Impaired Expected Value Computations in Schizophrenia Are Associated With a Reduced Ability to Integrate Reward Probability and Magnitude of Recent Outcomes

Effort-Cost Decision-making Among Individuals With Schizophrenia: A Systematic Review and Meta-analysis

Importance

Motivational impairments in schizophrenia are by definition associated with poor outcome. It is postulated that the reduction of goal-directed behavior arises from abnormal trade-offs between rewards and efforts.

Objective

To examine whether schizophrenia is associated with impairments in effort-cost decision-making.

Data Sources

For this systematic review and meta-analysis, the PubMed, ScienceDirect, PsycINFO, Embase, and ClinicalTrials.gov databases were searched from inception to July 2022 for studies that investigated effort-cost decision-making in schizophrenia. Search terms included effort, cost, and schizophrenia.

Study Selection

Consensual criteria for inclusion were peer-reviewed studies published in English that used a computerized effort-cost decision-making behavioral paradigm and compared individuals with schizophrenia with control individuals.

Data Extraction and Synthesis

The Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline was used for abstracting data. Data were extracted independently by 2 authors and then pooled using random-effects sizes and bayesian approaches.

Main Outcomes and Measures

The main outcomes were performance on effort-cost decision-making tasks requiring an effort-reward trade-off, measured by Hedges g effect size. Effects of moderators were tested with meta-regressions and subgroup analyses.

Results

Twenty studies involving 1503 participants were included: 837 individuals with schizophrenia (541 [64.6%] male; mean [SD] age, 35.89 [6.70] years) and 666 control individuals without schizophrenia (360 [54.1%] male; mean [SD] age, 34.16 [5.92] years). Participants with schizophrenia had significantly reduced willingness to expend effort for rewards compared with controls (k = 20; effect size, 0.43; 95% CI, 0.30-0.56; P < .001; I2 = 33.1%; Q test P = .08). The magnitude of the deficit was significantly greater for high-reward trials. The severity of negative symptoms was negatively associated with effort-cost decision-making (k = 8; effect size, -0.33; 95% CI, -0.50 to -0.15; P < .001), while participants with a high number of negative symptoms had a significantly larger impairment in effort-cost decision-making (k = 5; effect size, 0.47; 95% CI, 0.10-0.84; P = .01).

Conclusions and Relevance

In this systematic review and meta-analysis, schizophrenia was associated with deficits in effort allocation as indexed by effort-cost decision-making tasks. Understanding the cognitive and neurobiological mechanisms driving effort allocation impairments may assist in developing novel interventions.

Reward and fictive prediction error signals in ventral striatum: asymmetry between factual and counterfactual processing

Reward prediction error, the difference between the expected and obtained reward, is known to act as a reinforcement learning neural signal. In the current study, we propose a model fitting approach that combines behavioral and neural data to fit computational models of reinforcement learning. Briefly, we penalized subject-specific fitted parameters that moved away too far from the group median, except when that deviation led to an improvement in the model's fit to neural responses. By means of a probabilistic monetary learning task and fMRI, we compared our approach with standard model fitting methods. Q-learning outperformed actor-critic at both behavioral and neural level, although the inclusion of neuroimaging data into model fitting improved the fit of actor-critic models. We observed both action-value and state-value prediction error signals in the striatum, while standard model fitting approaches failed to capture state-value signals. Finally, left ventral striatum correlated with reward prediction error while right ventral striatum with fictive prediction error, suggesting a functional hemispheric asymmetry regarding prediction-error driven learning.

Retention of Value Representations Across Time in People With Schizophrenia and Healthy Control Subjects

BACKGROUND

The current study aimed to further etiological understanding of the psychological mechanisms underlying negative symptoms in people with schizophrenia. Specifically, we tested whether negative symptom severity is associated with reduced retention of reward-related information over time and thus a degraded ability to utilize such information to guide future action selection.

METHODS

Forty-four patients with a diagnosis of schizophrenia or schizoaffective disorder and 28 healthy control volunteers performed a probabilistic reinforcement-learning task involving stimulus pairs in which choices resulted in reward or in loss avoidance. Following training, participants indicated their valuation of learned stimuli in a test/transfer phase. The test/transfer phase was administered immediately following training and 1 week later. Percent retention was defined as accuracy at week-long delay divided by accuracy at immediate delay.

RESULTS

Healthy control subjects and people with schizophrenia showed similarly robust retention of reinforcement learning over a 1-week delay interval. However, in the schizophrenia group, negative symptom severity was associated with reduced retention of information regarding the value of actions across a week-long interval. This pattern was particularly notable for stimuli associated with reward compared with loss avoidance.

CONCLUSIONS

Our results show that although individuals with schizophrenia may initially learn about rewarding aspects of their environment, such learning decays at a more rapid rate in patients with severe negative symptoms. Thus, previously learned reward-related information may be more difficult to access to guide future decision making and to motivate action selection.

Disruption of Nrxn1α within excitatory forebrain circuits drives value-based dysfunction

Goal-directed behaviors are essential for normal function and significantly impaired in neuropsychiatric disorders. Despite extensive associations between genetic mutations and these disorders, the molecular contributions to goal-directed dysfunction remain unclear. We examined mice with constitutive and brain region-specific mutations in Neurexin1α, a neuropsychiatric disease-associated synaptic molecule, in value-based choice paradigms. We found Neurexin1α knockouts exhibited reduced selection of beneficial outcomes and impaired avoidance of costlier options. Reinforcement modeling suggested that this was driven by deficits in updating and representation of value. Disruption of Neurexin1α within telencephalic excitatory projection neurons, but not thalamic neurons, recapitulated choice abnormalities of global Neurexin1α knockouts. Furthermore, this selective forebrain excitatory knockout of Neurexin1α perturbed value-modulated neural signals within striatum, a central node in feedback-based reinforcement learning. By relating deficits in value-based decision-making to region-specific Nrxn1α disruption and changes in value-modulated neural activity, we reveal potential neural substrates for the pathophysiology of neuropsychiatric disease-associated cognitive dysfunction.

