Negative symptoms and the failure to represent the expected reward value of actions: behavioral and computational modeling evidence

Linking Salience Signaling With Early Adversity and Affective Distress in Individuals at Clinical High Risk for Psychosis: Results From an Event-Related fMRI Study

Evidence suggests dysregulation of the salience network in individuals with psychosis, but few studies have examined the intersection of stress exposure and affective distress with prediction error (PE) signals among youth at clinical high-risk (CHR). Here, 26 individuals at CHR and 19 healthy volunteers (HVs) completed a monetary incentive delay task in conjunction with fMRI. We compared these groups on the amplitudes of neural responses to surprising outcomes-PEs without respect to their valence-across the whole brain and in two regions of interest, the anterior insula and amygdala. We then examined relations of these signals to the severity of depression, anxiety, and trauma histories in the CHR group. Relative to HV, youth at CHR presented with aberrant PE-evoked activation of the temporoparietal junction and weaker deactivation of the precentral gyrus, posterior insula, and associative striatum. No between-group differences were observed in the amygdala or anterior insula. Among youth at CHR, greater trauma histories were correlated with stronger PE-evoked amygdala activation. No associations were found between affective symptoms and the neural responses to PE. Our results suggest that unvalenced PE signals may provide unique information about the neurobiology of CHR syndromes and that early adversity exposure may contribute to neurobiological heterogeneity in this group. Longitudinal studies of young people with a range of risk syndromes are needed to further disentangle the contributions of distinct aspects of salience signaling to the development of psychopathology.

Reinforcement-learning in fronto-striatal circuits

We review the current state of knowledge on the computational and neural mechanisms of reinforcement-learning with a particular focus on fronto-striatal circuits. We divide the literature in this area into five broad research themes: the target of the learning-whether it be learning about the value of stimuli or about the value of actions; the nature and complexity of the algorithm used to drive the learning and inference process; how learned values get converted into choices and associated actions; the nature of state representations, and of other cognitive machinery that support the implementation of various reinforcement-learning operations. An emerging fifth area focuses on how the brain allocates or arbitrates control over different reinforcement-learning sub-systems or "experts". We will outline what is known about the role of the prefrontal cortex and striatum in implementing each of these functions. We then conclude by arguing that it will be necessary to build bridges from algorithmic level descriptions of computational reinforcement-learning to implementational level models to better understand how reinforcement-learning emerges from multiple distributed neural networks in the brain.

Anhedonia in Schizophrenia

Anhedonia has long been considered a cardinal symptom of schizophrenia. This symptom is strongly associated with poor functional outcome, and limited treatment options are available. While originally conceptualized as an inability to experience pleasure, recent work has consistently shown that individuals with schizophrenia have an intact capacity to experience pleasure in-the-moment. Adjacent work in basic affective neuroscience has broadened the conceptualization of anhedonia to include not only the capacity to experience pleasure but highlights important temporal affective dynamics and decision-making processes that go awry in schizophrenia. Here we detail these mechanisms for emotional and motivational impairment in people with schizophrenia including: (1) initial response to reward; (2) reward anticipation; (3) reward learning; (4) effort-cost decision-making; (5) working memory and cognitive control. We will review studies that utilized various types of rewards (e.g., monetary, social), in order to draw conclusions regarding whether findings vary by reward type. We will then discuss how modern assessment methods may best incorporate each of the mechanisms, to provide a more fine-grained understanding of anhedonia in individuals with schizophrenia. We will close by providing a discussion of relevant future directions.

The Role of Dopaminergic Genes in Probabilistic Reinforcement Learning in Schizophrenia Spectrum Disorders

Schizophrenia spectrum disorders (SZ) are characterized by impairments in probabilistic reinforcement learning (RL), which is associated with dopaminergic circuitry encompassing the prefrontal cortex and basal ganglia. However, there are no studies examining dopaminergic genes with respect to probabilistic RL in SZ. Thus, the aim of our study was to examine the impact of dopaminergic genes on performance assessed by the Probabilistic Selection Task (PST) in patients with SZ in comparison to healthy control (HC) subjects. In our study, we included 138 SZ patients and 188 HC participants. Genetic analysis was performed with respect to the following genetic polymorphisms: rs4680 in COMT, rs907094 in DARP-32, rs2734839, rs936461, rs1800497, and rs6277 in DRD2, rs747302 and rs1800955 in DRD4 and rs28363170 and rs2975226 in DAT1 genes. The probabilistic RL task was completed by 59 SZ patients and 95 HC subjects. SZ patients performed significantly worse in acquiring reinforcement contingencies during the task in comparison to HCs. We found no significant association between genetic polymorphisms and RL among SZ patients; however, among HC participants with respect to the DAT1 rs28363170 polymorphism, individuals with 10-allele repeat genotypes performed better in comparison to 9-allele repeat carriers. The present study indicates the relevance of the DAT1 rs28363170 polymorphism in RL in HC participants.

Greater preference for eveningness is associated with negative symptoms in an ultra-high risk for psychosis sample

AIM

Investigating biological processes in at-risk individuals may help elucidate the aetiological mechanisms underlying psychosis development, refine prediction models and improve intervention strategies. This study examined the associations between sleep disturbances, chronotype, depressive and psychotic symptoms in individuals at ultra-high risk for psychosis.

METHODS

A sample of 81 ultra-high risk patients completed clinical interviews and self-report assessments of chronotype and sleep during the Neurapro clinical trial. Mixed regression was used to investigate the cross-sectional associations between symptoms and sleep disturbances/chronotype.

RESULTS

Sleep disturbances were significantly associated with increased depressive and attenuated positive psychotic symptoms. Greater preference for eveningness was significantly associated with increased negative symptoms, but not with depressive or attenuated positive psychotic symptoms.

CONCLUSION

Sleep disturbances and chronotype may impact the emerging psychopathology experienced by ultra-high risk individuals. Further, the preliminary relationship observed between greater preference for eveningness and negative symptoms offers a unique opportunity to treat negative symptoms through chronobiological approaches.

Decision-making in suicidal behavior: A systematic review and meta-analysis

Impaired decision-making (DM) is well-known in suicidal behavior (SB). We aimed to review the evidence on DM and its mediating factors in SB and perform a meta-analysis on DM assessed using the Iowa Gambling Task (IGT). We conducted a search on databases of papers published on DM and SB up to 2020: 46 studies were included in the systematic review, and 18 in the meta-analysis. For meta-analysis, we compared DM performance between suicide attempters (SAs) and patients (PCs) or healthy controls (HCs). The systematic review showed that SAs have greater difficulties in all DM domains. The meta-analysis found worse IGT performance among SAs in comparison with PCs and HCs. A meta-regression did not find differences for age, gender, psychiatric disorder, and clinical status. Our findings indicate that SAs exhibited deficits in DM under conditions of risk though not ambiguity. Worse DM was independent of age, gender, psychiatric disorder, and suggested that DM impairment could be considered a cognitive trait of suicidal vulnerability, a risk factor and an attribute of SAs.

Mechanisms Underlying Motivational Dysfunction in Schizophrenia

Negative symptoms are a debilitating feature of schizophrenia which are often resistant to pharmacological intervention. The mechanisms underlying them remain poorly understood, and diagnostic methods rely on phenotyping through validated questionnaires. Deeper endo-phenotyping is likely to be necessary in order to improve current understanding. In the last decade, valuable behavioural insights have been gained through the use of effort-based decision making (EBDM) tasks. These have highlighted impairments in reward-related processing in schizophrenia, particularly associated with negative symptom severity. Neuroimaging investigations have related these changes to dysfunction within specific brain networks including the ventral striatum (VS) and frontal brain regions. Here, we review the behavioural and neural evidence associated with negative symptoms, shedding light on potential underlying mechanisms and future therapeutic possibilities. Findings in the literature suggest that schizophrenia is characterised by impaired reward based learning and action selection, despite preserved hedonic responses. Associations between amotivation and reward-processing deficits have not always been clear, and may be mediated by factors including cognitive dysfunction or dysfunctional or self-defeatist beliefs. Successful endo-phenotyping of negative symptoms as a function of objective behavioural and neural measurements is crucial in advancing our understanding of this complex syndrome. Additionally, transdiagnostic research–leveraging findings from other brain disorders, including neurological ones–can shed valuable light on the possible common origins of motivation disorders across diseases and has important implications for future treatment development.

