Mild Reinforcement Learning Deficits in Patients With First-Episode Psychosis (original) (raw)
Related papers
2019
BackgroundSchizophrenia is a complex disorder in which the causal relations between risk genes and observed clinical symptoms are not well understood and the explanatory gap is too wide to be clarified without considering an intermediary level. Thus, we aimed to test the hypothesis of a pathway from molecular polygenic influence to clinical presentation occurring via deficits in reinforcement learning.MethodsWe administered a reinforcement learning task (Go/NoGo) that measures reinforcement learning and the effect of Pavlovian bias on decision making. We modelled the behavioural data with a hierarchical Bayesian approach (hBayesDM) to decompose task performance into its underlying learning mechanisms. Study 1 included controls (n= 29, F|M=0.81), At Risk Mental State for psychosis (ARMS, n= 23, F|M=0.35) and FEP (First-episode psychosis, n= 26, F|M=0.18). Study 2 included healthy adolescents (n= 735, F|M= 1.06), 390 of whom had their polygenic risk scores for schizophrenia (PRSs) cal...
Biological psychiatry, 2007
Background:Rewards and punishments may make distinct contributions to learning via separate striato-cortical pathways. We investigated whether fronto-striatal dysfunction in schizophrenia (SZ) is characterized by selective impairment in either reward- (Go) or punishment-driven (NoGo) learning.Methods:We administered two versions of a Probabilistic Selection task (Frank et al., 2004) to 40 SZs and 31 controls, using difficult-to-verbalize stimuli (Exp 1) and nameable objects (Exp 2). In an acquisition phase, participants learned to choose between three different stimulus pairs (AB, CD, EF) presented in random order, based on probabilistic feedback (80%, 70%, 60%). We used ANOVAs to assess the effects of group and reinforcement probability on two measures of contingency learning. To characterize the preference of subjects for choosing the most rewarded stimulus and avoiding the most punished stimulus, we subsequently tested participants with novel pairs of stimuli involving either A or B, providing no feedback.Results:Controls demonstrated superior performance during the first 40 acquisition trials in each of the 80% and 70% conditions versus the 60% condition; patients showed similarly impaired (<60%) performance in all three conditions. In novel test pairs, patients showed decreased preference for the most rewarded stimulus (A; t=2.674; p=0.01). Patients were unimpaired at avoiding the most negative stimulus (B; t=0.737).Conclusions:The results of these experiments provide additional evidence for the presence of deficits in reinforcement learning in SZ, suggesting that reward-driven (Go) learning may be more profoundly impaired than punishment-driven (NoGo) learning.
Reduced reward-related probability learning in schizophrenia patients
Neuropsychiatric disease and treatment, 2012
Although it is known that individuals with schizophrenia demonstrate marked impairment in reinforcement learning, the details of this impairment are not known. The aim of this study was to test the hypothesis that reward-related probability learning is altered in schizophrenia patients. Twenty-five clinically stable schizophrenia patients and 25 age- and gender-matched controls participated in the study. A simple gambling paradigm was used in which five different cues were associated with different reward probabilities (50%, 67%, and 100%). Participants were asked to make their best guess about the reward probability of each cue. Compared with controls, patients had significant impairment in learning contingencies on the basis of reward-related feedback. The correlation analyses revealed that the impairment of patients partially correlated with the severity of negative symptoms as measured on the Positive and Negative Syndrome Scale but that it was not related to antipsychotic dose....
General functioning predicts reward and punishment learning in schizophrenia
Schizophrenia research, 2011
Previous studies investigating feedback-driven reinforcement learning in patients with schizophrenia have provided mixed results. In this study, we explored the clinical predictors of reward and punishment learning using a probabilistic classification learning task. Patients with schizophrenia (n = 40) performed similarly to healthy controls (n = 30) on the classification learning task. However, more severe negative and general symptoms were associated with lower reward-learning performance, whereas poorer general psychosocial functioning was correlated with both lower reward-and punishment-learning performances. Multiple linear regression analyses indicated that general psychosocial functioning was the only significant predictor of reinforcement learning performance when education, antipsychotic dose, and positive, negative and general symptoms were included in the analysis. These results suggest a close relationship between reinforcement learning and general psychosocial functioning in schizophrenia.
Schizophrenia Bulletin, 2020
Background: Motivational deficits in people with psychosis may be a result of impairments in reinforcement learning (RL). Therefore, behavioral paradigms that can accurately measure these impairments and their change over time are essential. Methods: We examined the reliability and replicability of 2 RL paradigms (1 implicit and 1 explicit, each with positive and negative reinforcement components) given at 2 time points to healthy controls (n = 75), and people with bipolar disorder (n = 62), schizoaffective disorder (n = 60), and schizophrenia (n = 68). Results: Internal consistency was acceptable (mean α = 0.78 ± 0.15), but test-retest reliability was fair to low (mean intraclass correlation = 0.33 ± 0.25) for both implicit and explicit RL. There were no clear effects of practice for these tasks. Largely, performance on these tasks shows intact implicit and impaired explicit RL in psychosis. Symptom presentation did not relate to performance in any robust way. Conclusions: Our findings replicate previous literature showing spared implicit RL and impaired explicit reinforcement in psychosis. This suggests typical basal ganglia dopamine release, but atypical recruitment of the orbitofrontal and dorsolateral prefrontal cortices. However, we found that these tasks have only fair to low test-retest reliability and thus may not be useful for assessing change over time in clinical trials.
