Impaired reward prediction error encoding and striatal-midbrain connectivity in depression

Common neural deficits across reward functions in major depression: a meta-analysis of fMRI studies

Major depressive disorder (MDD) is characterized by deficient reward functions in the brain. However, existing findings on functional alterations during reward anticipation, reward processing, and learning among MDD patients are inconsistent, and it was unclear whether a common reward system implicated in multiple reward functions is altered in MDD. Here we meta-analyzed 18 past studies that compared brain reward functions between adult MDD patients (N = 477, mean age = 26.50 years, female = 59.40%) and healthy controls (N = 506, mean age = 28.11 years, females = 55.58%), and particularly examined group differences across multiple reward functions. Jack-knife sensitivity and subgroup meta-analyses were conducted to test robustness of findings across patient comorbidity, task paradigm, and reward nature. Meta-regression analyses assessed the moderating effect of patient symptom severity and anhedonia scores. We found during reward anticipation, MDD patients showed lower activities in the lateral prefrontal-thalamus circuitry. During reward processing, patients displayed reduced activities in the right striatum and prefrontal cortex, but increased activities in the left temporal cortex. During reward learning, patients showed reduced activity in the lateral prefrontal-thalamic-striatal circuitry and the right parahippocampal-occipital circuitry but higher activities in bilateral cerebellum and the left visual cortex. MDD patients showed decreased activity in the right thalamus during both reward anticipation and learning, and in the right caudate during both reward processing and learning. Larger functional changes in MDD were observed among patients with more severe symptoms and higher anhedonia levels. The thalamic-striatal circuitry functional alterations could be the key neural mechanism underlying MDD patients overarching reward function deficiencies.

Exploring causal mechanisms of psychosis risk

Robust epidemiological evidence of risk and protective factors for psychosis is essential to inform preventive interventions. Previous evidence syntheses have classified these risk and protective factors according to their strength of association with psychosis. In this critical review we appraise the distinct and overlapping mechanisms of 25 key environmental risk factors for psychosis, and link these to mechanistic pathways that may contribute to neurochemical alterations hypothesised to underlie psychotic symptoms. We then discuss the implications of our findings for future research, specifically considering interactions between factors, exploring universal and subgroup-specific factors, improving understanding of temporality and risk dynamics, standardising operationalisation and measurement of risk and protective factors, and developing preventive interventions targeting risk and protective factors.

The effect of emotional faces on reward-related probability learning in depressed patients

BACKGROUND

Existing research indicates that individuals with Major Depressive Disorder (MDD) exhibit a bias toward salient negative stimuli. However, the impact of such biased stimuli on concurrent cognitive and affective processes in individuals with depression remains inadequately understood. This study aimed to investigate the effects of salient environmental stimuli, specifically emotional faces, on reward-associated processes in MDD.

METHODS

Thirty-three patients with recurrent MDD and thirty-two healthy controls (HC) matched for age, sex, and education were included in the study. We used a reward-related associative learning (RRAL) task primed with emotional (happy, sad, neutral) faces to investigate the effect of salient stimuli on reward-related learning and decision-making in functional magnetic resonance imaging (fMRI). Participants were instructed to ignore emotional faces during the task. The fMRI data were analyzed using a full-factorial general linear model (GLM) in Statistical Parametric Mapping (SPM12).

RESULTS

In depressed patients, cues primed with sad faces were associated with reduced amygdala activation. However, both HC and MDD group exhibited reduced ventral striatal activity while learning reward-related cues and receiving rewards.

LIMITATIONS

The patients'medication usage was not standardized.

CONCLUSIONS

This study underscores the functional alteration of the amygdala in response to cognitive tasks presented with negative emotionally salient stimuli in the environment of MDD patients. The observed alterations in amygdala activity suggest potential interconnected effects with other regions of the prefrontal cortex. Understanding the intricate neural connections and their disruptions in depression is crucial for unraveling the complex pathophysiology of the disorder.

Are depressive symptoms linked to a reduced pupillary response to novel positive information?-An eye tracking proof-of-concept study

Introduction

Depressive symptoms have been linked to difficulties in revising established negative beliefs in response to novel positive information. Recent predictive processing accounts have suggested that this bias in belief updating may be related to a blunted processing of positive prediction errors at the neural level. In this proof-of-concept study, pupil dilation in response to unexpected positive emotional information was examined as a psychophysiological marker of an attenuated processing of positive prediction errors associated with depressive symptoms.

Methods

Participants (N = 34) completed a modified version of the emotional Bias Against Disconfirmatory Evidence (BADE) task in which scenarios initially suggest negative interpretations that are later either confirmed or disconfirmed by additional information. Pupil dilation in response to the confirmatory and disconfirmatory information was recorded.

Results

Behavioral results showed that depressive symptoms were related to difficulties in revising negative interpretations despite disconfirmatory positive information. The eye tracking results pointed to a reduced pupil response to unexpected positive information among people with elevated depressive symptoms.

Discussion

Altogether, the present study demonstrates that the adapted emotional BADE task can be appropriate for examining psychophysiological aspects such as changes in pupil size along with behavioral responses. Furthermore, the results suggest that depression may be characterized by deviations in both behavioral (i.e., reduced updating of negative beliefs) and psychophysiological (i.e., decreased pupil dilation) responses to unexpected positive information. Future work should focus on a larger sample including clinically depressed patients to further explore these findings.

From Complexity to Precision-Charting Decision-Making Through Normative Modeling

This Viewpoint synthesizes data-driven and theory-driven approaches to normative modeling.

Factual and counterfactual learning in major adolescent depressive disorder, evidence from an instrumental learning study

BACKGROUND

The incidence of adolescent depressive disorder is globally skyrocketing in recent decades, albeit the causes and the decision deficits depression incurs has yet to be well-examined. With an instrumental learning task, the aim of the current study is to investigate the extent to which learning behavior deviates from that observed in healthy adolescent controls and track the underlying mechanistic channel for such a deviation.

METHODS

We recruited a group of adolescents with major depression and age-matched healthy control subjects to carry out the learning task with either gain or loss outcome and applied a reinforcement learning model that dissociates valence (positive v. negative) of reward prediction error and selection (chosen v. unchosen).

RESULTS

The results demonstrated that adolescent depressive patients performed significantly less well than the control group. Learning rates suggested that the optimistic bias that overall characterizes healthy adolescent subjects was absent for the depressive adolescent patients. Moreover, depressed adolescents exhibited an increased pessimistic bias for the counterfactual outcome. Lastly, individual difference analysis suggested that these observed biases, which significantly deviated from that observed in normal controls, were linked with the severity of depressive symoptoms as measured by HAMD scores.

CONCLUSIONS

By leveraging an incentivized instrumental learning task with computational modeling within a reinforcement learning framework, the current study reveals a mechanistic decision-making deficit in adolescent depressive disorder. These findings, which have implications for the identification of behavioral markers in depression, could support the clinical evaluation, including both diagnosis and prognosis of this disorder.

Scalp electroacupuncture targeting the VTADA neurons to relieve negative emotions and promote the alleviation of chronic pain

Object

Chronic pain and negative emotions are often linked, and both can impact the reward circuit. The use of electroacupuncture (EA) has been found to regulate and improve these conditions. This study explores the potential mechanism of chronic pain relief by adding acupoints with emotional regulation effect to the basis of routine EA analgesia, to optimize the acupoint compatibility scheme of EA in the treatment of analgesia.

Method

For this study, 42 male Wistar rats were used. Recombinant adeno-associated viruses were used to label and regulate the activity of dopamine (DA) neurons. The rat model was established by complete Freund's adjuvant (CFA). Lower limb electroacupuncture (LEA) was applied to the ST36 and BL60 acupoints. In addition, LEA + scalp EA (SEA) was given using the GV20 and GV24+ acupoints besides ST36 and BL60. To evaluate the pain threshold, we measured 50% paw withdrawal thresholds and thermal paw withdrawal latencies. Negative emotions were evaluated through the open field test, marble-burying test, sucrose preference test, and forced swimming test. Moreover, the conditional place preference test was conducted to measure the reward behavior in response to pain relief. Immunofluorescence staining, Western blotting, and qPCR were used to detect the activity of the VTADA-NAc reward circuit.