An active inference perspective on the negative symptoms of schizophrenia

Predictive coding has played a transformative role in the study of psychosis, casting delusions and hallucinations as statistical inference in a system with abnormal precision. However, the negative symptoms of schizophrenia, such as affective blunting, avolition, and asociality, remain poorly understood. We propose a computational framework for emotional expression based on active inference-namely that affective behaviours such as smiling are driven by predictions about the social consequences of smiling. Similarly to how delusions and hallucinations can be explained by predictive uncertainty in sensory circuits, negative symptoms naturally arise from uncertainty in social prediction circuits. This perspective draws on computational principles to explain blunted facial expressiveness and apathy-anhedonia in schizophrenia. Its phenomenological consequences also shed light on the content of paranoid delusions and indistinctness of self-other boundaries. Close links are highlighted between social prediction, facial affect mirroring, and the fledgling study of interoception. Advances in automated analysis of facial expressions and acoustic speech patterns will allow empirical testing of these computational models of the negative symptoms of schizophrenia.

Relations Among Anhedonia, Reinforcement Learning, and Global Functioning in Help-seeking Youth

Dysfunction in the neural circuits underlying salience signaling is implicated in symptoms of psychosis and may predict conversion to a psychotic disorder in youth at clinical high risk (CHR) for psychosis. Additionally, negative symptom severity, including consummatory and anticipatory aspects of anhedonia, may predict functional outcome in individuals with schizophrenia-spectrum disorders. However, it is unclear whether anhedonia is related to the ability to attribute incentive salience to stimuli (through reinforcement learning [RL]) and whether measures of anhedonia and RL predict functional outcome in a younger, help-seeking population. We administered the Salience Attribution Test (SAT) to 33 participants who met criteria for either CHR or a recent-onset psychotic disorder and 29 help-seeking youth with nonpsychotic disorders. In the SAT, participants must identify relevant and irrelevant stimulus dimensions and be sensitive to different reinforcement probabilities for the 2 levels of the relevant dimension ("adaptive salience"). Adaptive salience attribution was positively related to both consummatory pleasure and functioning in the full sample. Analyses also revealed an indirect effect of adaptive salience on the relation between consummatory pleasure and both role (αβ = .22, 95% CI = 0.02, 0.48) and social functioning (αβ = .14, 95% CI = 0.02, 0.30). These findings suggest a distinct pathway to poor global functioning in help-seeking youth, via impaired reward sensitivity and RL.

Computerized Assessment of Psychosis Risk

Early detection and intervention with young people at clinical high risk (CHR) for psychosis is critical for prevention efforts focused on altering the trajectory of psychosis. Early CHR research largely focused on validating clinical interviews for detecting at-risk individuals; however, this approach has limitations related to: (1) specificity (i.e., only 20% of CHR individuals convert to psychosis) and (2) the expertise and training needed to administer these interviews is limited. The purpose of our study is to develop the computerized assessment of psychosis risk (CAPR) battery, consisting of behavioral tasks that require minimal training to administer, can be administered online, and are tied to the neurobiological systems and computational mechanisms implicated in psychosis. The aims of our study are as follows: (1A) to develop a psychosis-risk calculator through the application of machine learning (ML) methods to the measures from the CAPR battery, (1B) evaluate group differences on the risk calculator score and test the hypothesis that the risk calculator score of the CHR group will differ from help-seeking and healthy controls, (1C) evaluate how baseline CAPR battery performance relates to symptomatic outcome two years later (i.e., conversion and symptomatic worsening). These aims will be explored in 500 CHR participants, 500 help-seeking individuals, and 500 healthy controls across the study sites. This project will provide a next-generation CHR battery, tied to illness mechanisms and powered by cutting-edge computational methods that can be used to facilitate the earliest possible detection of psychosis risk.

Altered risky decision making in patients with early non-affective psychosis

Abnormal risky decision making may represent an important factor contributing to functional impairment in psychotic disorders. Previous research revealed impaired decision making under risk in patients with chronic schizophrenia. However, risky decision making is under-studied in the early course of illness. We examined risky decision making in 33 patients with early non-affective psychosis and 32 demographically matched controls, using two well-validated experimental paradigms, balloon analogue risk task (BART) and Risky-Gains task (RGT), which modeled and assessed actual risk-taking behaviors in deliberative and time-pressured decision-making situations, respectively. Our results showed that patients exhibited suboptimal decision making on the BART and were more risk averse than controls by having fewer average balloon pumps in non-burst trials, lower explosion rate and lower total points gained. On the RGT, patients also behaved more conservatively than controls, with lower overall rate in choosing the risky option. Intriguingly, patients performed comparably to controls in adjusting risk-taking pattern following punished trials, suggesting relatively preserved sensitivity to punishment in early psychosis. Risk-taking measures showed no significant correlations with any symptom dimensions, impulsivity traits, cognitive functions or antipsychotic treatment after correcting for multiple comparisons. This study is the first to investigate risk-taking propensity in early psychosis based on BART/RGT performance, and consistently indicate that patients with early psychosis displayed altered risky decision making with increased risk aversion relative to healthy participants. Further investigation is warranted to clarify the longitudinal course of aberrant risky decision making and its relationship with functional outcome in early psychosis.

Reinforcement learning abnormalities in the attenuated psychosis syndrome and first episode psychosis

Prior studies indicate that chronic schizophrenia (SZ) is associated with a specific profile of reinforcement learning abnormalities. These impairments are characterized by: 1) reductions in learning rate, and 2) impaired Go learning and intact NoGo learning. Furthermore, each of these deficits are associated with greater severity of negative symptoms, consistent with theoretical perspectives positing that avolition and anhedonia are associated with impaired value representation. However, it is unclear whether these deficits extend to earlier phases of psychotic illness and when individuals are unmedicated. Two studies were conducted to examine reinforcement learning deficits in earlier phases of psychosis and in high risk patients. In study 1, participants included 35 participants with first episode psychosis (FEP) with limited antipsychotic medication exposure and 25 healthy controls (HC). Study 2 included 17 antipsychotic naïve individuals who were at clinical high-risk for psychosis (CHR) (i.e., attenuated psychosis syndrome) and 18 matched healthy controls (HC). In both studies, participants completed the Temporal Utility Integration Task, a measure of probabilistic reinforcement learning that contained Go and NoGo learning blocks. FEP displayed impaired Go and NoGo learning. In contrast, CHR did not display impairments in Go or NoGo learning. Impaired Go learning was not significantly associated with clinical outcomes in the CHR or FEP samples. Findings provide new evidence for areas of spared and impaired reinforcement learning in early phases of psychosis.

