Evidence of reward system dysfunction in youth at clinical high-risk for psychosis from two event-related fMRI paradigms

Global reward processing deficits predict negative symptoms transdiagnostically and transphasically in a severe mental illness-spectrum sample

Reward processing impairments are a key factor associated with negative symptoms in those with severe mental illnesses. However, past findings are inconsistent regarding which reward processing components are impaired and most strongly linked to negative symptoms. The current study examined the hypothesis that these mixed findings may be the result of multiple reward processing pathways (i.e., equifinality) to negative symptoms that cut across diagnostic boundaries and phases of illness. Participants included healthy controls (n = 100) who served as a reference sample and a severe mental illness-spectrum sample (n = 92) that included psychotic-like experiences, clinical high-risk for psychosis, bipolar disorder, and schizophrenia participants. All participants completed tasks measuring four RDoC Positive Valence System constructs: value representation, reinforcement learning, effort-cost computation, and hedonic reactivity. A k-means cluster analysis of the severe mental illness-spectrum samples identified three clusters with differential reward processing profiles that were characterized by: (1) global reward processing deficits (22.8%), (2) selective impairments in hedonic reactivity alone (40.2%), and (3) preserved reward processing (37%). Elevated negative symptoms were only observed in the global reward processing cluster. All clusters contained participants from each clinical group, and the distribution of these groups did not significantly differ among the clusters. Findings identified one pathway contributing to negative symptoms that was transdiagnostic and transphasic. Future work further characterizing divergent pathways to negative symptoms may help to improve symptom trajectories and personalized treatments.

Diminished differentiation of rewards in individuals at clinical high-risk for psychosis

Reward processing is impaired in people with schizophrenia, which may begin in the clinical high-risk (CHR) for psychosis period. The Monetary Incentive Delay (MID) task has been important in understanding the neural correlates of reward processing deficits in various psychiatric disorders. Previous research has found that CHR individuals have an imprecise mental representation of rewards, which leads to a diminished differentiation between rewards, though this has not been observed behaviorally. A total of 19 CHR individuals and 20 controls were given a novel variant of the MID task, designed to examine how modulating reward context may impact responses to reward cues, a process often referred to as "adaptive coding." Both groups appeared to update their behavior in response to the rewards available in this adaptive task. However, when compared to controls who showed a more graded decrease in response time to increasing reward contexts, CHR individuals appeared to have a sharp decrease in response time in the low reward context that is nearly stable across higher reward contexts. This is largely driven by the exponential component of the response time distribution, which is often interpreted to be more cognitively or effortfully influenced. Response times are related to negative symptoms, but not positive symptoms, disorganized symptoms, or estimated intelligence. Although an adaptive coding effect was not observed, these results provide novel insight into the reward processing mechanisms and volitional processes in the CHR population, as this was the first study to observe the diminished differentiation of rewards behaviorally.

Sleep deprivation attenuates neural responses to outcomes from risky decision-making

Sleep loss impacts a broad range of brain and cognitive functions. However, how sleep deprivation affects risky decision-making remains inconclusive. This study used functional MRI to examine the impact of one night of total sleep deprivation (TSD) on risky decision-making behavior and the underlying brain responses in healthy adults. In this study, we analyzed data from N = 56 participants in a strictly controlled 5-day and 4-night in-laboratory study using a modified Balloon Analogue Risk Task. Participants completed two scan sessions in counter-balanced order, including one scan during rested wakefulness (RW) and another scan after one night of TSD. Results showed no differences in participants' risk-taking propensity and risk-induced activation between RW and TSD. However, participants showed significantly reduced neural activity in the anterior cingulate cortex and bilateral insula for loss outcomes, and in bilateral putamen for win outcomes during TSD compared with RW. Moreover, risk-induced activation in the insula negatively correlated with participants' risk-taking propensity during RW, while no such correlations were observed after TSD. These findings suggest that sleep loss may impact risky decision-making by attenuating neural responses to decision outcomes and impairing brain-behavior associations.

Environmental context predicts state fluctuations in negative symptoms in youth at clinical high risk for psychosis

BACKGROUND

Negative symptoms (avolition, anhedonia, asociality) are a prevalent symptom in those across the psychosis-spectrum and also occur at subclinical levels in the general population. Recent work has begun to examine how environmental contexts (e.g. locations) influence negative symptoms. However, limited work has evaluated how environments may contribute to negative symptoms among youth at clinical high risk for psychosis (CHR). The current study uses Ecological Momentary Assessment to assess how four environmental contexts (locations, activities, social interactions, social interaction method) impact state fluctuations in negative symptoms in CHR and healthy control (CN) participants.

METHODS

CHR youth (n = 116) and CN (n = 61) completed 8 daily surveys for 6 days assessing negative symptoms and contexts.