Result

The injection of CFA significantly lowered the pain threshold. As the pain persisted, the anxiety and depression-like behaviors escalated while the response to reward reduced. Meanwhile, the VTADA-NAc pathway was suppressed with pain chronification. However, activating DA neurons in VTA attenuated the effects induced by CFA. LEA could relieve chronic pain, negative emotions, and reward disorders, while also activating the VTADA-NAc pathway. In addition, LEA + SEA exhibited a more pronounced effect compared with LEA alone. Nevertheless, chemogenetic inhibition of DA neurons decreased the efficacy of LEA + SEA in the treatment of chronic pain and associated comorbidities.

Conclusion

Adding SEA to conventional LEA effectively alleviates negative emotions and chronic pain, potentially due to the activation of the VTADA-NAc reward neural circuit. Thus, LEA + SEA is a more effective treatment for hyperalgesia and associated negative emotions compared with LEA alone.

Leveraging Decision Science to Characterize Depression

This brief review examines the potential to use decision science to objectively characterize depression. We provide a brief overview of the existing literature examining different domains of decision-making in depression. Because this overview highlights the specific role of reinforcement learning as an important decision process affected in the disorder, we then introduce reinforcement learning modeling and explain how this approach has identified specific reinforcement learning deficits in depression. We conclude with ideas for future research at the intersection of decision science and depression, emphasizing the potential for decision science to help uncover underlying mechanisms and targets for the treatment of depression.

Uncovering the Neural Correlates of Anhedonia Subtypes in Major Depressive Disorder: Implications for Intervention Strategies

Major depressive disorder (MDD) represents a serious public health concern, negatively affecting individuals' quality of life and making a substantial contribution to the global burden of disease. Anhedonia is a core symptom of MDD and is associated with poor treatment outcomes. Variability in anhedonia components within MDD has been observed, suggesting heterogeneity in psychopathology across subgroups. However, little is known about anhedonia subgroups in MDD and their underlying neural correlates across subgroups. To address this question, we employed a hierarchical cluster analysis based on Temporal Experience of Pleasure Scale subscales in 60 first-episode, drug-naive MDD patients and 32 healthy controls. Then we conducted a connectome-wide association study and whole-brain voxel-wise functional analyses for identified subgroups. There were three main findings: (1) three subgroups with different anhedonia profiles were identified using a data mining approach; (2) several parts of the reward network (especially pallidum and dorsal striatum) were associated with anticipatory and consummatory pleasure; (3) different patterns of within- and between-network connectivity contributed to the disparities of anhedonia profiles across three MDD subgroups. Here, we show that anhedonia in MDD is not uniform and can be categorized into distinct subgroups, and our research contributes to the understanding of neural underpinnings, offering potential treatment directions. This work emphasizes the need for tailored approaches in the complex landscape of MDD. The identification of homogeneous, stable, and neurobiologically valid MDD subtypes could significantly enhance our comprehension and management of this multifaceted condition.

Pramipexole for the Treatment of Depression: Efficacy and Mechanisms

Dopaminergic mechanisms are a plausible treatment target for patients with clinical depression but are relatively underexplored in conventional antidepressant medications. There is continuing interest in the potential antidepressant effects of the dopamine receptor agonist, pramipexole, with data from both case series and controlled trials indicating that this agent may produce benefit for patients with difficult-to-treat depression. Pramipexole's therapeutic utility in depression is likely to be expressed through alterations in reward mechanisms which are strongly influenced by dopamine pathways and are known to function abnormally in depressed patients. Our work in healthy participants using brain imaging in conjunction with computational modelling suggests that repeated pramipexole facilitates reward learning by inhibiting value decay. This mechanism needs to be confirmed in larger clinical trials in depressed patients. Such studies will also allow assessment of whether baseline performance in reward learning in depression predicts therapeutic response to pramipexole treatment.

CBT for difficult-to-treat depression: self-regulation model

BACKGROUND

Cognitive behavioural therapy (CBT) is an effective treatment for depression but a significant minority of clients do not complete therapy, do not respond to it, or subsequently relapse. Non-responders, and those at risk of relapse, are more likely to have adverse childhood experiences, early-onset depression, co-morbidities, interpersonal problems and heightened risk. This is a heterogeneous group of clients who are currently difficult to treat.

AIM

The aim was to develop a CBT model of depression that will be effective for difficult-to-treat clients who have not responded to standard CBT.

METHOD

The method was to unify theory, evidence and clinical strategies within the field of CBT to develop an integrated CBT model. Single case methods were used to develop the treatment components.

RESULTS

A self-regulation model of depression has been developed. It proposes that depression is maintained by repeated interactions of self-identity disruption, impaired motivation, disengagement, rumination, intrusive memories and passive life goals. Depression is more difficult to treat when these processes become interlocked. Treatment based on the model builds self-regulation skills and restructures self-identity, rather than target negative beliefs. A bespoke therapy plan is formed out of ten treatment components, based on an individual case formulation.

CONCLUSIONS

A self-regulation model of depression is proposed that integrates theory, evidence and practice within the field of CBT. It has been developed with difficult-to-treat cases as its primary purpose. A case example is described in a concurrent article (Barton et al., 2022) and further empirical tests are on-going.

Ventral striatal islands of Calleja neurons bidirectionally mediate depression-like behaviors in mice

The ventral striatum is a reward center implicated in the pathophysiology of depression. It contains islands of Calleja, clusters of dopamine D3 receptor-expressing granule cells, predominantly in the olfactory tubercle (OT). These OT D3 neurons regulate self-grooming, a repetitive behavior manifested in affective disorders. Here we show that chronic restraint stress (CRS) induces robust depression-like behaviors in mice and decreases excitability of OT D3 neurons. Ablation or inhibition of these neurons leads to depression-like behaviors, whereas their activation ameliorates CRS-induced depression-like behaviors. Moreover, activation of OT D3 neurons has a rewarding effect, which diminishes when grooming is blocked. Finally, we propose a model that explains how OT D3 neurons may influence dopamine release via synaptic connections with OT spiny projection neurons (SPNs) that project to midbrain dopamine neurons. Our study reveals a crucial role of OT D3 neurons in bidirectionally mediating depression-like behaviors, suggesting a potential therapeutic target.

Signed and unsigned effects of prediction error on memory: Is it a matter of choice?

Adaptive decision-making is governed by at least two types of memory processes. On the one hand, learned predictions through integrating multiple experiences, and on the other hand, one-shot episodic memories. These two processes interact, and predictions - particularly prediction errors - influence how episodic memories are encoded. However, studies using computational models disagree on the exact shape of this relationship, with some findings showing an effect of signed prediction errors and others showing an effect of unsigned prediction errors on episodic memory. We argue that the choice-confirmation bias, which reflects stronger learning from choice-confirming compared to disconfirming outcomes, could explain these seemingly diverging results. Our perspective implies that the influence of prediction errors on episodic encoding critically depends on whether people can freely choose between options (i.e., instrumental learning tasks) or not (Pavlovian learning tasks). The choice-confirmation bias on memory encoding might have evolved to prioritize memory representations that optimize reward-guided decision-making. We conclude by discussing open issues and implications for future studies.

Central regulation of stress-evoked peripheral immune responses

Stress-linked psychiatric disorders, including anxiety and major depressive disorder, are associated with systemic inflammation. Recent studies have reported stress-induced alterations in haematopoiesis that result in monocytosis, neutrophilia, lymphocytopenia and, consequently, in the upregulation of pro-inflammatory processes in immunologically relevant peripheral tissues. There is now evidence that this peripheral inflammation contributes to the development of psychiatric symptoms as well as to common co-morbidities of psychiatric disorders such as metabolic syndrome and immunosuppression. Here, we review the specific brain and spinal regions, and the neuronal populations within them, that respond to stress and transmit signals to peripheral tissues via the autonomic nervous system or neuroendocrine pathways to influence immunological function. We comprehensively summarize studies that have employed retrograde tracing to define neurocircuits linking the brain to the bone marrow, spleen, gut, adipose tissue and liver. Moreover, we highlight studies that have used chemogenetic or optogenetic manipulation or intracerebroventricular administration of peptide hormones to control somatic immune responses. Collectively, this growing body of literature illustrates potential mechanisms through which stress signals are conveyed from the CNS to immune cells to regulate stress-relevant behaviours and comorbid pathophysiology.