Brain activity and connectivity differences in reward value discrimination during effort computation in schizophrenia

Negative symptoms in the motivational domain are strongly correlated with deficits in social and occupational functioning in schizophrenia. However, the neural substrates underlying these symptoms remain largely unknown. Twenty-eight adults with schizophrenia and twenty healthy volunteers underwent functional magnetic resonance while completing a lottery game designed to capture reward-related cognitive processes. Each trial demanded an initial investment of effort in form of key presses to increase the odds of winning. Brain activity in response to different reward cues (1 euro versus 1 cent) was compared between groups. Whereas controls invested more effort in improving their chances to win 1 euro compared to 1 cent in the lottery game, patients invested similarly high amounts of effort in both reward conditions. The neuroimaging analysis revealed lower neural activity in the bilateral caudate and cingulo-opercular circuits and decreased effective connectivity between reward-associated areas and neural nodes in the frontoparietal and salience network in response to high- versus low-reward conditions in schizophrenia patients compared to controls. Effective connectivity differences across conditions were associated with amotivation symptoms in patients. Overall, our data provide the evidence of alterations in neural activity in the caudate and cingulo-opercular "task maintenance" circuits and frontoparietal effective connectivity with reward-associated nodes as possible underlying mechanisms of reward value discrimination deficits affecting effort computation in schizophrenia.

Proof-of-Mechanism Study of the Phosphodiesterase 10 Inhibitor RG7203 in Patients With Schizophrenia and Negative Symptoms

Background

Reduced activation of dopamine D₁ receptor signaling may be implicated in reward functioning as a potential driver of negative symptoms in schizophrenia. Phosphodiesterase 10A (PDE10A), an enzyme that is highly expressed in the striatum, modulates both dopamine D₂- and D₁-dependent signaling.

Methods

We assessed whether augmentation of D₁ signaling by the PDE10 inhibitor RG7203 enhances imaging and behavioral markers of reward functions in patients with schizophrenia and negative symptoms. In a 3-period, double-blind, crossover study, we investigated the effects of RG7203 (5 mg and 15 mg doses) and placebo as adjunctive treatment to stable background antipsychotic treatment in patients with chronic schizophrenia with moderate levels of negative symptoms. Effects on reward functioning and reward-based effortful behavior were evaluated using the monetary incentive delay task during functional magnetic resonance imaging and the effort-cost-benefit and working memory reinforcement learning tasks.

Results

Patients (N = 33; 30 male, mean age ± SD 36.6 ± 7.0 years; Positive and Negative Syndrome Scale negative symptom factor score 23.0 ± 3.5 at screening) were assessed at three study centers in the United States; 24 patients completed the study. RG7203 at 5 mg significantly increased reward expectation–related activity in the monetary incentive delay task, but in the context of significantly decreased overall activity across all task conditions.

Conclusions

In contrast to our expectations, RG7203 significantly worsened reward-based effortful behavior and indices of reward learning. The results do not support the utility of RG7203 as adjunctive treatment for negative symptoms in patients with schizophrenia.

Stochasticity, Nonlinear Value Functions, and Update Rules in Learning Aesthetic Biases

A theoretical framework for the reinforcement learning of aesthetic biases was recently proposed based on brain circuitries revealed by neuroimaging. A model grounded on that framework accounted for interesting features of human aesthetic biases. These features included individuality, cultural predispositions, stochastic dynamics of learning and aesthetic biases, and the peak-shift effect. However, despite the success in explaining these features, a potential weakness was the linearity of the value function used to predict reward. This linearity meant that the learning process employed a value function that assumed a linear relationship between reward and sensory stimuli. Linearity is common in reinforcement learning in neuroscience. However, linearity can be problematic because neural mechanisms and the dependence of reward on sensory stimuli were typically nonlinear. Here, we analyze the learning performance with models including optimal nonlinear value functions. We also compare updating the free parameters of the value functions with the delta rule, which neuroscience models use frequently, vs. updating with a new Phi rule that considers the structure of the nonlinearities. Our computer simulations showed that optimal nonlinear value functions resulted in improvements of learning errors when the reward models were nonlinear. Similarly, the new Phi rule led to improvements in these errors. These improvements were accompanied by the straightening of the trajectories of the vector of free parameters in its phase space. This straightening meant that the process became more efficient in learning the prediction of reward. Surprisingly, however, this improved efficiency had a complex relationship with the rate of learning. Finally, the stochasticity arising from the probabilistic sampling of sensory stimuli, rewards, and motivations helped the learning process narrow the range of free parameters to nearly optimal outcomes. Therefore, we suggest that value functions and update rules optimized for social and ecological constraints are ideal for learning aesthetic biases.

Decision making under ambiguity and risk in adolescent-onset schizophrenia

OBJECTIVE

Numerous studies have identified impaired decision making (DM) under both ambiguity and risk in adult patients with schizophrenia. However, the assessment of DM in patients with adolescent-onset schizophrenia (AOS) has been challenging as a result of the instability and heterogeneity of manifestations. The Iowa Gambling Task (IGT) and Game of Dice Task (GDT), which are frequently used to evaluate DM respectively under ambiguity and risk, are sensitive to adolescents and neuropsychiatric patients. Our research intended to examine the performance of DM in a relatively large sample of patients with AOS using the above-mentioned two tasks. We also aimed to take a closer look at the relationship between DM and symptom severity of schizophrenia.

METHODS

We compared the performance of DM in 71 patients with AOS and 53 well-matched healthy controls using IGT for DM under ambiguity and GDT for DM under risk through net scores, total scores and feedback ration. Neuropsychological tests were conducted in all participants. Clinical symptoms were evaluated by using Positive and Negative Syndrome Scale (PANSS) in 71 patients with AOS. Pearson's correlation revealed the relationship among total score of DM and clinical and neuropsychological data.

RESULTS

Compared to healthy controls, patients with AOS failed to show learning effect and had a significant difference on the 5th block in IGT and conducted more disadvantageous choices as well as exhibited worse negative feedback rate in GDT. Apart from DM impairment under risk, diminished DM abilities under ambiguity were found related to poor executive function in AOS in the present study.

CONCLUSIONS

Our findings unveiled the abnormal pattern of DM in AOS, mainly reflected under the risky condition, extending the knowledge on the performance of DM under ambiguity and risk in AOS. Inefficient DM under risk may account for the lagging impulse control and the combined effects of developmental disease. In addition, our study demonstrated that the performance on IGT was related to executive function in AOS.

Reliability and Replicability of Implicit and Explicit Reinforcement Learning Paradigms in People With Psychotic Disorders

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.

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.

Predicting Attention-Shaping Response in People With Schizophrenia

ABSTRACT

People with schizophrenia often experience attentional impairments that hinder learning during psychological interventions. Attention shaping is a behavioral technique that improves attentiveness in this population. Because reinforcement learning (RL) is thought to be the mechanism by which attention shaping operates, we investigated if preshaping RL performance predicted level of response to attention shaping in people with schizophrenia. Contrary to hypotheses, a steeper attentiveness growth curve was predicted by less intact pretreatment RL ability and lower baseline attentiveness, accounting for 59% of the variance. Moreover, baseline attentiveness accounted for over 13 times more variance in response to attention shaping than did RL ability. Results suggest attention shaping is most effective for lower-functioning patients, and those high in RL ability may already be close to ceiling in terms of their response to reinforcers. Attention shaping may not be a primarily RL-driven intervention, and other mechanisms of its effects should be considered.

High-frequency neuromodulation improves obsessive-compulsive behavior

Nearly one billion people worldwide suffer from obsessive-compulsive behaviors^1,2, yet our mechanistic understanding of these behaviors is incomplete, and effective therapeutics are unavailable. An emerging perspective characterizes obsessive-compulsive behaviors as maladaptive habit learning^3,4, which may be associated with abnormal beta-gamma neurophysiology of the orbitofrontal-striatal circuitry during reward processing^5,6. We target the orbitofrontal cortex with alternating current, personalized to the intrinsic beta-gamma frequency of the reward network, and show rapid, reversible, frequency-specific modulation of reward- but not punishment-guided choice behavior and learning, driven by increased exploration in the setting of an actor-critic architecture. Next, we demonstrate that chronic application of the procedure over 5 days robustly attenuates obsessive-compulsive behavior in a non-clinical population for 3 months, with the largest benefits for individuals with more severe symptoms. Finally, we show that convergent mechanisms underlie modulation of reward learning and reduction of obsessive-compulsive symptoms. The results contribute to neurophysiological theories of reward, learning and obsessive-compulsive behavior, suggest a unifying functional role of rhythms in the beta-gamma range, and set the groundwork for the development of personalized circuit-based therapeutics for related disorders.

