Anhedonia and depression symptoms have been linked to potential deficits in reward learning. However, how anhedonia impacts the ability to adjust and learn about the effort required to obtain rewards remains unclear.

We examined young people (N = 155, 16–25 years) with a range of depression and anhedonia symptoms using a probabilistic instrumental reward and effort learning task. Participants were asked to learn which options to choose to maximize reward or minimize effort for reward. We compared the exerted effort (button pressing speed) for high (puppy images) vs low (dog images) rewards and collected subjective reports of “liking,” “wanting,” and “willingness to exert effort.” Computational models were fit to the learning data and estimated parameter values were correlated with depression and anhedonia symptoms.

As depression symptoms and consummatory anhedonia increased, reward liking decreased, and as anticipatory anhedonia increased, liking, wanting, and willingness to exert effort for reward decreased.

Participants exerted more effort for high rewards than for low rewards, but anticipatory anhedonia diminished this difference.

Higher consummatory anhedonia was associated with poorer reward and effort learning, and with increased temperature parameter values for both learning types, indicating a higher tendency to make exploratory choices. Higher depression symptoms were associated with lower reward learning accuracy.

We provide novel evidence that anhedonia is associated with difficulties in modulating effort as a function of reward value and with the underexploitation of low effort and high reward options. We suggest that addressing these impairments could be a novel target for intervention in anhedonic young people.

Depression is characterized by divergent changes in positive and negative affect. Emerging roles of inflammation in depression portend avenues for novel immunomodulator-based monotherapy, targeting mechanistically distinct symptoms such as anhedonia and pessimism.

To investigate links between these divergent affective components and inflammation, we used a probabilistic reinforcement-learning fMRI paradigm, testing for evidence of hyposensitivity to reward, and hypersensitivity to punishment in low-inflammation depression cases (loCRP depression; CRP ≤ 3 mg/L; N = 48), high-inflammation depression cases (hiCRP depression; CRP > 3 mg/L; N = 31), and healthy controls (HC; CRP ≤ 3 mg/L; N = 45). We aimed to (i) determine whether depression cases with high and low inflammation showed aberrant neural activation to monetary gains and losses compared to controls, and (ii) examine if these alterations correlated with a continuous measure of C-reactive protein (CRP) in depression, as well as indices of anhedonia and pessimism derived from behavioral instruments in depression.

Voxel-wise activation was observed in key brain regions sensitive to monetary reward (ventromedial prefrontal cortex, vmPFC; nucleus accumbens, NAc) and punishment (insula) outcomes across all three groups. However, there was no significant difference in activation between groups. Within depression cases, increasing CRP scaled negatively with activation in the right vmPFC and left NAc but not insula cortex. However, there was no significant association between regional activation and severity of anhedonia or pessimism.

Our results support the previously reported association between CRP and striatal reward reactivity in depression but do not extend this to processing of negatively valenced information.

Motivational dysfunction is a core feature of depression and can have debilitating effects on everyday function. However, it is unclear which cognitive processes underlie impaired motivation and whether impairments persist following remission. Decision-making concerning exerting effort to obtain rewards offers a promising framework for understanding motivation, especially when examined with computational tools.

Effort-based decision-making was assessed using the Apple Gathering Task, where participants decide whether to exert effort via a grip-force device to obtain varying levels of reward; effort levels were individually calibrated and varied parametrically. We present a comprehensive computational analysis of decision-making, initially validating our model in healthy volunteers (N = 67), before applying it in a case–control study including current (N = 41) and remitted (N = 46) unmedicated depressed individuals and healthy volunteers with (N = 36) and without (N = 57) a family history of depression.

Four fundamental computational mechanisms that drive patterns of effort-based decisions, which replicated across samples, were identified: overall bias to accept effort challenges; reward sensitivity; and linear and quadratic effort sensitivity. Traditional model-agnostic analyses showed that both depressed groups showed lower willingness to exert effort. In contrast with previous findings, computational analysis revealed that this difference was primarily driven by lower effort-acceptance bias, but not altered effort or reward sensitivity.

This work provides insight into the computational mechanisms underlying motivational dysfunction in depression. Lower willingness to exert effort could represent a trait-like factor contributing to symptoms and a fruitful target for treatment and prevention.

Anhedonia, a transdiagnostic feature common to both Major Depressive Disorder (MDD) and Schizophrenia (SCZ), is characterized by abnormalities in hedonic experience. Previous studies have used machine learning (ML) algorithms without focusing on disorder-specific characteristics to independently classify SCZ and MDD. This study aimed to classify MDD and SCZ using ML models that integrate components of hedonic processing.