Journal of abnormal psychology, 2015
There is increasing evidence that schizophrenia (SZ) and bipolar disorder (BD) share a number of cognitive, neurobiological, and genetic markers. Shared features may be most prevalent among SZ and BD with a history of psychosis. This study extended this literature by examining reinforcement learning (RL) performance in individuals with SZ (n = 29), BD with a history of psychosis (BD+; n = 24), BD without a history of psychosis (BD-; n = 23), and healthy controls (HC; n = 24). RL was assessed through a probabilistic stimulus selection task with acquisition and test phases. Computational modeling evaluated competing accounts of the data. Each participant's trial-by-trial decision-making behavior was fit to 3 computational models of RL: (a) a standard actor-critic model simulating pure basal ganglia-dependent learning, (b) a pure Q-learning model simulating action selection as a function of learned expected reward value, and (c) a hybrid model where an actor-critic is "augment...
Neuropsychology, 2011
Objective: Patients with schizophrenia (SZ) show reinforcement learning impairments related to both the gradual/procedural acquisition of reward contingencies, and the ability to use trial-to-trial feedback to make rapid behavioral adjustments. Method: We used neurocomputational modeling to develop plausible mechanistic hypotheses explaining reinforcement learning impairments in individuals with SZ. We tested the model with a novel Go/NoGo learning task in which subjects had to learn to respond or withhold responses when presented with different stimuli associated with different probabilities of gains or losses in points. We analyzed data from 34 patients and 23 matched controls, characterizing positive-and negative-feedback-driven learning in both a training phase and a test phase. Results: Consistent with simulations from a computational model of aberrant dopamine input to the basal ganglia patients, patients with SZ showed an overall increased rate of responding in the training phase, together with reduced response-time acceleration to frequently rewarded stimuli across training blocks, and a reduced relative preference for frequently rewarded training stimuli in the test phase. Patients did not differ from controls on measures of procedural negative-feedback-driven learning, although patients with SZ exhibited deficits in trial-to-trial adjustments to negative feedback, with these measures correlating with negative symptom severity. Conclusions: These findings support the hypothesis that patients with SZ have a deficit in procedural "Go" learning, linked to abnormalities in DA transmission at D1-type receptors, despite a "Go bias" (increased response rate), potentially related to excessive tonic dopamine. Deficits in trial-to-trial reinforcement learning were limited to a subset of patients with SZ with severe negative symptoms, putatively stemming from prefrontal cortical dysfunction.
Explicit and Implicit Reinforcement Learning Across the Psychosis Spectrum
Journal of abnormal psychology, 2017
Motivational and hedonic impairments are core features of a variety of types of psychopathology. An important aspect of motivational function is reinforcement learning (RL), including implicit (i.e., outside of conscious awareness) and explicit (i.e., including explicit representations about potential reward associations) learning, as well as both positive reinforcement (learning about actions that lead to reward) and punishment (learning to avoid actions that lead to loss). Here we present data from paradigms designed to assess both positive and negative components of both implicit and explicit RL, examine performance on each of these tasks among individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis, and examine their relative relationships to specific symptom domains transdiagnostically. None of the diagnostic groups differed significantly from controls on the implicit RL tasks in either bias toward a rewarded response or bias away from a pu...
NeuroImage, 2010
In patients with schizophrenia, the ability to learn from reinforcement is known to be impaired. The present fMRI study aimed at investigating the neural correlates of reinforcement-related trial-and-error learning in 19 schizophrenia patients and 20 healthy volunteers. A modified gambling paradigm was applied where each cue indicated a subsequent number which had to be guessed. In order to vary predictability, the cuenumber associations were based on different probabilities (50%, 81%, 100%) which the participants were not informed about. Patients' ability to learn contingencies on the basis of feedback and reward was significantly impaired. While in healthy volunteers increasing predictability was associated with decreasing activation in a fronto-parietal network, this decrease was not detectable in patients. Analysis of expectancy-related reinforcement processing yielded a hypoactivation in putamen, dorsal cingulate and superior frontal cortex in patients relative to controls. Present results indicate that both reinforcement-associated processing and reinforcement learning might be impaired in the context of the disorder. They moreover suggest that the activation deficits which patients exhibit in association with the processing of reinforcement might constitute the basis for the learning deficits and their accompanying activation alterations.