Modeling perception and behavior in individuals at clinical high risk for psychosis: Support for the predictive processing framework

Early intervention in psychotic spectrum disorders is critical for maximizing key clinical outcomes. While there is some evidence for the utility of intervention during the prodromal phase of the illness, efficacy of interventions is difficult to assess without appropriate risk stratification. This will require biomarkers that robustly help to identify risk level and are also relatively easy to obtain. Recent work highlights the utility of computer-based behavioral tasks for understanding the pathophysiology of psychotic symptoms. Computational modeling of performance on such tasks may be particularly useful because they explicitly and formally link performance and symptom expression. Several recent studies have successfully applied principles of Bayesian inference to understanding the computational underpinnings of hallucinations. Within this framework, hallucinations are seen as arising from an over-weighting of prior beliefs relative to sensory evidence. This view is supported by recently-published data from two tasks: the Conditioned Hallucinations (CH) task, which determines the degree to which participants use expectations in detecting a target tone; and a Sine-Vocoded Speech (SVS) task, in which participants can use prior exposure to speech samples to inform their understanding of degraded speech stimuli. We administered both of these tasks to two samples of participants at clinical high risk for psychosis (CHR; N = 19) and healthy controls (HC; N = 17). CHR participants reported both more conditioned hallucinations and more pre-training SVS detection. In addition, relationships were found between participants' performance on both tasks. On computational modeling of behavior on the CH task, CHR participants demonstrate significantly poorer recognition of task volatility as well as a trend toward higher weighting of priors. A relationship was found between this latter effect and performance on both tasks. Taken together, these results support the assertion that these two tasks may be driven by similar latent factors in perceptual inference, and highlight the potential utility of computationally-based tasks in identifying risk.

Reward processing electrophysiology in schizophrenia: Effects of age and illness phase

BACKGROUND

Reward processing abnormalities may underlie characteristic pleasure and motivational impairments in schizophrenia. Some neural measures of reward processing show age-related modulation, highlighting the importance of considering age effects on reward sensitivity. We compared event-related potentials (ERPs) reflecting reward anticipation (stimulus-preceding negativity, SPN) and evaluation (reward positivity, RewP; late positive potential, LPP) across individuals with schizophrenia (SZ) and healthy controls (HC), with an emphasis on examining the effects of chronological age, brain age (i.e., predicted age based on neurobiological measures), and illness phase.

METHODS

Subjects underwent EEG while completing a slot-machine task for which rewards were not dependent on performance accuracy, speed, or response preparation. Slot-machine task EEG responses were compared between 54 SZ and 54 HC individuals, ages 19 to 65. Reward-related ERPs were analyzed with respect to chronological age, categorically-defined illness phase (early; ESZ versus chronic schizophrenia; CSZ), and were used to model brain age relative to chronological age.

RESULTS

Illness phase-focused analyses indicated there were no group differences in average SPN or RewP amplitudes. However, a group × reward outcome interaction revealed that ESZ differed from HC in later outcome processing, reflected by greater LPP responses following loss versus reward (a reversal of the HC pattern). While brain age estimates did not differ among groups, depressive symptoms in SZ were associated with older brain age estimates while controlling for negative symptoms.

CONCLUSIONS

ESZ and CSZ did not differ from HC in reward anticipation or early outcome processing during a cognitively undemanding reward task, highlighting areas of preserved functioning. However, ESZ showed altered later reward outcome evaluation, pointing to selective reward deficits during the early illness phase of schizophrenia. Further, an association between ERP-derived brain age and depressive symptoms in SZ extends prior findings linking depression with reward-related ERP blunting. Taken together, both illness phase and age may impact reward processing among SZ, and brain aging may offer a promising, novel marker of reward dysfunction that warrants further study.

Abnormal cognitive effort allocation and its association with amotivation in first-episode psychosis

BACKGROUND

Abnormal effort-based decision-making represents a potential mechanism underlying motivational deficits (amotivation) in psychotic disorders. Previous research identified effort allocation impairment in chronic schizophrenia and focused mostly on physical effort modality. No study has investigated cognitive effort allocation in first-episode psychosis (FEP).

METHOD

Cognitive effort allocation was examined in 40 FEP patients and 44 demographically-matched healthy controls, using Cognitive Effort-Discounting (COGED) paradigm which quantified participants' willingness to expend cognitive effort in terms of explicit, continuous discounting of monetary rewards based on parametrically-varied cognitive demands (levels N of N-back task). Relationship between reward-discounting and amotivation was investigated. Group differences in reward-magnitude and effort-cost sensitivity, and differential associations of these sensitivity indices with amotivation were explored.

RESULTS

Patients displayed significantly greater reward-discounting than controls. In particular, such discounting was most pronounced in patients with high levels of amotivation even when N-back performance and reward base amount were taken into consideration. Moreover, patients exhibited reduced reward-benefit sensitivity and effort-cost sensitivity relative to controls, and that decreased sensitivity to reward-benefit but not effort-cost was correlated with diminished motivation. Reward-discounting and sensitivity indices were generally unrelated to other symptom dimensions, antipsychotic dose and cognitive deficits.

CONCLUSION

This study provides the first evidence of cognitive effort-based decision-making impairment in FEP, and indicates that decreased effort expenditure is associated with amotivation. Our findings further suggest that abnormal effort allocation and amotivation might primarily be related to blunted reward valuation. Prospective research is required to clarify the utility of effort-based measures in predicting amotivation and functional outcome in FEP.

Cognitive Impairment and Diminished Neural Responses Constitute a Biomarker Signature of Negative Symptoms in Psychosis

The treatment of negative symptoms (NS) in psychosis represents an urgent unmet medical need given the significant functional impairment it contributes to psychosis syndromes. The lack of progress in treating NS is impacted by the lack of known pathophysiology or associated quantitative biomarkers, which could provide tools for research. This current analysis investigated potential associations between NS and an extensive battery of behavioral and brain-based biomarkers in 932 psychosis probands from the B-SNIP database. The current analyses examined associations between PANSS-defined NS and (1) cognition, (2) pro-/anti-saccades, (3) evoked and resting-state electroencephalography (EEG), (4) resting-state fMRI, and (5) tractography. Canonical correlation analyses yielded symptom-biomarker constructs separately for each biomarker modality. Biomarker modalities were integrated using canonical discriminant analysis to summarize the symptom-biomarker relationships into a "biomarker signature" for NS. Finally, distinct biomarker profiles for 2 NS domains ("diminished expression" vs "avolition/apathy") were computed using step-wise linear regression. NS were associated with cognitive impairment, diminished EEG response amplitudes, deviant resting-state activity, and oculomotor abnormalities. While a connection between NS and poor cognition has been established, association to neurophysiology is novel, suggesting directions for future mechanistic studies. Each biomarker modality was related to NS in distinct and complex ways, giving NS a rich, interconnected fingerprint and suggesting that any one biomarker modality may not adequately capture the full spectrum of symptomology.