We recruited 99 patients with MDD, 100 patients with SCZ, and 113 healthy controls (HC) from four sites. The patient groups were allocated to distinct training and testing datasets. All participants completed a modified Monetary Incentive Delay (MID) task, which yielded features categorized into five hedonic components, two reward consequences, and three reward magnitudes. We employed a stacking ensemble model with SHapley Additive exPlanations (SHAP) values to identify key features distinguishing MDD, SCZ, and HC across binary and multi-class classifications.

The stacking model demonstrated high classification accuracy, with Area Under the Curve (AUC) values of 96.08% (MDD versus HC) and 91.77% (SCZ versus HC) in the main dataset. However, the MDD versus SCZ classification had an AUC of 57.75%. The motivation reward component, loss reward consequence, and high reward magnitude were the most influential features within respective categories for distinguishing both MDD and SCZ from HC (p < 0.001). A refined model using only the top eight features maintained robust performance, achieving AUCs of 96.06% (MDD versus HC) and 95.18% (SCZ versus HC).

The stacking model effectively classified SCZ and MDD from HC, contributing to understanding transdiagnostic mechanisms of anhedonia.

Diagnostic accuracy is an unmet need for major depressive disorder (MDD) and major depressive episode (MDE) in bipolar disorder. Very limited research has evaluated bipolar disorder/MDE and MDD using ecological momentary assessment (EMA) time-series data.

We aimed to examine differentiating phenomenological characteristics in positive affect dynamics, and temporal relationships with pleasure towards current activity and meaning in life (MIL), among MDD, MDE/bipolar disorder and healthy controls using EMA.

Participants (N = 88, mean age 28.7 years, 69% female), including individuals with MDD (n = 29) and MDE/bipolar disorder (n = 29) and healthy controls (n = 30), were assessed for positive affect, pleasure and MIL 5 times daily over a 2-week period. Multilevel modelling analysis was conducted, with estimation of first-order autoregressive model structure and time-lagged relationship between pleasure and positive affect.

From 4632 EMA observations, positive affect dynamics (inertia, variability and instability) did not differ significantly across groups (all P > 0.05). Although all groups demonstrated a bidirectional relationship between positive affect and pleasure, for MDE/bipolar disorder, both pleasuret − 1 (β = −0.11, t[51.09] = −2.31, P = 0.025) and positive affectt − 1 (β = −0.13, t[56.54] = −2.30, P = 0.025) predicted subsequent MIL less significantly than for MDD and healthy controls.

Individuals with MDE/bipolar disorder, but not MDD, had less self-reported MIL from positive affect and pleasure. There is little evidence that emotional experience alone characterises the pathophysiology between MDD and MDE/bipolar disorder; such investigation may be limited by within-group heterogeneity. Our findings provide a new perspective on using a time-series approach beyond bimodal measures in EMA to differentiate bipolar disorder/MDE and MDD.

Elucidation of transphasic mechanisms (i.e., mechanisms that occur across illness phases) underlying negative symptoms could inform early intervention and prevention efforts and additionally identify treatment targets that could be effective regardless of illness stage. This study examined whether a key reinforcement learning behavioral pattern characterized by reduced difficulty learning from rewards that have been found to underlie negative symptoms in those with a schizophrenia diagnosis also contributes to negative symptoms in those at clinical high-risk (CHR) for psychosis.

CHR youth (n = 46) and 51 healthy controls (CN) completed an explicit reinforcement learning task with two phases. During the acquisition phase, participants learned to select between pairs of stimuli probabilistically reinforced with feedback indicating receipt of monetary gains or avoidance of losses. Following training, the transfer phase required participants to select between pairs of previously presented stimuli during the acquisition phase and novel stimuli without receiving feedback. These test phase pairings allowed for inferences about the contributions of prediction error and value representation mechanisms to reinforcement learning deficits.

In acquisition, CHR participants displayed impaired learning from gains specifically that were associated with greater negative symptom severity. Transfer performance indicated these acquisition deficits were largely driven by value representation deficits. In addition to negative symptoms, this profile of deficits was associated with a greater risk of conversion to psychosis and lower functioning.

Impairments in positive reinforcement learning, specifically effectively representing reward value, may be an important transphasic mechanism of negative symptoms and a marker of psychosis liability.

Ultrasonic vocalisations (USVs) emitted by rats may reflect affective states. Specifically, 50 kHz calls emitted during juvenile playing are associated with positive affect. Given that depression is characterised by profound alterations in this domain, we proposed that USV calls may configure a suitable tool for assessing depressive-like states. Utilising the Flinders Sensitive Line (FSL), a well-established animal model of depression, we assessed USV calls emitted by rats during tickling, a procedure based on juvenile rats’ rough-and-tumble play.