Alterations of brainstem volume in patients with first-episode and recurrent major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a prevalent mental health condition characterized by recurrent episodes in a substantial proportion of patients. The number of previous episodes is one of the most crucial predictors of depression recurrence. However, the underlying neural mechanisms remain unclear. To date, there have been limited neuroimaging studies investigating morphological changes of the brainstem in patients with first-episode MDD (FMDD) and recurrent MDD (RMDD). This study aimed to examine volumetric changes of individual brainstem regions in relation to the number of previous episodes and disease duration.

METHOD

A total of 111 individuals including 36 FMDD, 25 RMDD, and 50 healthy controls (HCs) underwent T1-weighted structural magnetic resonance imaging scans. A Bayesian segmentation algorithm was used to analyze the volume of each brainstem region, including the medulla oblongata, pons, midbrain, and superior cerebellar peduncle (SCP), as well as the whole brainstem volume. Analyses of variance (ANOVA) were performed to obtain brain regions with significant differences among three groups and then post hoc tests were calculated for inter-group comparisons. Partial correlation analyses were further conducted to identify associations between regional volumes and clinical features.

RESULTS

The ANOVA revealed significant brainstem volumetric differences among three groups in the pons, midbrain, SCP, and the whole brainstem (F = 3.996 ~ 5.886, adjusted p = 0.015 ~ 0.028). As compared with HCs, both groups of MDD patients showed decreased volumes in the pons as well as the entire brainstem (p = 0.002 ~ 0.034), however, only the FMDD group demonstrated a significantly reduced volume in the midbrain (p = 0.003). Specifically, the RMDD group exhibited significantly decreased SCP volume when comparing to both FMDD (p = 0.021) group and HCs (p = 0.008). Correlation analyses revealed that the SCP volumes were negatively associated with the number of depressive episodes (r=-0.36, p < 0.01) and illness duration (r=-0.28, p = 0.035) in patients with MDD.

CONCLUSION

The present findings provided evidence of decreased brainstem volume involving in the pathophysiology of MDD, particularly, volumetric reduction in the SCP might represent a neurobiological marker for RMDD. Further research is needed to confirm our observations and deepen our understanding of the neural mechanisms underlying depression recurrence.

Sensitivity to intrinsic rewards is domain general and related to mental health

Humans frequently engage in intrinsically rewarding activities (for example, consuming art, reading). Despite such activities seeming diverse, we show that sensitivity to intrinsic rewards is domain general and associated with mental health. In this cross-sectional study, participants online (N = 483) were presented with putative visual, cognitive and social intrinsic rewards as well as monetary rewards and neutral stimuli. All rewards elicited positive feelings (were 'liked'), generated consummatory behaviour (were 'wanted') and increased the likelihood of the action leading to them (were 'reinforcing'). Factor analysis revealed that ~40% of response variance across stimuli was explained by a general sensitivity to all rewards, but not to neutral stimuli. Affective aspects of mental health were associated with sensitivity to intrinsic, but not monetary, rewards. These results may help explain thriving and suffering: individuals with high reward sensitivity will engage in a variety of intrinsically rewarding activities, eventually finding those they excel at, whereas low sensitivity individuals will not.

Stress to inflammation and anhedonia: Mechanistic insights from preclinical and clinical models

Anhedonia, as evidenced by impaired pleasurable response to reward, reduced reward motivation, and/or deficits in reward-related learning, is a common feature of depression. Such deficits in reward processing are also an important clinical target as a risk factor for depression onset. Unfortunately, reward-related deficits remain difficult to treat. To address this gap and inform the development of effective prevention and treatment strategies, it is critical to understand the mechanisms that drive impairments in reward function. Stress-induced inflammation is a plausible mechanism of reward deficits. The purpose of this paper is to review evidence for two components of this psychobiological pathway: 1) the effects of stress on reward function; and 2) the effects of inflammation on reward function. Within these two areas, we draw upon preclinical and clinical models, distinguish between acute and chronic effects of stress and inflammation, and address specific domains of reward dysregulation. By addressing these contextual factors, the review reveals a nuanced literature which might be targeted for additional scientific inquiry to inform the development of precise interventions.

Adaptive Design Optimization as a Promising Tool for Reliable and Efficient Computational Fingerprinting

A key challenge in understanding mental (dys)functions is their etiological and functional heterogeneity, and several multidimensional assessments have been proposed for their comprehensive characterization. However, such assessments require lengthy testing, which may hinder reliable and efficient characterization of individual differences due to increased fatigue and distraction, especially in clinical populations. Computational modeling may address this challenge as it often provides more reliable measures of latent neurocognitive processes underlying observed behaviors and captures individual differences better than traditional assessments. However, even with a state-of-the-art hierarchical modeling approach, reliable estimation of model parameters still requires a large number of trials. Recent work suggests that Bayesian adaptive design optimization (ADO) is a promising way to address these challenges. With ADO, experimental design is optimized adaptively from trial to trial to extract the maximum amount of information about an individual's characteristics. In this review, we first describe the ADO methodology and then summarize recent work demonstrating that ADO increases the reliability and efficiency of latent neurocognitive measures. We conclude by discussing the challenges and future directions of ADO and proposing development of ADO-based computational fingerprints to reliably and efficiently characterize the heterogeneous profiles of psychiatric disorders.

Biased belief updating in depression

Cognitive approaches to depression have benefitted from recent research on belief updating, examining how new information is used to alter beliefs. This review presents recent advances in understanding various sources of bias in belief updating in depression. Specifically, research has demonstrated that people with depression have difficulty revising negative beliefs in response to novel positive information, whereas belief updating in depression is not related to an enhanced integration of negative information. In terms of mechanisms underlying the deficient processing of positive information, research has shown that people with depression use defensive cognitive strategies to devalue novel positive information. Furthermore, the disregard of novel positive information can be amplified by the presence of state negative affect, and the resulting persistence of negative beliefs in turn perpetuates chronically low mood, contributing to a self-reinforcing negative feedback loop of beliefs and affect. Synthesising previous research, this review proposes a coherent framework of when belief change is likely to occur, and argues that future research also needs to elucidate why people with depression hesitate to abandon negative beliefs. Recent insights from belief updating have not only improved the understanding of the psychopathology of depression, but also have the potential to improve its cognitive-behavioural treatment.

Beta Oscillations in Monkey Striatum Encode Reward Prediction Error Signals

Reward prediction error (RPE) signals are crucial for reinforcement learning and decision-making as they quantify the mismatch between predicted and obtained rewards. RPE signals are encoded in the neural activity of multiple brain areas, such as midbrain dopaminergic neurons, prefrontal cortex, and striatum. However, it remains unclear how these signals are expressed through anatomically and functionally distinct subregions of the striatum. In the current study, we examined to which extent RPE signals are represented across different striatal regions. To do so, we recorded local field potentials (LFPs) in sensorimotor, associative, and limbic striatal territories of two male rhesus monkeys performing a free-choice probabilistic learning task. The trial-by-trial evolution of RPE during task performance was estimated using a reinforcement learning model fitted on monkeys' choice behavior. Overall, we found that changes in beta band oscillations (15-35 Hz), after the outcome of the animal's choice, are consistent with RPE encoding. Moreover, we provide evidence that the signals related to RPE are more strongly represented in the ventral (limbic) than dorsal (sensorimotor and associative) part of the striatum. To conclude, our results suggest a relationship between striatal beta oscillations and the evaluation of outcomes based on RPE signals and highlight a major contribution of the ventral striatum to the updating of learning processes.SIGNIFICANCE STATEMENT Reward prediction error (RPE) signals are crucial for reinforcement learning and decision-making as they quantify the mismatch between predicted and obtained rewards. Current models suggest that RPE signals are encoded in the neural activity of multiple brain areas, including the midbrain dopaminergic neurons, prefrontal cortex and striatum. However, it remains elusive whether RPEs recruit anatomically and functionally distinct subregions of the striatum. Our study provides evidence that RPE-related modulations in local field potential (LFP) power are dominant in the striatum. In particular, they are stronger in the rostro-ventral rather than the caudo-dorsal striatum. Our findings contribute to a better understanding of the role of striatal territories in reward-based learning and may be relevant for neuropsychiatric and neurologic diseases that affect striatal circuits.