RESULTS

Mixed-effects modeling demonstrated that negative symptoms largely varied across contexts in both groups. CHR participants had higher negative symptoms than CN participants in most contexts, but groups had similar symptom reductions during recreational activities and phone call interactions. Among CHR participants, negative symptoms were elevated in several contexts, including studying/working, commuting, eating, running errands, and being at home.

CONCLUSIONS

Results demonstrate that negative symptoms dynamically change across some contexts in CHR participants. Negative symptoms were more intact in some contexts, while other contexts, notably some used to promote functional recovery, may exacerbate negative symptoms in CHR. Findings suggest that environmental factors should be considered when understanding state fluctuations in negative symptoms among those at CHR participants.

Reinforcement learning profiles and negative symptoms across chronic and clinical high-risk phases of psychotic illness

Negative symptoms are prominent in individuals with schizophrenia (SZ) and youth at clinical high-risk for psychosis (CHR). In SZ, negative symptoms are linked to reinforcement learning (RL) dysfunction; however, previous research suggests implicit RL remains intact. It is unknown whether implicit RL is preserved in the CHR phase where negative symptom mechanisms are unclear, knowledge of which may assist in developing early identification and prevention methods. Participants from two studies completed an implicit RL task: Study 1 included 53 SZ individuals and 54 healthy controls (HC); Study 2 included 26 CHR youth and 23 HCs. Bias trajectories reflecting implicit RL were compared between groups and correlations with negative symptoms were examined. Cluster analysis investigated RL profiles across the combined samples. Implicit RL was comparable between HC and their corresponding SZ and CHR groups. However, cluster analysis was able to parse performance heterogeneity across diagnostic boundaries into two distinct RL profiles: a Positive/Early Learning cluster (65% of participants) with positive bias scores increasing from the first to second task block, and a Negative/Late Learning cluster (35% of participants) with negative bias scores increasing from the second to third block. Clusters did not differ in the proportion of CHR vs. SZ cases; however, the Negative/Late Learning cluster had more severe negative symptoms. Although implicit RL is intact in CHR similar to SZ, distinct implicit RL phenotypic profiles with elevated negative symptoms were identified trans-phasically, suggesting distinct reward-processing mechanisms can contribute to negative symptoms independent of phases of illness.

In Context: A Developmental Model of Reward Processing, With Implications for Autism and Sensitive Periods

OBJECTIVE

Differences in reward processing have been associated with numerous psychiatric disorders, including autism and attention-deficit/hyperactivity disorder (ADHD). Many attempts to understand reward processing characterize differences in clinical populations after disorder onset; however, divergence may begin much earlier. In fact, the typical developmental progression of reward processing in infancy and early childhood is poorly understood. We re-conceptualize classic infant developmental constructs such as preferential looking into a Six-Component Developmental Model of Reward Processing: an infant- and young child-focused framework to guide research and assessment of reward processing across development.

METHOD

The extant developmental literature including recent textbooks, systematic reviews, and meta-analyses was reviewed to build a conceptual framework. We describe experimental paradigms to assess each developmental component of reward processing longitudinally from infancy. A timeline of each component's emergence was estimated.

RESULTS

Six components of reward processing were identified-association, discrimination, preference/valuation, effort, anticipation, and response. Selected evidence suggests emergence between birth and 6 months. Application of this model to autism led to a reinterpretation of existing disparate results, and illuminated a path to study the developmental processes underlying a popular hypothesis of autism, the motivation hypothesis. Current evidence further suggests that a sensitive period may exist for the emergence of reward processing.

CONCLUSION

The proposed framework offers a useful reconceptualization of the extant literature. Future longitudinal work using the suggested experimental paradigms with high-risk populations could elucidate the developmental trajectory of the components and timing of potential sensitive period(s) for each component.

Action selection in early stages of psychosis: an active inference approach

BACKGROUND

To interact successfully with their environment, humans need to build a model to make sense of noisy and ambiguous inputs. An inaccurate model, as suggested to be the case for people with psychosis, disturbs optimal action selection. Recent computational models, such as active inference, have emphasized the importance of action selection, treating it as a key part of the inferential process. Based on an active inference framework, we sought to evaluate previous knowledge and belief precision in an action-based task, given that alterations in these parameters have been linked to the development of psychotic symptoms. We further sought to determine whether task performance and modelling parameters would be suitable for classification of patients and controls.

METHODS

Twenty-three individuals with an at-risk mental state, 26 patients with first-episode psychosis and 31 controls completed a probabilistic task in which action choice (go/no-go) was dissociated from outcome valence (gain or loss). We evaluated group differences in performance and active inference model parameters and performed receiver operating characteristic (ROC) analyses to assess group classification.