Juvenile FSL rats and their control counterparts, the Flinders Resistant Line (FRL) and Sprague Dawley, were submitted to tickling sessions to imitate rats playing behaviour. The rats were tickled daily for 6 weeks starting at PND21. Tickling sessions were recorded for further acoustic analysis of 50 kHz calls.

Tickling increased 50 kHz calls in all the strains. FSL rats emitted more calls than control strains and exhibited a higher number of flat-trill combination calls.

Tickling is a robust method for inducing 50 kHz USV calls. Analysing USV calls emitted during tickling configurates a suitable method for studying affective states relevant to depression. FSL rats did not present anhedonia but rather higher reward sensitivity, which may underlie their stress vulnerability.

Few previous studies have established Snaith–Hamilton Pleasure Scale (SHAPS) cut-off values using receiver operating characteristic curve analysis and applied these values to compare predictors of anhedonia between clinical and nonclinical groups.

To determine the optimal cut-off values for the SHAPS and use them to identify predictors of anhedonia in clinical and nonclinical groups in Taiwan.

This cross-sectional and correlational study used convenience sampling to recruit 160 patients from three hospitals and 412 students from two universities in northern Taiwan. Data analysis included receiver operating characteristic curve, univariate and multivariate analyses.

The optimal SHAPS cut-off values were 29.5 and 23.5 for the clinical and nonclinical groups, respectively. Moreover, two-stage analysis revealed that participants in the clinical group who perceived themselves as nondepressed, and participants in the nonclinical group who did not skip classes and whose fathers exhibited higher levels of care and protection were less likely to attain the cut-off values. Conversely, participants in the nonclinical group who reported lower academic satisfaction and were unwilling to seek help from family or friends were more likely to attain the cut-off values.

Our findings highlight the importance of optimal cut-off values in screening for depression risk within clinical and nonclinical groups. Accordingly, the development of comprehensive, individualised programmes to monitor variation trends in SHAPS scores and relevant predictors of anhedonia across different target populations is crucial.

Serotonin norepinephrine reuptake inhibitors (SNRIs) have been postulated to afford benefits in alleviating anhedonia and amotivation. This post hoc pooled analysis evaluated the effect of venlafaxine XR, an SNRI, on these symptoms in patients with major depressive disorder (MDD).

Data was pooled from five short-term randomized, placebo-controlled studies of venlafaxine XR for the treatment of MDD, comprising 1087 (venlafaxine XR, n = 585; placebo, n = 502) adult subjects. The change from baseline score in the MADRS anhedonia factor (based on items 1 [apparent sadness], 2 [reported sadness], 6 [concentration difficulties], 7 [lassitude], and 8 [inability to feel]) for anhedonia, and in motivational deficits (based on 3 items of HAM-D17: involvement in work and activities, psychomotor retardation, and energy level [ie, general somatic symptoms]) for amotivation, were measured through 8 weeks. Mixed model repeated measures (MMRMs) were used to analyze changes over time and ANCOVA to analyze the change from baseline at week 8 with LOCF employed to handle missing data.

At the end of 8 weeks, the change from baseline was significantly greater in patients on venlafaxine XR in both anhedonia (mean, 95% CI: −2.73 [−3.63, −1.82], p < 0.0001) and amotivation scores (mean, 95% CI: −0.78 [−1.04, −0.52], p < 0.0001) than those on placebo. For both measures, the between-group separation from baseline was statistically significant starting from week 2 onwards, and it increased over time.

This analysis demonstrates that venlafaxine XR is effective in improving symptoms of anhedonia and motivational deficits in patients with MDD.

Identifying neuroimaging biomarkers of antidepressant response may help guide treatment decisions and advance precision medicine.

To examine the relationship between anhedonia and functional neurocircuitry in key reward processing brain regions in people with major depressive disorder receiving aripiprazole adjunct therapy with escitalopram.

Data were collected as part of the CAN-BIND-1 study. Participants experiencing a current major depressive episode received escitalopram for 8 weeks; escitalopram non-responders received adjunct aripiprazole for an additional 8 weeks. Functional magnetic resonance imaging (on weeks 0 and 8) and clinical assessment of anhedonia (on weeks 0, 8 and 16) were completed. Seed-based correlational analysis was employed to examine the relationship between baseline resting-state functional connectivity (rsFC), using the nucleus accumbens (NAc) and anterior cingulate cortex (ACC) as key regions of interest, and change in anhedonia severity after adjunct aripiprazole.

Anhedonia severity significantly improved after treatment with adjunct aripiprazole.

There was a positive correlation between anhedonia improvement and rsFC between the ACC and posterior cingulate cortex, ACC and posterior praecuneus, and NAc and posterior praecuneus. There was a negative correlation between anhedonia improvement and rsFC between the ACC and anterior praecuneus and NAc and anterior praecuneus.