Time perception reflects individual differences in motor and non-motor symptoms of Parkinson's disease

Dopaminergic signaling in the striatum has been shown to play a critical role in the perception of time. Decreasing striatal dopamine efficacy is at the core of Parkinson's disease (PD) motor symptoms and changes in dopaminergic action have been associated with many comorbid non-motor symptoms in PD. We hypothesize that patients with PD perceive time differently and in accordance with their specific comorbid non-motor symptoms and clinical state. We recruited patients with PD and compared individual differences in patients' clinical features with their ability to judge millisecond to second intervals of time (500ms-1100ms) while on or off their prescribed dopaminergic medications. We show that individual differences in comorbid non-motor symptoms, PD duration, and prescribed dopaminergic pharmacotherapeutics account for individual differences in time perception performance. We report that comorbid impulse control disorder is associated with temporal overestimation; depression is associated with decreased temporal accuracy; and PD disease duration and prescribed levodopa monotherapy are associated with reduced temporal precision and accuracy. Observed differences in time perception are consistent with hypothesized dopaminergic mechanisms thought to underlie the respective motor and non-motor symptoms in PD, but also raise questions about specific dopaminergic mechanisms. In future work, time perception tasks like the one used here, may provide translational or reverse translational utility in investigations aimed at disentangling neural and cognitive systems underlying PD symptom etiology.

One Sentence Summary

Quantitative characterization of time perception behavior reflects individual differences in Parkinson's disease motor and non-motor symptom clinical presentation that are consistent with hypothesized neural and cognitive mechanisms.

Modelling mood updating: a proof of principle study

BACKGROUND

Recent developments in computational psychiatry have led to the hypothesis that mood represents an expectation (prior belief) on the likely interoceptive consequences of action (i.e. emotion). This stems from ideas about how the brain navigates its external world by minimising an upper bound on surprisal (free energy) of sensory information and echoes developments in other perceptual domains.

AIMS

In this paper we aim to present a simple partial observable Markov decision process that models mood updating in response to stressful or non-stressful environmental fluctuations while seeking to minimise surprisal in relation to prior beliefs about the likely interoceptive signals experienced with specific actions (attenuating or amplifying stress and pleasure signals).

METHOD

We examine how, by altering these prior beliefs we can model mood updating in depression, mania and anxiety.

RESULTS

We discuss how these models provide a computational account of mood and its related psychopathology and relate it to previous research in reward processing.

CONCLUSIONS

Models such as this can provide hypotheses for experimental work and also open up the potential modelling of predicted disease trajectories in individual patients.

How negative mood hinders belief updating in depression: results from two experimental studies

BACKGROUND

In two experimental studies, we tested the hypothesis that negative mood would hinder the revision of negative beliefs in response to unexpectedly positive information in depression, whereas positive mood was expected to enhance belief updating.

METHODS

In study 1 (N = 101), we used a subclinical sample to compare the film-based induction of sad v. happy mood with a distraction control group. Subsequently, participants underwent a well-established paradigm to examine intra-individual changes in performance-related expectations after unexpectedly positive performance feedback. In study 2, we applied the belief-updating task from study 1 to an inpatient sample (N = 81) and induced sad v. happy mood via film-clips v. recall of autobiographic events.

RESULTS

The results of study 1 showed no significant group differences in belief updating; the severity of depressive symptoms was a negative predictor of belief revision, though, and there was a non-significant trend suggesting that the presence of sad mood hindered belief updating in the subgroup of participants with a diagnosed depressive episode. Study 2 revealed that participants updated their expectations significantly less in line with positive feedback when they underwent the induction of negative mood prior to feedback, relative to positive mood.

CONCLUSIONS

By indicating that the presence of negative mood can hinder the revision of negative beliefs in clinically depressed people, our findings suggest that learning from new experiences can be hampered if state negative mood is activated. Thus, interventions relying on learning from novel positive experiences should aim at reducing state negative mood in depression.

Angiotensin blockade enhances motivational reward learning via enhancing striatal prediction error signaling and frontostriatal communication

Adaptive human learning utilizes reward prediction errors (RPEs) that scale the differences between expected and actual outcomes to optimize future choices. Depression has been linked with biased RPE signaling and an exaggerated impact of negative outcomes on learning which may promote amotivation and anhedonia. The present proof-of-concept study combined computational modeling and multivariate decoding with neuroimaging to determine the influence of the selective competitive angiotensin II type 1 receptor antagonist losartan on learning from positive or negative outcomes and the underlying neural mechanisms in healthy humans. In a double-blind, between-subjects, placebo-controlled pharmaco-fMRI experiment, 61 healthy male participants (losartan, n = 30; placebo, n = 31) underwent a probabilistic selection reinforcement learning task incorporating a learning and transfer phase. Losartan improved choice accuracy for the hardest stimulus pair via increasing expected value sensitivity towards the rewarding stimulus relative to the placebo group during learning. Computational modeling revealed that losartan reduced the learning rate for negative outcomes and increased exploitatory choice behaviors while preserving learning for positive outcomes. These behavioral patterns were paralleled on the neural level by increased RPE signaling in orbitofrontal-striatal regions and enhanced positive outcome representations in the ventral striatum (VS) following losartan. In the transfer phase, losartan accelerated response times and enhanced VS functional connectivity with left dorsolateral prefrontal cortex when approaching maximum rewards. These findings elucidate the potential of losartan to reduce the impact of negative outcomes during learning and subsequently facilitate motivational approach towards maximum rewards in the transfer of learning. This may indicate a promising therapeutic mechanism to normalize distorted reward learning and fronto-striatal functioning in depression.

Anhedonia in Relation to Reward and Effort Learning in Young People with Depression Symptoms

Anhedonia, a central depression symptom, is associated with impairments in reward processing. However, it is not well understood which sub-components of reward processing (anticipation, motivation, consummation, and learning) are impaired in association with anhedonia in depression. In particular, it is unclear how learning about different rewards and the effort needed to obtain them might be associated with anhedonia and depression symptoms. Therefore, we examined learning in young people (N = 132, mean age 20, range 17-25 yrs.) with a range of depression and anhedonia symptoms using a probabilistic instrumental learning task. The task required participants to learn which options to choose to maximize their reward outcomes across three conditions (chocolate taste, puppy images, or money) and to minimize the physical effort required to obtain the rewards. Additionally, we collected questionnaire measures of anticipatory and consummatory anhedonia, as well as subjective reports of "liking", "wanting" and "willingness to exert effort" for the rewards used in the task. We found that as anticipatory anhedonia increased, subjective liking and wanting of rewards decreased. Moreover, higher anticipatory anhedonia was significantly associated with lower reward learning accuracy, and participants demonstrated significantly higher reward learning than effort learning accuracy. To our knowledge, this is the first study observing an association of anhedonia with reward liking, wanting, and learning when reward and effort learning are measured simultaneously. Our findings suggest an impaired ability to learn from rewarding outcomes could contribute to anhedonia in young people. Future longitudinal research is needed to confirm this and reveal the specific aspects of reward learning that predict anhedonia. These aspects could then be targeted by novel anhedonia interventions.

Computational models of subjective feelings in psychiatry

Research in computational psychiatry is dominated by models of behavior. Subjective experience during behavioral tasks is not well understood, even though it should be relevant to understanding the symptoms of psychiatric disorders. Here, we bridge this gap and review recent progress in computational models for subjective feelings. For example, happiness reflects not how well people are doing, but whether they are doing better than expected. This dependence on recent reward prediction errors is intact in major depression, although depressive symptoms lower happiness during tasks. Uncertainty predicts subjective feelings of stress in volatile environments. Social prediction errors influence feelings of self-worth more in individuals with low self-esteem despite a reduced willingness to change beliefs due to social feedback. Measuring affective state during behavioral tasks provides a tool for understanding psychiatric symptoms that can be dissociable from behavior. When smartphone tasks are collected longitudinally, subjective feelings provide a potential means to bridge the gap between lab-based behavioral tasks and real-life behavior, emotion, and psychiatric symptoms.