RESULTS

We found reduced overall performance in patients with psychosis. Active inference modelling revealed that patients showed increased forgetting, reduced confidence in policy selection and less optimal general choice behaviour, with poorer action-state associations. Importantly, ROC analysis showed fair-to-good classification performance for all groups, when combining modelling parameters and performance measures.

LIMITATIONS

The sample size is moderate.

CONCLUSION

Active inference modelling of this task provides further explanation for dysfunctional mechanisms underlying decision-making in psychosis and may be relevant for future research on the development of biomarkers for early identification of psychosis.

"Wanting" versus "needing" related value: An fMRI meta-analysis

Consumption and its excesses are sometimes explained by imbalance of need or lack of control over "wanting." "Wanting" assigns value to cues that predict rewards, whereas "needing" assigns value to biologically significant stimuli that one is deprived of. Here we aimed at studying how the brain activation patterns related to value of "wanted" stimuli differs from that of "needed" stimuli using activation likelihood estimation neuroimaging meta-analysis approaches. We used the perception of a cue predicting a reward for "wanting" related value and the perception of food stimuli in a hungry state as a model for "needing" related value. We carried out separate, contrasts, and conjunction meta-analyses to identify differences and similarities between "wanting" and "needing" values. Our overall results for "wanting" related value show consistent activation of the ventral tegmental area, striatum, and pallidum, regions that both activate behavior and direct choice, while for "needing" related value, we found an overall consistent activation of the middle insula and to some extent the caudal-ventral putamen, regions that only direct choice. Our study suggests that wanting has more control on consumption and behavioral activation.

The impact of the COVID-19 pandemic on negative symptoms in individuals at clinical high-risk for psychosis and outpatients with chronic schizophrenia

Negative symptoms are core features of schizophrenia-spectrum disorders that are frequently observed across all phases of illness. By their nature, COVID-19 social isolation, physical distancing, and health precautions induce behavioural aspects of negative symptoms. However, it is unclear whether these prevention measures also lead to increases in experiential negative symptoms, whether such effects are equivalent across individual negative symptom domains, and if exacerbations occur equivalently across phases of illness. The current study compared negative symptom severity scores obtained during the pandemic to pre-pandemic assessments in two samples: (1) outpatients with chronic schizophrenia (SZ: n = 32) and matched healthy controls (CN: n = 31) and (2) individuals at clinical high risk for psychosis (CHR: n = 25) and matched CN (n = 30). Pre-pandemic ratings of negative symptoms were clinically elevated in SZ and CHR groups, which did not differ from each other in severity. In SZ, ratings obtained during the pandemic were significantly higher than pre-pandemic ratings for all 5 domains (alogia, blunted affect, anhedonia, avolition, and asociality) and item-level analyses indicated that exacerbations occurred on both experiential and behavioral symptoms of anhedonia, avolition, and asociality. In contrast, CHR only exhibited increases in anhedonia and avolition items during the pandemic compared to pre-ratings. Findings suggest that negative symptoms should be a critical treatment target during and after the pandemic in the schizophrenia spectrum given that they are worsening and critically related to risk for conversion, functional outcome, and recovery.

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.

Neural Circuitry of Salience and Reward Processing in Psychosis

The processing of salient and rewarding stimuli is integral to engaging our attention, stimulating anticipation for future events, and driving goal-directed behaviors. Widespread impairments in these processes are observed in psychosis, which may be associated with worse functional outcomes or mechanistically linked to the development of symptoms. Here, we summarize the current knowledge of behavioral and functional neuroimaging in salience, prediction error, and reward. Although each is a specific process, they are situated in multiple feedback and feedforward systems integral to decision making and cognition more generally. We argue that the origin of salience and reward processing dysfunctions may be centered in the subcortex during the earliest stages of psychosis, with cortical abnormalities being initially more spared but becoming more prominent in established psychotic illness/schizophrenia. The neural circuits underpinning salience and reward processing may provide targets for delaying or preventing progressive behavioral and neurobiological decline.

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.

Brain reward circuitry: The overlapping neurobiology of trauma and substance use disorders

Mental health symptoms secondary to trauma exposure and substance use disorders (SUDs) co-occur frequently in both clinical and community samples. The possibility of a shared aetiology remains an important question in translational neuroscience. Advancements in genetics, basic science, and neuroimaging have led to an improved understanding of the neural basis of these disorders, their frequent comorbidity and high rates of relapse remain a clinical challenge. This project aimed to conduct a review of the field's current understanding regarding the neural circuitry underlying posttraumatic stress disorder and SUD. A comprehensive review was conducted of available published literature regarding the shared neurobiology of these disorders, and is summarized in detail, including evidence from both animal and clinical studies. Upon summarizing the relevant literature, this review puts forth a hypothesis related to their shared neurobiology within the context of fear processing and reward cues. It provides an overview of brain reward circuitry and its relation to the neurobiology, symptomology, and phenomenology of trauma and substance use. This review provides clinical insights and implications of the proposed theory, including the potential development of novel pharmacological and therapeutic treatments to address this shared neurobiology. Limitations and extensions of this theory are discussed to provide future directions and insights for this shared phenomena.