Effective connectivity of the right anterior insula in schizophrenia: The salience network and task-negative to task-positive transition

Triple network dysfunction theory of schizophrenia postulates that the interaction between the default-mode and the fronto-parietal executive network is disrupted by aberrant salience signals from the right anterior insula (rAI). To date, it is not clear how the proposed resting-state disruption translates to task-processing inefficiency in subjects with schizophrenia. Using a contiguous resting and 2-back task performance fMRI paradigm, we quantified the change in effective connectivity that accompanies rest-to-task state transition in 29 clinically stable patients with schizophrenia and 31 matched healthy controls. We found an aberrant task-evoked increase in the influence of the rAI to both executive (Cohen's d = 1.35, p = 2.8 × 10-6) and default-mode (Cohen's d = 1.22, p = 1.5 × 10-5) network regions occur in patients when compared to controls. In addition, the effective connectivity from middle occipital gyrus (dorsal visual cortex) to insula is also increased in patients as compared with healthy controls. Aberrant insula to executive network influence is pronounced in patients with more severe negative symptom burden. These findings suggest that control signals from rAI are abnormally elevated and directed towards both task-positive and task-negative brain regions, when task-related demands arise in schizophrenia. This aberrant, undiscriminating surge in salience signalling may disrupt contextually appropriate allocation of resources in the neuronal workspace in patients with schizophrenia.

Reinforcement learning as an intermediate phenotype in psychosis? Deficits sensitive to illness stage but not associated with polygenic risk of schizophrenia in the general population

BACKGROUND

Schizophrenia 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.

METHODS

We 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) calculated.

RESULTS

Patients with FEP showed significant impairments in overriding Pavlovian conflict, a lower learning rate and a lower sensitivity to both reward and punishment. Less widespread deficits were observed in ARMS. PRSs did not significantly predict performance on the task in the general population, which only partially correlated with measures of psychopathology.

CONCLUSIONS

Reinforcement learning deficits are observed in first episode psychosis and, to some extent, in those at clinical risk for psychosis, and were not predicted by molecular genetic risk for schizophrenia in healthy individuals. The study does not support the role of reinforcement learning as an intermediate phenotype in psychosis.

Impaired theta phase coupling underlies frontotemporal dysconnectivity in schizophrenia

Frontotemporal dysconnectivity is a key pathology in schizophrenia. The specific nature of this dysconnectivity is unknown, but animal models imply dysfunctional theta phase coupling between hippocampus and medial prefrontal cortex (mPFC). We tested this hypothesis by examining neural dynamics in 18 participants with a schizophrenia diagnosis, both medicated and unmedicated; and 26 age, sex and IQ matched control subjects. All participants completed two tasks known to elicit hippocampal-prefrontal theta coupling: a spatial memory task (during magnetoencephalography) and a memory integration task. In addition, an overlapping group of 33 schizophrenia and 29 control subjects underwent PET to measure the availability of GABAARs expressing the α5 subunit (concentrated on hippocampal somatostatin interneurons). We demonstrate-in the spatial memory task, during memory recall-that theta power increases in left medial temporal lobe (mTL) are impaired in schizophrenia, as is theta phase coupling between mPFC and mTL. Importantly, the latter cannot be explained by theta power changes, head movement, antipsychotics, cannabis use, or IQ, and is not found in other frequency bands. Moreover, mPFC-mTL theta coupling correlated strongly with performance in controls, but not in subjects with schizophrenia, who were mildly impaired at the spatial memory task and no better than chance on the memory integration task. Finally, mTL regions showing reduced phase coupling in schizophrenia magnetoencephalography participants overlapped substantially with areas of diminished α5-GABAAR availability in the wider schizophrenia PET sample. These results indicate that mPFC-mTL dysconnectivity in schizophrenia is due to a loss of theta phase coupling, and imply α5-GABAARs (and the cells that express them) have a role in this process.

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.

Dynamic changes of brain networks during feedback-related processing of reinforcement learning in schizophrenia

Previous studies have reported that schizophrenia (SZ) patients showed selective reinforcement learning deficits and abnormal feedback-related event-related potential (ERP) components. However, how the brain networks and their topological properties evolve over time during transient feedback-related cognition processing in SZ patients has not been investigated so far. In this paper, using publicly available feedback-related ERP data which were recorded from SZ patients and healthy controls (HC) when they performed a reinforcement learning task, we carried out an event-related network analysis where topology of brain functional networks was characterized with some graph measures including clustering coefficient (C), global efficiency (E_global) and local efficiency (E_local) on a millisecond timescale. Our results showed that the brain functional networks displayed rapid rearrangements of topological properties during transient feedback-related cognition process for both two groups. More importantly, we found that SZ patients exhibited significantly reduced theta-band (time window of 170-350 ms after stimuli onset) brain functional connectivity strength, E_global, E_local and C in response to negative feedback stimuli compared to HC group. The network based statistic (NBS) analysis detected one significantly decreased theta-band subnetwork in SZ patients mainly involving in frontal-occipital and temporal-occipital connections compared to HC group. In addition, clozapine treatment seemed to greatly reduce theta-band power and topological measures of brain networks in SZ patients. Finally, the theta-band power, graph measures and functional connectivity were extracted to train a support vector machine classifier for classification of HC from SZ, or Cloz + SZ or Cloz- SZ, and a relatively good classification accuracy of 84.48%, 89.47% and 78.26% was obtained, respectively. The above results suggested a less optimal organization of theta-band brain network in SZ patients, and studying the topological parameters of brain networks evolve over time during transient feedback-related processing could be useful for understanding the pathophysiologic mechanisms underlying reinforcement learning deficits in SZ patients.

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

The Hierarchical Taxonomy of Psychopathology (HiTOP) is a scientific effort to address shortcomings of traditional mental disorder diagnoses, which suffer from arbitrary boundaries between psychopathology and normality, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. This paper synthesizes evidence on the validity and utility of the thought disorder and detachment spectra of HiTOP. These spectra are composed of symptoms and maladaptive traits currently subsumed within schizophrenia, other psychotic disorders, and schizotypal, paranoid and schizoid personality disorders. Thought disorder ranges from normal reality testing, to maladaptive trait psychoticism, to hallucinations and delusions. Detachment ranges from introversion, to maladaptive detachment, to blunted affect and avolition. Extensive evidence supports the validity of thought disorder and detachment spectra, as each spectrum reflects common genetics, environmental risk factors, childhood antecedents, cognitive abnormalities, neural alterations, biomarkers, and treatment response. Some of these characteristics are specific to one spectrum and others are shared, suggesting the existence of an overarching psychosis superspectrum. Further research is needed to extend this model, such as clarifying whether mania and dissociation belong to thought disorder, and explicating processes that drive development of the spectra and their subdimensions. Compared to traditional diagnoses, the thought disorder and detachment spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and higher acceptability to clinicians. Validated measures are available to implement the system in practice. The more informative, reliable and valid characterization of psychosis-related psychopathology offered by HiTOP can make diagnosis more useful for research and clinical care.

Clinical, behavioural and neural validation of the PANSS amotivation factor

Negative symptoms in schizophrenia have been suggested to map onto two distinct factors - amotivation and diminished expression. Only recently, two-factor solutions for measuring negative symptoms have been proposed for the Positive and Negative Symptom Scale (PANSS), the most commonly used scale to assess the psychopathology of patients with schizophrenia. We aimed to validate the PANSS two-factor structure on a clinical, behavioural and neural level. For this multi-level validation, we reanalysed several datasets with patients for whom both the Brief Negative Symptom Assessment Scale (BNSS) and PANSS data were collected. We used a clinical dataset (n = 120) as well as behavioural data from an effort-based decision making task (n = 31) and functional neuroimaging data from a monetary incentive delay task (n = 41). Both tasks have previously been shown to be associated with BNSS amotivation. On the clinical level, the PANSS amotivation and diminished expression were highly correlated with their BNSS counterparts. On the behavioural level, we found that the PANSS amotivation factor but not the diminished expression factor specifically associated with willingness to invest effort to obtain a reward. On the neural level, PANSS amotivation was specifically related to reduced ventral striatal activation during reward anticipation. Our data confirm that the PANSS clearly allows distinguishing amotivation from diminished expression, as it relates selectively to specific aspects of behaviour and brain function. Our results will allow a re-analysis and sharing of existing datasets that used the PANSS to further substantiate the distinction between the two factors in neuroscientific studies and clinical trials.