Individual differences in naturalistic learning link negative emotionality to the development of anxiety

Organisms learn from prediction errors (PEs) to predict the future. Laboratory studies using small financial outcomes find that humans use PEs to update expectations and link individual differences in PE-based learning to internalizing disorders. Because of the low-stakes outcomes in most tasks, it is unclear whether PE learning emerges in naturalistic, high-stakes contexts and whether individual differences in PE learning predict psychopathology risk. Using experience sampling to assess 625 college students' expected exam grades, we found evidence of PE-based learning and a general tendency to discount negative PEs, an "optimism bias." However, individuals with elevated negative emotionality, a personality trait linked to the development of anxiety disorders, displayed a global pessimism and learning differences that impeded accurate expectations and predicted future anxiety symptoms. A sensitivity to PEs combined with an aversion to negative PEs may result in a pessimistic and inaccurate model of the world, leading to anxiety.

Plasticity of synapses and reward circuit function in the genesis and treatment of depression

What changes in brain function cause the debilitating symptoms of depression? Can we use the answers to this question to invent more effective, faster acting antidepressant drug therapies? This review provides an overview and update of the converging human and preclinical evidence supporting the hypothesis that changes in the function of excitatory synapses impair the function of the circuits they are embedded in to give rise to the pathological changes in mood, hedonic state, and thought processes that characterize depression. The review also highlights complementary human and preclinical findings that classical and novel antidepressant drugs relieve the symptoms of depression by restoring the functions of these same synapses and circuits. These findings offer a useful path forward for designing better antidepressant compounds.

The (un)learning of social functions and its significance for mental health

Social interactions are dynamic, context-dependent, and reciprocal events that influence prospective strategies and require constant practice and adaptation. This complexity of social interactions creates several research challenges. We propose a new framework encouraging future research to investigate not only individual differences in capacities relevant for social functioning and their underlying mechanisms, but also the flexibility to adapt or update one's social abilities. We suggest three key capacities relevant for social functioning: (1) social perception, (2) sharing emotions or empathizing, and (3) mentalizing. We elaborate on how adaptations in these capacities may be investigated on behavioral and neural levels. Research on these flexible adaptations of one's social behavior is needed to specify how humans actually "learn to be social". Learning to adapt implies plasticity of the relevant brain networks involved in the underlying social processes, indicating that social abilities are malleable for different contexts. To quantify such measures, researchers need to find ways to investigate learning through dynamic changes in adaptable social paradigms and examine several factors influencing social functioning within the three aformentioned social key capacities. This framework furthers insight concerning individual differences, provides a holistic approach to social functioning, and may improve interventions for ameliorating social abilities in patients.

Medial Prefrontal Cortex Activity to Reward Outcome Moderates the Association Between Victimization Due to Sexual Orientation and Depression in Youth

BACKGROUND

Sexual minority youth (SMY) are 3 times more likely to experience depression than heterosexual peers. Minority stress theory posits that this association is explained by sexual orientation victimization, which acts as a stressor to impact depression. For those vulnerable to the effects of stress, victimization may worsen depression by altering activity in neural reward systems. This study examines whether neural reward systems moderate the influence of sexual orientation victimization, a common and distressing experience in SMY, on depression.

METHODS

A total of 81 participants ages 15 to 22 years (41% SMY, 52% marginalized race) reported sexual orientation victimization, depression severity, and anhedonia severity, and underwent a monetary reward functional magnetic resonance imaging task. Significant activation to reward > neutral outcome (p_{familywise error} < .05) was determined within a meta-analytically derived Neurosynth reward mask. A univariate linear model examined the impact of reward activation and identity on victimization-depression relationships.

RESULTS

SMY reported higher depression (p < .001), anhedonia (p = .03), and orientation victimization (p < .001) than heterosexual youth. The bilateral ventral striatum, medial prefrontal cortex (mPFC), anterior cingulate cortex, and right orbitofrontal cortex were significantly active to reward. mPFC activation moderated associations between sexual orientation victimization and depression (p = .03), with higher depression severity observed in those with a combination of higher mPFC activation and greater orientation victimization.

CONCLUSIONS

Sexual orientation victimization was related to depression but only in the context of higher mPFC activation, a pattern observed in depressed youth. These novel results provide evidence for neural reward sensitivity as a vulnerability factor for depression in SMY, suggesting mechanisms for disparities, and are a first step toward a clinical neuroscience understanding of minority stress in SMY.

A systematic review of the pharmacological modulation of autobiographical memory specificity

Background

Over-general autobiographical memory (AM) retrieval is proposed to have a causal role in the maintenance of psychological disorders like depression and PTSD. As such, the identification of drugs that modulate AM specificity may open up new avenues of research on pharmacological modeling and treatment of psychological disorders.

Aim

The current review summarizes randomized, placebo-controlled studies of acute pharmacological modulation of AM specificity.

Method

A systematic search was conducted of studies that examined the acute effects of pharmacological interventions on AM specificity in human volunteers (healthy and clinical participants) measured using the Autobiographical Memory Test.

Results

Seventeen studies were identified (986 total participants), of which 16 were judged to have low risk of bias. The presence and direction of effects varied across drugs and diagnostic status of participants (clinical vs. healthy volunteers). The most commonly studied drug-hydrocortisone-produced an overall impairment in AM specificity in healthy volunteers [g = -0.28, CI (-0.53, -0.03), p = 0.03], although improvements were reported in two studies of clinical participants. In general, studies of monoamine modulators reported no effect on specificity.

Conclusion

Pharmacological enhancement of AM specificity is inconsistent, although monaminergic modulators show little promise in this regard. Drugs that reduce AM specificity in healthy volunteers may be useful experimental-pharmacological tools that mimic an important transdiagnostic impairment in psychological disorders.

Systematic review registration

PROSPERO, identifier CRD42020199076, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020199076.

Computational reinforcement learning, reward (and punishment), and dopamine in psychiatric disorders

In the DSM-5, psychiatric diagnoses are made based on self-reported symptoms and clinician-identified signs. Though helpful in choosing potential interventions based on the available regimens, this conceptualization of psychiatric diseases can limit basic science investigation into their underlying causes. The reward prediction error (RPE) hypothesis of dopamine neuron function posits that phasic dopamine signals encode the difference between the rewards a person expects and experiences. The computational framework from which this hypothesis was derived, temporal difference reinforcement learning (TDRL), is largely focused on reward processing rather than punishment learning. Many psychiatric disorders are characterized by aberrant behaviors, expectations, reward processing, and hypothesized dopaminergic signaling, but also characterized by suffering and the inability to change one's behavior despite negative consequences. In this review, we provide an overview of the RPE theory of phasic dopamine neuron activity and review the gains that have been made through the use of computational reinforcement learning theory as a framework for understanding changes in reward processing. The relative dearth of explicit accounts of punishment learning in computational reinforcement learning theory and its application in neuroscience is highlighted as a significant gap in current computational psychiatric research. Four disorders comprise the main focus of this review: two disorders of traditionally hypothesized hyperdopaminergic function, addiction and schizophrenia, followed by two disorders of traditionally hypothesized hypodopaminergic function, depression and post-traumatic stress disorder (PTSD). Insights gained from a reward processing based reinforcement learning framework about underlying dopaminergic mechanisms and the role of punishment learning (when available) are explored in each disorder. Concluding remarks focus on the future directions required to characterize neuropsychiatric disorders with a hypothesized cause of underlying dopaminergic transmission.

The prevalence of internet addiction and its association with quality of life among clinically stable patients with major depressive disorder

BACKGROUND

Internet addiction (IA) is associated with mental health problems but its impact on quality of life (QOL) is understudied. We examined the prevalence of IA and its association with QOL in clinically stable patients with major depressive disorder (MDD).

METHODS

In a cross-sectional survey between September 2020 and July 2021, the Young's Internet Addiction Test (IAT), the Patient Health Questionnaire-2 (PHQ-2) and the World Health Organization Quality of Life Brief version scale (WHOQOL-BREF) were administered to 1267 patients with MDD. Logistic regression was used to examine the correlates of IA, while analysis of covariance (ANCOVA) was used to examine the association between IA and QOL."

