2015
DOI: 10.1093/schbul/sbv075
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Impaired Activation in Cognitive Control Regions Predicts Reversal Learning in Schizophrenia

Abstract: Reinforcement learning deficits have been associated with schizophrenia (SZ). However, the pathophysiology that gives rise to these abnormalities remains unclear. To address this question, SZ patients (N = 58) and controls (CN; N = 36) completed a probabilistic reversal-learning paradigm during functional magnetic resonance imaging scanning. During the task, participants choose between 2 stimuli. Initially, 1 stimulus was frequently rewarded (80%); the other was infrequently rewarded (20%). The reward continge… Show more

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Cited by 80 publications
(90 citation statements)
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References 60 publications
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“…We present two core findings: First, medicated patients both overestimated their prior higher-level belief about the volatility of the environment and exhibited an increased influence of volatility estimates on lower-level learning of actionoutcome contingencies. This provides a computational explanation of the increased switching behavior seen in patients with schizophrenia, both in this and in previous studies (8,(11)(12)(13)(14)(15)(16). We replicate this finding in an independent cohort of unmedicated patients.…”
Section: Discussionsupporting
confidence: 87%
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“…We present two core findings: First, medicated patients both overestimated their prior higher-level belief about the volatility of the environment and exhibited an increased influence of volatility estimates on lower-level learning of actionoutcome contingencies. This provides a computational explanation of the increased switching behavior seen in patients with schizophrenia, both in this and in previous studies (8,(11)(12)(13)(14)(15)(16). We replicate this finding in an independent cohort of unmedicated patients.…”
Section: Discussionsupporting
confidence: 87%
“…Replicating previous studies (8,(11)(12)(13)(14)(15)(16), patients were impaired in flexible decisionmaking driven by enhanced switching between choice options. Using computational modeling of hierarchical Bayesian learning, we demonstrate a possible underlying learning mechanism: an enhanced prior belief about the environment being volatile combined and a stronger influence of volatility on lower-level learning of action-outcome contingencies.…”
Section: Discussionsupporting
confidence: 63%
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“…They exhibit increased switching and achieve fewer performance-dependent reversals, even when learning of initial stimulus-outcome associations appears intact. [91][92][93][94][95] This switching correlates with positive symptoms in both deterministic and probabilistic tasks. 93,96,97 In fact, patients with the highest positive symptom ratings exhibit the highest rates of switching, and they require fewer trials (i.e., less evidence) to alter responding after a reversal occurs.…”
Section: Reversal Learningmentioning
confidence: 92%
“…103 Intriguingly, recent analyses of reversal learning point to patient subgroups among both unmedicated, drug-naive patients (in the earliest stages of the illness) and medicated patients in the chronic phase. [91][92][93][94][95] Unlike healthy controls and patients who successfully navigate the task, a subgroup with higher positive symptoms exhibited reduced prefrontal cortex activation and choice behavior inconsistent with a Hidden Markov Model (a computational estimation of beliefs about reversals and contingency stability updated trial-by-trial 93 ). Patients who switch excessively also have more positive symptoms.…”
Section: Reversal Learningmentioning
confidence: 99%