Enhancing Psychosis Risk Prediction Through Computational Cognitive Neuroscience

Research suggests that early identification and intervention with individuals at clinical high risk (CHR) for psychosis may be able to improve the course of illness. The first generation of studies suggested that the identification of CHR through the use of specialized interviews evaluating attenuated psychosis symptoms is a promising strategy for exploring mechanisms associated with illness progression, etiology, and identifying new treatment targets. The next generation of research on psychosis risk must address two major limitations: (1) interview methods have limited specificity, as recent estimates indicate that only 15%-30% of individuals identified as CHR convert to psychosis and (2) the expertise needed to make CHR diagnosis is only accessible in a handful of academic centers. Here, we introduce a new approach to CHR assessment that has the potential to increase accessibility and positive predictive value. Recent advances in clinical and computational cognitive neuroscience have generated new behavioral measures that assay the cognitive mechanisms and neural systems that underlie the positive, negative, and disorganization symptoms that are characteristic of psychotic disorders. We hypothesize that measures tied to symptom generation will lead to enhanced sensitivity and specificity relative to interview methods and the cognitive intermediate phenotype measures that have been studied to date that are typically indicators of trait vulnerability and, therefore, have a high false positive rate for conversion to psychosis. These new behavioral measures have the potential to be implemented on the internet and at minimal expense, thereby increasing accessibility of assessments.

Grant Report on Social Reward Learning in Schizophrenia †

We report on the ongoing R21 project “Social Reward Learning in Schizophrenia”. Impairments in social cognition are a hallmark of schizophrenia. However, little work has been done on social reward learning deficits in schizophrenia. The overall goal of the project is to assess social reward learning in schizophrenia. A probabilistic reward learning (PRL) task is being used in the MRI scanner to evaluate reward learning to negative and positive social feedback. Monetary reward learning is used as a comparison to assess specificity. Behavioral outcomes and brain areas, included those involved in reward, are assessed in patients with schizophrenia or schizoaffective disorder and controls. It is also critical to determine whether decreased expected value (EV) of social stimuli and/or reward prediction error (RPE) learning underlie social reward learning deficits to inform potential treatment pathways. Our central hypothesis is that the pattern of social learning deficits is an extension of a more general reward learning impairment in schizophrenia and that social reward learning deficits critically contribute to deficits in social motivation and pleasure. We hypothesize that people with schizophrenia will show impaired behavioral social reward learning compared to controls, as well as decreased ventromedial prefrontal cortex (vmPFC) EV signaling at time of choice and decreased striatal RPE signaling at time of outcome, with potentially greater impairment to positive than negative feedback. The grant is in its second year. It is hoped that this innovative approach may lead to novel and more targeted treatment approaches for social cognitive impairments, using cognitive remediation and/or brain stimulation.

Reward and punishment learning in schizophrenia and bipolar disorder

Prior studies on reward learning deficits in psychiatric disorders have used probabilistic learning tasks, making it unclear whether impairment is due to the probabilistic nature of the task rather than reward processing. In this study, we tested probabilistic vs. deterministic reward and punishment learning in healthy controls and three patient groups: schizophrenia (SZ), psychotic bipolar disorder (BD), and nonpsychotic BD. Experimental results show that reward learning was impaired in patients with SZ and patients with psychotic BD in the probabilistic learning task compared to patients with nonpsychotic BD and healthy controls. In contrast, punishment learning in the probabilistic task was impaired in patients with nonpsychotic BD compared to the other patient groups and healthy controls. There were no significant differences among all groups in the deterministic learning task scores. We also found that Hamilton Depression Scale scores negatively correlated with probabilistic learning performance. Our data may suggest that reward learning impairment may be due to the nature of the task as well as subtype of BD.

Impact of Positive Emotion Regulation Training on Negative Symptoms and Social Functioning in Schizophrenia: A Field Test

Background: The poor efficacy of drug or psychological treatments on the primary negative symptoms of schizophrenia has led to the development of new interventions. The Positive Emotions Program for Schizophrenia (PEPS) is an emotion regulation strategy training that aims to intensify positive emotions and develop positive performance beliefs. A randomized controlled trial showed that PEPS is effective in reducing the composite score of the reduction of experience syndrome (anhedonia and apathy). The present study is designed to evaluate its feasibility in natural conditions to measure external validity of PEPS. Materials and Methods: Twenty-one participants recruited through the French national network of expert centers followed eight sessions of PEPS and were assessed pre- and posttest with the Scale for Assessment of Negative Symptoms (SANS) and the Personal and Social Performance (PSP). The scales of the SANS were divided into a composite score of the reduction of the ability to experience and a composite score of the reduction of expression. Results: All participants followed the 8 sessions of PEPS, and both composite scores were significantly and clinically improved at posttest. Social functioning assessed with the PSP was also improved. Conclusions: This field test shows that participation in PEPS is accompanied by a reduction of negative symptoms and an improvement of social functioning. Both negative syndromes, reduction of expression and reduction of experience, are improved. Participants are younger than those in previous studies, which may explain this unexpected result. However, this calls for a controlled study with younger participants.