Retinal functioning and reward processing in schizophrenia

Retinal responses to light, as measured by electroretinography (ERG), have been shown to be reduced in schizophrenia. Data from a prior ERG study in healthy humans indicated that activity of a retinal cell type affected in schizophrenia can be modified by the presence of a food reward. Therefore, we aimed to determine whether ERG amplitudes would be sensitive to the well-documented reward processing impairment in schizophrenia. Flash ERG data from 15 clinically stable people with schizophrenia or schizoaffective disorder and 15 healthy controls were collected under three conditions: baseline, anticipation of a food reward, and immediately after consuming the food reward. At the group level, data indicated that controls' ERG responses varied as a function of salience of the food reward (baseline vs. anticipation vs. consumption) whereas patients' ERG responses did not vary significantly across conditions. Correlations between ERG amplitudes and scores on measures of hedonic capacity (including motivation and pleasure negative symptom ratings for patients) indicated consistent relationships. These data suggest that flash ERG amplitudes may be a sensitive indicator of the integrity of reward processing mechanisms. However, several differences in the direction of findings between this and a prior study in controls point to the need for further investigation of the contributions of a number of key variables to the observed effects.

The Topography of Striatal Dopamine and Symptoms in Psychosis: An Integrative Positron Emission Tomography and Magnetic Resonance Imaging Study

Background

Striatal dopamine dysfunction is thought to underlie symptoms in psychosis, yet it remains unclear how a single neurotransmitter could cause the diverse presentations that are observed clinically. One hypothesis is that the consequences of aberrant dopamine signaling vary depending on where within the striatum the dysfunction occurs. Positron emission tomography allows for the quantification of dopamine function across the striatum. In the current study, we used a novel method to investigate the relationship between spatial variability in dopamine synthesis capacity and psychotic symptoms.

Methods

We used a multimodal imaging approach combining ¹⁸F-DOPA positron emission tomography and resting-state magnetic resonance imaging in 29 patients with first-episode psychosis and 21 healthy control subjects. In each participant, resting-state functional connectivity maps were used to quantify the functional connectivity of each striatal voxel to well-established cortical networks. Network-specific striatal dopamine synthesis capacity (Ki^cer) was then calculated for the resulting connectivity-defined parcellations.

Results

The connectivity-defined parcellations generated Ki^cer values with equivalent reliability, and significantly greater orthogonality compared with standard anatomical parcellation methods. As a result, dopamine-symptom associations were significantly different from one another for different subdivisions, whereas no unique subdivision relationships were found when using an anatomical parcellation. In particular, dopamine function within striatal areas connected to the default mode network was strongly associated with negative symptoms (p < .001).

Conclusions

These findings suggest that individual differences in the topography of dopamine dysfunction within the striatum contribute to shaping psychotic symptomatology. Further validation of the novel approach in future studies is necessary.

Striatal Dopamine and Reward Prediction Error Signaling in Unmedicated Schizophrenia Patients

Increased striatal dopamine synthesis capacity has consistently been reported in patients with schizophrenia. However, the mechanism translating this into behavior and symptoms remains unclear. It has been proposed that heightened striatal dopamine may blunt dopaminergic reward prediction error signaling during reinforcement learning. In this study, we investigated striatal dopamine synthesis capacity, reward prediction errors, and their association in unmedicated schizophrenia patients (n = 19) and healthy controls (n = 23). They took part in FDOPA-PET and underwent functional magnetic resonance imaging (fMRI) scanning, where they performed a reversal-learning paradigm. The groups were compared regarding dopamine synthesis capacity (Kicer), fMRI neural prediction error signals, and the correlation of both. Patients did not differ from controls with respect to striatal Kicer. Taking into account, comorbid alcohol abuse revealed that patients without such abuse showed elevated Kicer in the associative striatum, while those with abuse did not differ from controls. Comparing all patients to controls, patients performed worse during reversal learning and displayed reduced prediction error signaling in the ventral striatum. In controls, Kicer in the limbic striatum correlated with higher reward prediction error signaling, while there was no significant association in patients. Kicer in the associative striatum correlated with higher positive symptoms and blunted reward prediction error signaling was associated with negative symptoms. Our results suggest a dissociation between striatal subregions and symptom domains, with elevated dopamine synthesis capacity in the associative striatum contributing to positive symptoms while blunted prediction error signaling in the ventral striatum related to negative symptoms.

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.

Driven by Pain, Not Gain: Computational Approaches to Aversion-Related Decision Making in Psychiatry

Although it is well known that "losses loom larger than gains," computational approaches to aversion-related decision making (ARDM) for psychiatric disorders is an underdeveloped area. Computational models of ARDM have been implemented primarily as state-dependent reinforcement learning models with bias parameters to quantify Pavlovian associations, and differential learning rates to quantify instrumental updating have been shown to depend on context, involve complex cost calculations, and include the consideration of counterfactual outcomes. Little is known about how individual differences influence these models relevant to anxiety-related conditions or addiction-related dysfunction. It is argued that model parameters reflecting 1) Pavlovian biases in the context of reinforcement learning or 2) hyperprecise prior beliefs in the context of active inference play an important role in the emergence of dysfunctional avoidance behaviors. The neural implementation of ARDM includes brain areas that are important for valuation (ventromedial prefrontal cortex) and positive reinforcement-related prediction errors (ventral striatum), but also aversive processing (insular cortex and cerebellum). Computational models of ARDM will help to establish a quantitative explanatory account of the development of anxiety disorders and addiction, but such models also face several challenges, including limited evidence for stability of individual differences, relatively low reliability of tasks, and disorder heterogeneity. Thus, it will be necessary to develop robust, reliable, and model-based experimental probes; recruit larger sample sizes; and use single case experimental designs for better pragmatic and explanatory biological models of psychiatric disorders.

Trust and the city: Linking urban upbringing to neural mechanisms of trust in psychosis

OBJECTIVE

Elevated prevalence of non-affective psychotic disorders is often found in densely populated areas. This functional magnetic resonance imaging study investigates if reduced trust, a component of impaired social functioning in patients with psychotic disorder, is associated with urban upbringing.

METHODS

In total, 39 patients (22 first episode and 17 clinical high risk) and 30 healthy controls, aged 16-29, performed two multi-round trust games, with a cooperative and unfair partner during functional magnetic resonance imaging scanning. Baseline trust was operationalized as the first investment made, and changes of trust as changes in investments made over the 20 trials during the games. Urban exposure during upbringing (0-15 years) was defined as higher urban (≥2500 inhabitants/km²) or lower urban (<2500 inhabitants/km²).

RESULTS

Patients displayed lower baseline trust (first investment) than controls, regardless of urbanicity exposure. During cooperative interactions, lower-urban patients showed increasing investments. In addition, during cooperative interactions, group-by-developmental urbanicity interactions were found in the right and left amygdalae, although for the latter only at trend level. Higher urbanicity was associated with decreased activation of the left amygdala in patients and controls during investments and with increased activation of the right and left amygdalae in patients only, during repayments. During unfair interactions, no associations of urbanicity with behavior or brain activation were found.