RESULTS

The prevalence of IA (IAT total scores ≥50) was 27.2 % (95 % CI: 24.7 %-29.6 %) in MDD patients. Compared to patients without IA, those with IA had lower QOL (F_{(1, 1267)} = 19.1, P < 0.001). Logistic regression revealed that higher education (senior high school and above; OR = 1.85, 95 % CI: 1.13-3.03), family history of psychiatric disorders (OR = 1.72, 95 % CI: 1.08-2.73), and higher PHQ-2 total score (OR = 1.23, 95 % CI: 1.14-1.32) were positively associated with IA while older age (OR = 0.93, 95 % CI: 0.91-0.96) was inversely related to IA.

CONCLUSION

IA is much more common in clinically stable patients with MDD compared to the reported figures in the general population. It would be prudent to screen and monitor internet use in MDD patients and treat those with IA.

Effects of gonadal steroids on reward circuitry function and anhedonia in women with a history of postpartum depression

BACKGROUND

Reward system dysfunction is evident across neuropsychiatric conditions. Here we present data from a double-blinded pharmaco-fMRI study investigating the triggering of anhedonia and reward circuit activity in women.

METHODS

The hormonal states of pregnancy and parturition were simulated in euthymic women with a history of postpartum depression (PPD+; n = 15) and those without such a history (PPD-; n = 15) by inducing hypogonadism, adding back estradiol and progesterone for 8 weeks ("addback"), and then withdrawing both steroids ("withdrawal"). Anhedonia was assessed using the Inventory of Depression and Anxiety Symptoms (IDAS) during each hormone phase. Those who reported a 30 % or greater increase in IDAS anhedonia, dysphoria, or ill temper during addback or withdrawal, compared with pre-treatment, were identified as hormone sensitive (HS+) and all others were identified as non-hormone sensitive (HS-). The monetary incentive delay (MID) task was administered during fMRI sessions at pre-treatment and during hormone withdrawal to assess brain activation during reward anticipation and feedback.

RESULTS

On average, anhedonia increased during addback and withdrawal in PPD+ but not PPD-. During reward feedback, both HS+ (n = 10) and HS- (n = 18) showed decreased activation in clusters in the right putamen (p < .031, FWE-corrected) and left postcentral and supramarginal gyri (p < .014, FWE-corrected) at the withdrawal scans, relative to pre-treatment scans.

LIMITATIONS

A modest sample size, stringent exclusion criteria, and relative lack of diversity in study participants limit the generalizability of results.

CONCLUSION

Although results do not explain differential hormone sensitivity in depression, they demonstrate significant effects of reproductive hormones on reward-related brain function in women.

Rodent models of early adversity: Impacts on developing social behavior circuitry and clinical implications

Flexible and context-appropriate social functioning is key for survival across species. This flexibility also renders social behavior highly plastic, particularly during early development when attachment to caregiver can provide a template for future social processing. As a result, early caregiving adversity can have unique and lasting impacts on social behavior and even confer vulnerability to psychiatric disorders. However, the neural circuit mechanisms translating experience to outcome remain poorly understood. Here, we consider social behavior scaffolding through the lens of reward and threat processing. We begin by surveying several complementary rodent models of early adversity, which together have highlighted impacts on neural circuits processing social cues. We next explore these circuits underlying perturbed social functioning with focus on dopamine (DA) and its role in regions implicated in social and threat processing such as the prefrontal cortex (PFC), basolateral amygdala (BLA) and the lateral habenula (LHb). Finally, we turn to human populations once more to examine how altered DA signaling and LHb dysfunction may play a role in social anhedonia, a common feature in diagnoses such as schizophrenia and major depressive disorder (MDD). We argue that this translational focus is critical for identifying specific features of adversity that confer heightened vulnerability for clinical outcomes involving social cue processing.

Blunted reward prediction error signals in internet gaming disorder

BACKGROUND

Internet gaming disorder (IGD) is a type of behavioural addictions. One of the key features of addiction is the excessive exposure to addictive objectives (e.g. drugs) reduces the sensitivity of the brain reward system to daily rewards (e.g. money). This is thought to be mediated via the signals expressed as dopaminergic reward prediction error (RPE). Emerging evidence highlights blunted RPE signals in drug addictions. However, no study has examined whether IGD also involves alterations in RPE signals that are observed in other types of addictions.

METHODS

To fill this gap, we used functional magnetic resonance imaging data from 45 IGD and 42 healthy controls (HCs) during a reward-related prediction-error task and utilised a psychophysiological interaction (PPI) analysis to characterise the underlying neural correlates of RPE and related functional connectivity.

RESULTS

Relative to HCs, IGD individuals showed impaired reinforcement learning, blunted RPE signals in multiple regions of the brain reward system, including the right caudate, left orbitofrontal cortex (OFC), and right dorsolateral prefrontal cortex (DLPFC). Moreover, the PPI analysis revealed a pattern of hyperconnectivity between the right caudate, right putamen, bilateral DLPFC, and right dorsal anterior cingulate cortex (dACC) in the IGD group. Finally, linear regression suggested that the connection between the right DLPFC and right dACC could significantly predict the variation of RPE signals in the left OFC.

CONCLUSIONS

These results highlight disrupted RPE signalling and hyperconnectivity between regions of the brain reward system in IGD. Reinforcement learning deficits may be crucial underlying characteristics of IGD pathophysiology.

What Can Reinforcement Learning Models of Dopamine and Serotonin Tell Us about the Action of Antidepressants?

Although evidence suggests that antidepressants are effective at treating depression, the mechanisms behind antidepressant action remain unclear, especially at the cognitive/computational level. In recent years, reinforcement learning (RL) models have increasingly been used to characterise the roles of neurotransmitters and to probe the computations that might be altered in psychiatric disorders like depression. Hence, RL models might present an opportunity for us to better understand the computational mechanisms underlying antidepressant effects. Moreover, RL models may also help us shed light on how these computations may be implemented in the brain (e.g., in midbrain, striatal, and prefrontal regions) and how these neural mechanisms may be altered in depression and remediated by antidepressant treatments. In this paper, we evaluate the ability of RL models to help us understand the processes underlying antidepressant action. To do this, we review the preclinical literature on the roles of dopamine and serotonin in RL, draw links between these findings and clinical work investigating computations altered in depression, and appraise the evidence linking modification of RL processes to antidepressant function. Overall, while there is no shortage of promising ideas about the computational mechanisms underlying antidepressant effects, there is insufficient evidence directly implicating these mechanisms in the response of depressed patients to antidepressant treatment. Consequently, future studies should investigate these mechanisms in samples of depressed patients and assess whether modifications in RL processes mediate the clinical effect of antidepressant treatments.

Toward a Better Understanding of the Mechanisms and Pathophysiology of Anhedonia: Are We Ready for Translation?

Anhedonia-the loss of pleasure or lack of reactivity to pleasurable stimuli-remains a formidable treatment challenge across neuropsychiatric disorders. In major depressive disorder, anhedonia has been linked to poor disease course, worse response to psychological, pharmacological, and neurostimulation treatments, and increased suicide risk. Moreover, although some neural abnormalities linked to anhedonia normalize after successful treatment, several persist-for example, blunted activation of the ventral striatum to reward-related cues and reduced functional connectivity involving the ventral striatum. Critically, some of these abnormalities have also been identified in unaffected, never-depressed children of parents with major depressive disorder and have been found to prospectively predict the first onset of major depression. Thus, neural abnormalities linked to anhedonia may be promising targets for prevention. Despite increased appreciation of the clinical importance of anhedonia and its underlying neural mechanisms, important gaps remain. In this overview, the author first summarizes the extant knowledge about the pathophysiology of anhedonia, which may provide a road map toward novel treatment and prevention strategies, and then highlights several priorities to facilitate clinically meaningful breakthroughs. These include a need for 1) appropriately controlled clinical trials, especially those embracing an experimental therapeutics approach to probe target engagement; 2) novel preclinical models relevant to anhedonia, with stronger translational value; and 3) clinical scales that incorporate neuroscientific advances in our understanding of anhedonia. The author concludes by highlighting important future directions, emphasizing the need for an integrated, collaborative, cross-species, and multilevel approach to tackling anhedonic phenotypes.

