decision-making impairment in a wide variety of clinical populations. Our study evaluated how IGT learning occurs across two sessions, and whether a period of intervening sleep between sessions can enhance learning. Furthermore, we investigate whether pre-sleep learning is necessary for this improvement. A 200-trial version of the IGT was administered at two sessions separated by wake, sleep or sleep and wake (time-of-day control). Participants were categorized as learners and non-learners based on initial performance in session one. In session one, participants initially preferred the high-frequency reward decks B and D, however, a subset of learners decreased choice from negative expected value ‘bad’ deck B and increased choices towards with a positive expected value ‘good’ decks (decks C and D). The learners who had a period of sleep (sleep and sleep/wake control conditions) between sessions showed significantly larger reduction in choices from deck B and increase in choices from good decks compared to learners that had intervening wake. Our results are the first to show that post-learning sleep can improve performance on a complex decision-making task such as the IGT. These results provide new insights into IGT learning and have important implications for understanding the neural mechanisms of “sleeping on” a decision.

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Probabilistic classification and gambling in patients with schizophrenia receiving medication: comparison of risperidone, olanzapine, clozapine and typical antipsychotics

Abstract: Results generally supported the hypothesis that patients treated with risperidone perform more like those treated with typical antipsychotics than those treated with other atypical antipsychotics.

Cited by 11 publications

References 48 publications

Probabilistic Reversal Learning in Schizophrenia: Stability of Deficits and Potential Causal Mechanisms

Probabilistic Reversal Learning in Schizophrenia: Stability of Deficits and Potential Causal Mechanisms

Neural mechanisms regulating different forms of risk-related decision-making: Insights from animal models

Post Learning Sleep Improves Cognitive-Emotional Decision-Making: Evidence for a ‘Deck B Sleep Effect’ in the Iowa Gambling Task

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