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.

A Bioecosystem Theory of Negative Symptoms in Schizophrenia

Objective: Negative symptoms are a core feature of schizophrenia that has been linked to numerous poor clinical outcomes. Although person-level mechanisms have been identified for negative symptoms, psychosocial and pharmacological treatments targeting these mechanisms have been ineffective. The current theoretical paper proposes that limited treatment progress may result in part from a failure to identify and target environmental processes that cause and maintain negative symptoms. Methods: A novel theoretical model is outlined, called the bioecosystem theory of negative symptoms, that offers a conceptual framework for studying interactions among environmental systems and person-related biological and psychosocial factors. Results: Relying on Bronfenbrenner's developmental theory as an organizing framework, four interactive environmental systems are proposed to be critical for the genesis and maintenance of negative symptoms: (1) Microsystem: the immediate environment; (2) Mesosystem: the interactions among microsystems; (3) Exosystem: indirect environments that influence the individual through the microsystems; (4) Macrosystem: socio-cultural factors. The environmental factors within these systems are proposed to function as a network and have dynamic within-system interactions, as well as cross-system interactions that change over time and across phases of illness. Conclusions: Environmental contributions to negative symptoms have received minimal empirical attention, despite their potential to explain variance in negative symptom severity. The bioecosystem model of negative symptoms introduced here offers a novel conceptual framework for exploring environmental contributions to negative symptoms and their interaction with person-level biological and psychological factors. This theory may facilitate new avenues for identifying environmental treatment targets and novel systems-level interventions.

Aberrant Salience, Information Processing, and Dopaminergic Signaling in People at Clinical High Risk for Psychosis

The aberrant salience hypothesis proposes that striatal dopamine dysregulation causes misattribution of salience to irrelevant stimuli leading to psychosis. Recently, new lines of preclinical evidence on information coding by subcortical dopamine coupled with computational models of the brain's ability to predict and make inferences about the world (predictive processing) provide a new perspective on this hypothesis. We review these and summarize the evidence for dopamine dysfunction, reward processing, and salience abnormalities in people at clinical high risk of psychosis (CHR) relative to findings in patients with psychosis. This review identifies consistent evidence for dysregulated subcortical dopamine function in people at CHR, but also indicates a number of areas where neurobiological processes are different in CHR subjects relative to patients with psychosis, particularly in reward processing. We then consider how predictive processing models may explain psychotic symptoms in terms of alterations in prediction error and precision signaling using Bayesian approaches. We also review the potential role of environmental risk factors, particularly early adverse life experiences, in influencing the prior expectations that individuals have about their world in terms of computational models of the progression from being at CHR to frank psychosis. We identify a number of key outstanding questions, including the relative roles of prediction error or precision signaling in the development of symptoms and the mechanism underlying dopamine dysfunction. Finally, we discuss how the integration of computational psychiatry with biological investigation may inform the treatment for people at CHR of psychosis.

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.

Striatum-related functional activation during reward- versus punishment-based learning in psychosis risk

Psychosis is strongly related to increased striatal dopamine. However, the neural consequences of increased striatal dopamine in psychosis risk are still not fully understood. Consistent with an increase in striatal dopamine, in previous research, psychosis risk has been associated with neural EEG evidence of a greater response to unexpected reward than unexpected punishment feedback on a reversal-learning task. However, previous research has not directly examined whether psychosis risk is associated with altered striatal activation when receiving unexpected feedback on this task. There were two groups of participants: an antipsychotic medication-naive psychosis risk group (n = 21) who had both (a) extreme levels of self-reported psychotic-like beliefs and experiences and (b) interview-rated current-attenuated psychotic symptoms; and a comparison group (n = 20) who had average levels of self-reported psychotic-like beliefs and experiences. Participants completed a reversal-leaning task during fMRI scanning. As expected, in both ROI and whole-brain analyses, the psychosis risk group exhibited greater striatal activation (for whole-brain analyses, the peak was located in the right caudate) to unexpected reward than unexpected punishment feedback relative to the comparison group. These results indicate that psychosis risk is associated with a relatively increased neural sensitivity to unexpected reward than unexpected punishment outcomes and appears consistent with increased striatal dopamine. The results may help us better understand and detect striatal dysfunction in psychosis risk.