A missing link in affect regulation: the cerebellum

The cerebellum is one-third the size of the cerebrum yet holds twice the number of neurons. Historically, its sole function was thought to be in the calibration of smooth movements through the creation and ongoing modification of motor programs. This traditional viewpoint has been challenged by findings showing that cerebellar damage can lead to striking changes in non-motor behavior, including emotional changes. In this manuscript, we review the literature on clinical and subclinical affective disturbances observed in individuals with lesions to the cerebellum. Disorders include pathological laughing and crying, bipolar disorder, depression and mixed mood changes. We propose a theoretical model based on cerebellar connectivity to explain how the cerebellum calibrates affect. We conclude with actionable steps for future researchers to test this model and improve upon the limitations of past literature.

Reduced nucleus accumbens functional connectivity in reward network and default mode network in patients with recurrent major depressive disorder

The nucleus accumbens (NAc) is considered a hub of reward processing and a growing body of evidence has suggested its crucial role in the pathophysiology of major depressive disorder (MDD). However, inconsistent results have been reported by studies on reward network-focused resting-state functional MRI (rs-fMRI). In this study, we examined functional alterations of the NAc-based reward circuits in patients with MDD via meta- and mega-analysis. First, we performed a coordinated-based meta-analysis with a new SDM-PSI method for all up-to-date rs-fMRI studies that focused on the reward circuits of patients with MDD. Then, we tested the meta-analysis results in the REST-meta-MDD database which provided anonymous rs-fMRI data from 186 recurrent MDDs and 465 healthy controls. Decreased functional connectivity (FC) within the reward system in patients with recurrent MDD was the most robust finding in this study. We also found disrupted NAc FCs in the DMN in patients with recurrent MDD compared with healthy controls. Specifically, the combination of disrupted NAc FCs within the reward network could discriminate patients with recurrent MDD from healthy controls with an optimal accuracy of 74.7%. This study confirmed the critical role of decreased FC in the reward network in the neuropathology of MDD. Disrupted inter-network connectivity between the reward network and DMN may also have contributed to the neural mechanisms of MDD. These abnormalities have potential to serve as brain-based biomarkers for individual diagnosis to differentiate patients with recurrent MDD from healthy controls.

The Convergence Model of Brain Reward Circuitry: Implications for Relief of Treatment-Resistant Depression by Deep-Brain Stimulation of the Medial Forebrain Bundle

Deep-brain stimulation of the medial forebrain bundle (MFB) can provide effective, enduring relief of treatment-resistant depression. Panksepp provided an explanatory framework: the MFB constitutes the core of the neural circuitry subserving the anticipation and pursuit of rewards: the “SEEKING” system. On that view, the SEEKING system is hypoactive in depressed individuals; background electrical stimulation of the MFB alleviates symptoms by normalizing activity. Panksepp attributed intracranial self-stimulation to excitation of the SEEKING system in which the ascending projections of midbrain dopamine neurons are an essential component. In parallel with Panksepp’s qualitative work, intracranial self-stimulation has long been studied quantitatively by psychophysical means. That work argues that the predominant directly stimulated substrate for MFB self-stimulation are myelinated, non-dopaminergic fibers, more readily excited by brief electrical current pulses than the thin, unmyelinated axons of the midbrain dopamine neurons. The series-circuit hypothesis reconciles this view with the evidence implicating dopamine in MFB self-stimulation as follows: direct activation of myelinated MFB fibers is rewarding due to their trans-synaptic activation of midbrain dopamine neurons. A recent study in which rats worked for optogenetic stimulation of midbrain dopamine neurons challenges the series-circuit hypothesis and provides a new model of intracranial self-stimulation in which the myelinated non-dopaminergic neurons and the midbrain dopamine projections access the behavioral final common path for reward seeking via separate, converging routes. We explore the potential implications of this convergence model for the interpretation of the antidepressant effect of MFB stimulation. We also discuss the consistent finding that psychomotor stimulants, which boost dopaminergic neurotransmission, fail to provide a monotherapy for depression. We propose that non-dopaminergic MFB components may contribute to the therapeutic effect in parallel to, in synergy with, or even instead of, a dopaminergic component.

Reinforcement Learning in Patients With Mood and Anxiety Disorders vs Control Individuals: A Systematic Review and Meta-analysis

IMPORTANCE

Computational psychiatry studies have investigated how reinforcement learning may be different in individuals with mood and anxiety disorders compared with control individuals, but results are inconsistent.

OBJECTIVE

To assess whether there are consistent differences in reinforcement-learning parameters between patients with depression or anxiety and control individuals.

DATA SOURCES

Web of Knowledge, PubMed, Embase, and Google Scholar searches were performed between November 15, 2019, and December 6, 2019, and repeated on December 3, 2020, and February 23, 2021, with keywords (reinforcement learning) AND (computational OR model) AND (depression OR anxiety OR mood).

STUDY SELECTION

Studies were included if they fit reinforcement-learning models to human choice data from a cognitive task with rewards or punishments, had a case-control design including participants with mood and/or anxiety disorders and healthy control individuals, and included sufficient information about all parameters in the models.

DATA EXTRACTION AND SYNTHESIS

Articles were assessed for inclusion according to MOOSE guidelines. Participant-level parameters were extracted from included articles, and a conventional meta-analysis was performed using a random-effects model. Subsequently, these parameters were used to simulate choice performance for each participant on benchmarking tasks in a simulation meta-analysis. Models were fitted, parameters were extracted using bayesian model averaging, and differences between patients and control individuals were examined. Overall effect sizes across analytic strategies were inspected.

MAIN OUTCOMES AND MEASURES

The primary outcomes were estimated reinforcement-learning parameters (learning rate, inverse temperature, reward learning rate, and punishment learning rate).

RESULTS

A total of 27 articles were included (3085 participants, 1242 of whom had depression and/or anxiety). In the conventional meta-analysis, patients showed lower inverse temperature than control individuals (standardized mean difference [SMD], -0.215; 95% CI, -0.354 to -0.077), although no parameters were common across all studies, limiting the ability to infer differences. In the simulation meta-analysis, patients showed greater punishment learning rates (SMD, 0.107; 95% CI, 0.107 to 0.108) and slightly lower reward learning rates (SMD, -0.021; 95% CI, -0.022 to -0.020) relative to control individuals. The simulation meta-analysis showed no meaningful difference in inverse temperature between patients and control individuals (SMD, 0.003; 95% CI, 0.002 to 0.004).

CONCLUSIONS AND RELEVANCE

The simulation meta-analytic approach introduced in this article for inferring meta-group differences from heterogeneous computational psychiatry studies indicated elevated punishment learning rates in patients compared with control individuals. This difference may promote and uphold negative affective bias symptoms and hence constitute a potential mechanistic treatment target for mood and anxiety disorders.

A Predictive Coding Framework for Understanding Major Depression

Predictive coding models of brain processing propose that top-down cortical signals promote efficient neural signaling by carrying predictions about incoming sensory information. These "priors" serve to constrain bottom-up signal propagation where prediction errors are carried via feedforward mechanisms. Depression, traditionally viewed as a disorder characterized by negative cognitive biases, is associated with disrupted reward prediction error encoding and signaling. Accumulating evidence also suggests that depression is characterized by impaired local and long-range prediction signaling across multiple sensory domains. This review highlights the electrophysiological and neuroimaging evidence for disrupted predictive processing in depression. The discussion is framed around the manner in which disrupted generative predictions about the sensorium could lead to depressive symptomatology, including anhedonia and negative bias. In particular, the review focuses on studies of sensory deviance detection and reward processing, highlighting research evidence for both disrupted generative predictions and prediction error signaling in depression. The role of the monoaminergic and glutamatergic systems in predictive coding processes is also discussed. This review provides a novel framework for understanding depression using predictive coding principles and establishes a foundational roadmap for potential future research.

Reward-Related Neural Circuitry in Depressed and Anxious Adolescents: A Human Connectome Project

OBJECTIVE

Although depression and anxiety often have distinct etiologies, they frequently co-occur in adolescence. Recent initiatives have underscored the importance of developing new ways of classifying mental illness based on underlying neural dimensions that cut across traditional diagnostic boundaries. Accordingly, the aim of the study was to clarify reward-related neural circuitry that may characterize depressed-anxious youth.

METHOD

The Boston Adolescent Neuroimaging of Depression and Anxiety Human Connectome Project tested group differences regarding subcortical volume and nucleus accumbens activation during an incentive processing task among 14- to 17-year-old adolescents presenting with a primary depressive and/or anxiety disorder (n = 129) or no lifetime history of mental disorders (n = 64). In addition, multimodal modeling examined predictors of depression and anxiety symptom change over a 6-month follow-up period.