CONCLUSION

Urban upbringing was unrelated to baseline trust. Associations with urbanicity were stronger for patients compared to controls, suggesting greater susceptibility to urbanicity effects during the developmental period. Higher-urban patients failed to compensate for the initial distrust specifically during repeated cooperative interactions. This finding highlights potential implications for social functioning. Urban upbringing was linked to differential amygdala activation, suggesting altered mechanisms of feedback learning, but this was not associated with trust game behavior.

Dopamine and glutamate in schizophrenia: biology, symptoms and treatment

Glutamate and dopamine systems play distinct roles in terms of neuronal signalling, yet both have been proposed to contribute significantly to the pathophysiology of schizophrenia. In this paper we assess research that has implicated both systems in the aetiology of this disorder. We examine evidence from post-mortem, preclinical, pharmacological and in vivo neuroimaging studies. Pharmacological and preclinical studies implicate both systems, and in vivo imaging of the dopamine system has consistently identified elevated striatal dopamine synthesis and release capacity in schizophrenia. Imaging of the glutamate system and other aspects of research on the dopamine system have produced less consistent findings, potentially due to methodological limitations and the heterogeneity of the disorder. Converging evidence indicates that genetic and environmental risk factors for schizophrenia underlie disruption of glutamatergic and dopaminergic function. However, while genetic influences may directly underlie glutamatergic dysfunction, few genetic risk variants directly implicate the dopamine system, indicating that aberrant dopamine signalling is likely to be predominantly due to other factors. We discuss the neural circuits through which the two systems interact, and how their disruption may cause psychotic symptoms. We also discuss mechanisms through which existing treatments operate, and how recent research has highlighted opportunities for the development of novel pharmacological therapies. Finally, we consider outstanding questions for the field, including what remains unknown regarding the nature of glutamate and dopamine function in schizophrenia, and what needs to be achieved to make progress in developing new treatments.

Cognition and Reward Circuits in Schizophrenia: Synergistic, Not Separate

Schizophrenia has been studied from the perspective of cognitive or reward-related impairments, yet it cannot be wholly related to one or the other process and their corresponding neural circuits. We posit a comprehensive circuit-based model proposing that dysfunctional interactions between the brain's cognitive and reward circuits underlie schizophrenia. The model is underpinned by how the relationship between glutamatergic and dopaminergic dysfunction in schizophrenia drives interactions between cognition and reward circuits. We argue that this interaction is synergistic: that is, deficits of cognition and reward processing interact, and this interaction is a core feature of schizophrenia. In adopting this position, we undertake a focused review of animal physiology and human clinical data, and in proposing this synergistic model, we highlight dopaminergic afferents from the ventral tegmental area to nucleus accumbens (mesolimbic circuit) and frontal cortex (mesocortical circuit). We then expand on the role of glutamatergic inputs to these dopamine circuits and dopaminergic modulation of critical excitatory pathways with attention given to the role of glutamatergic hippocampal outputs onto nucleus accumbens. Finally, we present evidence for how in schizophrenia, dysfunction in the mesolimbic and mesocortical circuits and their corresponding glutamatergic inputs gives rise to clinical and cognitive phenotypes and is associated with positive and negative symptom dimensions. The synthesis attempted here provides an impetus for a conceptual shift that links cognitive and motivational aspects of schizophrenia and that can lead to treatment approaches that seek to harmonize network interactions between the brain's cognition and reward circuits with ameliorative effects in each behavioral domain.

Are Negative Symptoms Merely the "Real World" Consequences of Deficits in Social Cognition?

Many investigations have demonstrated that negative symptoms and social cognitive deficits in schizophrenia play a large role in determining functional outcomes and ultimately long-term prognosis. Given this, there is increasing interest in understanding the relationship between these two symptom domains, particularly since studies have consistently found moderate to large associations between them. This shared variance raises a key question: to what degree do these two categories of symptoms arise from overlapping or identical changes in brain function? In other words, do some or all negative symptoms represent merely the downstream effects of social cognition deficits on daily functioning? In this commentary, the evidence for and against this possibility, limitations of currently validated empirical measurements of these symptoms, and directions for further investigation of this hypothesis are discussed. Understanding the shared and distinct mechanisms of these disabling deficits will have important implications for the design of novel, personalized treatments for psychotic illness.

Striato-nigro-striatal tract dispersion abnormalities in patients with chronic schizophrenia

The white matter connections between the midbrain dopamine neurons and the striatum are part of a neural system involved in reward-based learning, a process that is impaired in patients with schizophrenia. The striato-nigro-striatal (SNS) tract, which participates in this process, has not as yet been explored. The present study aimed to use diffusion MRI (dMRI) to delineate the SNS tract, and to compare the application of two dMRI measures, Tract Dispersion (TD), an index of white matter morphology, and Fractional Anisotropy (FA), an index of white matter integrity, to detect group differences between patients with chronic schizophrenia (CSZ) and healthy controls (HC). dMRI scans were acquired in 22 male patients with CSZ and 23 age-matched HC. Two-tensor tractography was used in addition to manually-delineated regions of interest to extract the SNS tract. A mixed-model analysis of variance was used to investigate differences in TD and FA between CSZ patients and HC. The associations between TD and behavioral measures were also explored. Patients and controls differed significantly in TD (P = 0.04), but not in FA (P = 0.69). The group differences in TD were driven by a higher TD in the right hemisphere in the CSZ group. Higher TD correlated significantly with poorer performance in the Iowa Gambling Task (IGT) when combining the scores of both groups. The findings suggest that dysconnectiviy of the SNS tract which is associated with schizophrenia, could arise from abnormalities in white matter morphology. These abnormalities may potentially reflect irregularities in brain development.

Efficacy of Acceptance and Commitment Therapy in Daily Life (ACT-DL) in early psychosis: study protocol for a multi-centre randomized controlled trial

Background

Psychotic experiences, social functioning and general psychopathology are important targets for early intervention in individuals with Ultra-High-Risk state (UHR) and a first-episode psychosis (FEP). Acceptance and Commitment Therapy (ACT) is a promising, next-generation Cognitive Behavioural Therapy (CBT) that aims to modify these targets, but evidence on sustainable change and its underlying mechanisms in individuals’ daily lives remains limited. The aim of the INTERACT study is to investigate the efficacy of a novel ecological momentary intervention, Acceptance and Commitment Therapy in Daily Life (ACT-DL) in a multi-centre randomised controlled trial of individuals with UHR or FEP.

Methods/design

In a multi-centre randomised controlled trial, individuals aged 16–65 years with UHR or FEP will be randomly allocated to ACT-DL in addition to treatment as usual (TAU) as the experimental condition or a control condition of TAU only, which will include – for the entire study period – access to routine mental health care and, where applicable, CBT for psychosis (CBTp). Outcomes will be assessed at baseline (i.e. before randomisation), post-intervention (i.e. after the 8-week intervention period), and 6-month and 12-month follow-ups (i.e. 6 and 12 months after completing the intervention period) by blinded assessors. The primary outcome will be distress associated with psychotic experiences, while secondary outcomes will include (momentary) psychotic experiences, social functioning and psychopathology. Process measures to assess putative mechanisms of change will include psychological flexibility, stress sensitivity and reward experiences. In addition, acceptability, treatment adherence and treatment fidelity of ACT-DL will be assessed.

Discussion

The current study is the first to test the efficacy of ACT-DL in individuals with UHR and FEP. If this trial demonstrates the efficacy of ACT-DL, it has the potential to significantly advance the treatment of people with UHR and FEP and, more generally, provides initial support for implementing mHealth interventions in mental health services.

Trial registration

Netherlands Trial Register, ID: NTR4252. Registered on 26 September 2013.