RESULTS

Our findings highlighted considerable convergence. Relative to healthy youth, depressed-anxious adolescents exhibited reduced nucleus accumbens volume and activation following reward receipt. These findings remained when removing all medicated participants (∼59% of depressed-anxious youth). Subgroup analyses comparing anxious-only, depressed-anxious, and healthy youth also were largely consistent. Multimodal modeling showed that only structural alterations predicted depressive symptoms over time.

CONCLUSION

Multimodal findings highlight alterations within nucleus accumbens structure and function that characterize depressed-anxious adolescents. In the current hypothesis-driven analyses, however, only reduced nucleus accumbens volume predicted depressive symptoms over time. An important next step will be to clarify why structural alterations have an impact on reward-related processes and associated symptoms.

Pleasure, Reward Value, Prediction Error and Anhedonia

In order to develop effective treatments for anhedonia we need to understand its underlying neurobiological mechanisms. Anhedonia is conceptually strongly linked to reward processing, which involves a variety of cognitive and neural operations. This chapter reviews the evidence for impairments in experiencing hedonic response (pleasure), reward valuation and reward learning based on outcomes (commonly conceptualised in terms of "reward prediction error"). Synthesising behavioural and neuroimaging findings, we examine case-control studies of patients with depression and schizophrenia, including those focusing specifically on anhedonia. Overall, there is reliable evidence that depression and schizophrenia are associated with disrupted reward processing. In contrast to the historical definition of anhedonia, there is surprisingly limited evidence for impairment in the ability to experience pleasure in depression and schizophrenia. There is some evidence that learning about reward and reward prediction error signals are impaired in depression and schizophrenia, but the literature is inconsistent. The strongest evidence is for impairments in the representation of reward value and how this is used to guide action. Future studies would benefit from focusing on impairments in reward processing specifically in anhedonic samples, including transdiagnostically, and from using designs separating different components of reward processing, formulating them in computational terms, and moving beyond cross-sectional designs to provide an assessment of causality.

Alterations of Static and Dynamic Functional Connectivity of the Nucleus Accumbens in Patients With Major Depressive Disorder

BACKGROUND

Major depressive disorder (MDD) is associated with dysfunction of the reward system. As an important node in the reward system, the resting-state functional connectivity of the nucleus accumbens (NAc) is related to the etiology of MDD. However, an increasing number of recent studies propose that brain activity is dynamic over time, no study to date has examined whether the NAc dynamic functional connectivity (DFC) is changed in patients with MDD. Moreover, few studies have examined the impact of the clinical characteristics of patients with MDD.

METHODS

A total of 220 MDD patients and 159 healthy controls (HCs), group-matched for age, sex, and education level, underwent resting-state functional magnetic resonance imagining (rs-fMRI) scans. Seed-based resting-state functional connectivity (RSFC) and DFC of the NAc were conducted. Two sample t-tests were performed to alter RSFC/DFC of NAc. In addition, we examined the association between altered RSFC/DFC and depressive severity using Pearson correlation. Finally, we divided patients with MDD into different subgroups according to clinical characteristics and tested whether there were differences between the subgroups.

RESULTS

Compared with the HCs, MDD patients show reduced the NAc-based RSFC with the dorsolateral prefrontal cortex (DLPFC), hippocampus, middle temporal gyrus (MTG), inferior temporal gyrus (ITG), precuneus, and insula, and patients with MDD show reduced the NAc-based DFC with the DLPFC, ventromedial prefrontal cortex (VMPFC), ventrolateral prefrontal cortex (VLPFC), MTG, ITG, and insula. MDD severity was associated with RSFC between the NAc and precentral gyrus (r = 0.288, p = 0.002, uncorrected) and insula (r = 0.272, p = 0.003, uncorrected).

CONCLUSION

This study demonstrates abnormal RSFC and DFC between the NAc and distributed cerebral regions in MDD patients, characterized by decreased RSFC and DFC of the NAc connecting with the reward, executive, default-mode, and salience network. Our results expand previous descriptions of the NAc RSFC abnormalities in MDD, and the altered RSFC/DFC may reflect the disrupted function of the NAc.

Anhedonia in Nicotine Dependence

Prior findings indicate that trait anhedonia enhances the likelihood of becoming a tobacco smoker, and preliminary evidence suggests that smoking abstinence leads to anhedonic states in some individuals and situations, and nicotine administration reduces anhedonic states. Nevertheless, many vital questions exist concerning relationships between anhedonia and nicotine dependence, including situational and individual difference factors that may moderate the strength of these associations. This chapter provides a critical review of the literature assessing relationships of anhedonia to nicotine dependence and the effects of acute nicotine through the lenses of the Research Domain Criteria's (RDoC) Positive Valence Systems (NIMH, RDoC changes to the matrix (CMAT) workgroup update: proposed positive valence domain revisions. A report by the national advisory mental health council workgroup on changes to the research domain criteria matrix, 2018) and the Situation x Trait Affective Response (STAR) model of nicotine's effects and nicotine dependence (Gilbert, Smoking individual differences, psychopathology, and emotion. Taylor and Francis, Washington, DC, 1995; Gilbert, Hum Psychopharmacol Clin Exp 12:S89-S102, 1997). The effects of nicotine and nicotine withdrawal on subjective, behavioral, and brain indices vary across the three RDoC Positive Valences Systems (Reward Responsiveness, Reward Learning, and Reward Valuation) in a manner that supports the research and potential clinical utility of using RDoC criteria and the STAR model to guide research and clinical innovation. We provide a revision of the STAR model that incorporates the three RDoC Positive Valence Systems with evidence that nicotine's effects on hedonic and affective processes vary as a function of the dominance/salience of (1) situational hedonic and affective cues and task/active coping cues, and (2) state executive functioning level/capacity and state reward sensitivity such that these effects of nicotine are maximal during states of suboptimal cognitive functioning and reward sensitivity, combined with low situational stimulus salience and low task-related cues/demands.

Anhedonia in Depression and Bipolar Disorder

Anhedonia is a hallmark feature of depression and is highly prevalent among individuals with mood disorders. The history and neurobiology of anhedonia has been most extensively studied in the context of unipolar Major Depressive Disorder (MDD), with converging lines of evidence indicating that marked anhedonia heralds a more chronic and treatment-refractory illness course. Furthermore, findings from neuroimaging studies suggest that anhedonia in MDD is associated with aberrant reward-related activation in key brain reward regions, particularly blunted reward anticipation-related activation in the ventral striatum. However, the ongoing clinical challenge of treating anhedonia in the context of Bipolar Disorder (BD) also highlights important gaps in our understanding of anhedonia's prevalence, severity, and pathophysiology along the entire mood disorder spectrum. In addition, although current theoretical models posit a key role for reward hyposensitivity in BD depression, unlike studies in MDD, studies in BD do not clearly show evidence for reduced reward-related activation in striatal or other brain regions. Although further research is needed, the evidence to date hints at a divergent pathophysiology for anhedonia in unipolar and bipolar mood disorders, which, if better understood, could lead to significant improvements in the diagnosis and treatment of MDD and BD.

Prefrontal cortex and depression

The prefrontal cortex (PFC) has emerged as one of the regions most consistently impaired in major depressive disorder (MDD). Although functional and structural PFC abnormalities have been reported in both individuals with current MDD as well as those at increased vulnerability to MDD, this information has not translated into better treatment and prevention strategies. Here, we argue that dissecting depressive phenotypes into biologically more tractable dimensions - negative processing biases, anhedonia, despair-like behavior (learned helplessness) - affords unique opportunities for integrating clinical findings with mechanistic evidence emerging from preclinical models relevant to depression, and thereby promises to improve our understanding of MDD. To this end, we review and integrate clinical and preclinical literature pertinent to these core phenotypes, while emphasizing a systems-level approach, treatment effects, and whether specific PFC abnormalities are causes or consequences of MDD. In addition, we discuss several key issues linked to cross-species translation, including functional brain homology across species, the importance of dissecting neural pathways underlying specific functional domains that can be fruitfully probed across species, and the experimental approaches that best ensure translatability. Future directions and clinical implications of this burgeoning literature are discussed.