Motivational deficits in schizophrenia relate to abnormalities in cortical learning rate signals

Individuals from across the psychosis spectrum display impairments in reinforcement learning. In some individuals, these deficits may result from aberrations in reward prediction error (RPE) signaling, conveyed by dopaminergic projections to the ventral striatum (VS). However, there is mounting evidence that VS RPE signals are relatively intact in medicated people with schizophrenia (PSZ). We hypothesized that, in PSZ, reinforcement learning deficits often are not related to RPE signaling per se but rather their impact on learning and behavior (i.e., learning rate modulation), due to dysfunction in anterior cingulate and dorsomedial prefrontal cortex (dmPFC). Twenty-six PSZ and 23 healthy volunteers completed a probabilistic reinforcement learning paradigm with occasional, sudden, shifts in contingencies. Using computational modeling, we found evidence of an impairment in trial-wise learning rate modulation (α) in PSZ before and after a reinforcement contingency shift, expressed most in PSZ with more severe motivational deficits. In a subsample of 22 PSZ and 22 healthy volunteers, we found little evidence for between-group differences in VS RPE and dmPFC learning rate signals, as measured with fMRI. However, a follow-up psychophysiological interaction analysis revealed decreased dmPFC-VS connectivity concurrent with learning rate modulation, most prominently in individuals with the most severe motivational deficits. These findings point to an impairment in learning rate modulation in PSZ, leading to a reduced ability to adjust task behavior in response to unexpected outcomes. At the level of the brain, learning rate modulation deficits may be associated with decreased involvement of the dmPFC within a greater RL network.

Predictive Modulation of Corticospinal Excitability and Implicit Encoding of Movement Probability in Schizophrenia

The ability to infer from uncertain information is impaired in schizophrenia and is associated with hallucinations and false beliefs. The accumulation of information is a key process for generating a predictive internal model, which statistically estimates an outcome from a specific situation. This study examines if updating the predictive model by the accumulation of information in absence of feedback is impaired in schizophrenia. We explored the implicit adaptation to the probability of being instructed to perform a movement (33%-Go, 50%-Go, or 66%-Go) in a Go/NoGo task in terms of reaction times (RTs), electromyographic activity, and corticospinal excitability (CSE) of primary motor cortex (M1). CSE was assessed at two time points to evaluate prediction of the upcoming instruction based on previously accumulated information: at rest (preceding the warning signal) and at the Go/NoGo signal onset. Three groups were compared: patients with schizophrenia (n = 20), unaffected siblings (n = 16), and healthy controls (n = 20). Controls and siblings showed earlier movement onset and increased CSE with higher Go probability. CSE adaptation seemed long-lasting, because the two CSE measures, at least 1500 ms apart, strongly correlated. Patients with schizophrenia failed to show movement onset (RT) adaptation and modulation of CSE. In contrast, all groups decreased movement duration with increasing Go probability. Modulation of CSE in the anticipatory phase of the potential movement reflected the estimation of upcoming response probability in unaffected controls and siblings. Impaired modulation of CSE supports the hypothesis that implicit adaptation to probabilistic context is altered in schizophrenia.

From laboratory to life: associating brain reward processing with real-life motivated behaviour and symptoms of depression in non-help-seeking young adults

BACKGROUND

Depression has been associated with abnormalities in neural underpinnings of Reward Learning (RL). However, inconsistencies have emerged, possibly owing to medication effects. Additionally, it remains unclear how neural RL signals relate to real-life behaviour. The current study, therefore, examined neural RL signals in young, mildly to moderately depressed - but non-help-seeking and unmedicated - individuals and how these signals are associated with depressive symptoms and real-life motivated behaviour.

METHODS

Individuals with symptoms along the depression continuum (n = 87) were recruited from the community. They performed an RL task during functional Magnetic Resonance Imaging and were assessed with the Experience Sampling Method (ESM), completing short questionnaires on emotions and behaviours up to 10 times/day for 15 days. Q-learning model-derived Reward Prediction Errors (RPEs) were examined in striatal areas, and subsequently associated with depressive symptoms and an ESM measure capturing (non-linearly) how anticipation of reward experience corresponds to actual reward experience later on.

RESULTS

Significant RPE signals were found in the striatum, insula, amygdala, hippocampus, frontal and occipital cortices. Region-of-interest analyses revealed a significant association between RPE signals and (a) self-reported depressive symptoms in the right nucleus accumbens (b = -0.017, p = 0.006) and putamen (b = -0.013, p = .012); and (b) the quadratic ESM variable in the left (b = 0.010, p = .010) and right (b = 0.026, p = 0.011) nucleus accumbens and right putamen (b = 0.047, p < 0.001).

CONCLUSIONS

Striatal RPE signals are disrupted along the depression continuum. Moreover, they are associated with reward-related behaviour in real-life, suggesting that real-life coupling of reward anticipation and engagement in rewarding activities might be a relevant target of psychological therapies for depression.

From neuroimaging to daily functioning: A multimethod analysis of reward anticipation in people with schizophrenia

Negative symptoms are a core clinical feature of schizophrenia that are only marginally responsive to current treatments. Recent work suggests that deficits in reinforcement learning and anticipatory responses to reward may be two mechanisms that help explain impairments in motivation in those with schizophrenia. The present study utilized a reinforcement-learning paradigm, which allowed us to examine both reward anticipation and reinforcement learning. Twenty-eight people with schizophrenia and 30 healthy controls completed a reinforcement-learning task while undergoing functional MRI. Participants with schizophrenia also completed a weeklong ecological momentary assessment protocol reporting anticipated motivation and pleasure in their daily activities. Unexpectedly, we found no significant group differences in performance or neural response in reinforcement learning. However, we found that poorer reward learning was associated with greater clinician ratings of negative symptoms and daily reports of anticipatory motivation and pleasure negative symptoms. In regards to anticipatory responses, we found that people with schizophrenia showed blunted activation in the anterior cingulate, insula, caudate, and putamen while anticipating reward. Further, blood oxygen level-dependent (BOLD) response in reward related regions during anticipation of reward was significantly related to both clinician-rated motivation and pleasure deficits as well as daily reports of motivation and pleasure. Our results provide further evidence of deficits during reward anticipation in individuals with schizophrenia, particularly for those with severe negative symptoms, and some evidence for worse reward learning among those with greater negative symptoms. Moreover, our findings suggest that these deficits show important relationships with emotional and motivational functioning in everyday life. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Impact of long-term institutionalization on experiential pleasure and motivation in patients with schizophrenia

Anhedonia and amotivation, the hallmarks of negative symptoms in schizophrenia, are believed to be due to "emotion-behavior decoupling," a failure in translating pleasure experience into appropriate goal-directed behavior. A number of studies have reported that long-term institutionalized schizophrenia patients suffer from more severe negative symptoms than community-dwelling patients, but few studies have investigated pleasure experience and motivational behavior in schizophrenia patients who have experienced long-term institutionalization. In this study, we recruited 26 long-term institutionalized schizophrenia patients, 27 community-dwelling schizophrenia patients, and 27 healthy controls. Participants were administered two specific computer-based tasks to assess anhedonia and amotivation. The Anticipatory and Consummatory Pleasure (ACP) Task was used to measure emotion-behavior decoupling and the Effort-Expenditure for Rewards Task (EEfRT) was used to measure amotivation related to rewards. Findings from the ACP Task showed that compared with healthy controls, the coupling between emotion experience and motivated behavior was significantly weaker in both clinical groups, suggesting that emotion-behavior decoupling could be a stable trait in schizophrenia patients. In the EEfRT, compared with both community-dwelling patients and healthy controls, institutionalized patients with schizophrenia failed to expend more effort to gain potential rewards even when reward probability increased. These findings further reveal the underlying mechanism of anhedonia and amotivation and their potential relationships with long-term institutionalization in patients with schizophrenia.