Eight weeks of aripiprazole, adjunct to escitalopram, was associated with improved anhedonia symptoms. Changes in functional connectivity between key reward regions were associated with anhedonia improvement, suggesting aripiprazole may be an effective treatment for individuals experiencing reward-related deficits. Future studies are required to replicate our findings and explore their generalisability, using other agents with partial dopamine (D2) agonism and/or serotonin (5-HT2A) antagonism.

Aberrant reward functioning is implicated in depression. While attention precedes behavior and guides higher-order cognitive processes, reward learning from an attentional perspective – the effects of prior reward-learning on subsequent attention allocation – has been mainly overlooked.

The present study explored the effects of reward-based attentional learning in depression using two separate, yet complimentary, studies. In study 1, participants with high (HD) and low (LD) levels of depression symptoms were trained to divert their gaze toward one type of stimuli over another using a novel gaze-contingent music reward paradigm – music played when fixating the desired stimulus type and stopped when gazing the alternate one. Attention allocation was assessed before, during, and following training. In study 2, using negative reinforcement, the same attention allocation pattern was trained while substituting the appetitive music reward for gazing the desired stimulus type with the removal of an aversive sound (i.e. white noise).

In study 1 both groups showed the intended shift in attention allocation during training (online reward learning), while generalization of learning at post-training was only evident among LD participants. Conversely, in study 2 both groups showed post-training generalization. Results were maintained when introducing anxiety as a covariate, and when using a more powerful sensitivity analysis. Finally, HD participants showed higher learning speed than LD participants during initial online learning, but only when using negative, not positive, reinforcement.

Deficient generalization of learning characterizes the attentional system of HD individuals, but only when using reward-based positive reinforcement, not negative reinforcement.

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.

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

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.

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.

Abnormal reward functioning is central to anhedonia and amotivation symptoms of schizophrenia (SCZ). Reward processing encompasses a series of psychological components. This systematic review and meta-analysis examined the brain dysfunction related to reward processing of individuals with SCZ spectrum disorders and risks, covering multiple reward components.

After a systematic literature search, 37 neuroimaging studies were identified and divided into four groups based on their target psychology components (i.e. reward anticipation, reward consumption, reward learning, effort computation). Whole-brain Seed-based d Mapping (SDM) meta-analyses were conducted for all included studies and each component.

The meta-analysis for all reward-related studies revealed reduced functional activation across the SCZ spectrum in the striatum, orbital frontal cortex, cingulate cortex, and cerebellar areas. Meanwhile, distinct abnormal patterns were found for reward anticipation (decreased activation of the cingulate cortex and striatum), reward consumption (decreased activation of cerebellum IV/V areas, insula and inferior frontal gyri), and reward learning processing (decreased activation of the striatum, thalamus, cerebellar Crus I, cingulate cortex, orbitofrontal cortex, and parietal and occipital areas). Lastly, our qualitative review suggested that decreased activation of the ventral striatum and anterior cingulate cortex was also involved in effort computation.

These results provide deep insights on the component-based neuro-psychopathological mechanisms for anhedonia and amotivation symptoms of the SCZ spectrum.

While studies from the start of the COVID-19 pandemic have described initial negative effects on mental health and exacerbating mental health inequalities, longer-term studies are only now emerging.

In total, 34 465 individuals in the UK completed online questionnaires and were re-contacted over the first 12 months of the pandemic. We used growth mixture modelling to identify trajectories of depression, anxiety and anhedonia symptoms using the 12-month data. We identified sociodemographic predictors of trajectory class membership using multinomial regression models.

Most participants had consistently low symptoms of depression or anxiety over the year of assessments (60%, 69% respectively), and a minority had consistently high symptoms (10%, 15%). We also identified participants who appeared to show improvements in symptoms as the pandemic progressed, and others who showed the opposite pattern, marked symptom worsening, until the second national lockdown. Unexpectedly, most participants showed stable low positive affect, indicating anhedonia, throughout the 12-month period. From regression analyses, younger age, reporting a previous mental health diagnosis, non-binary, or self-defined gender, and an unemployed or a student status were significantly associated with membership of the stable high symptom groups for depression and anxiety.

While most participants showed little change in their depression and anxiety symptoms across the first year of the pandemic, we highlight the divergent responses of subgroups of participants, who fared both better and worse around national lockdowns. We confirm that previously identified predictors of negative outcomes in the first months of the pandemic also predict negative outcomes over a 12-month period.

Anhedonia is a symptom usually, and probably simplistically, defined as the inability to experience pleasure. It is considered one of the core symptoms of depression and a negative symptom of schizophrenia.

We intend to explore whether previous studies found common or dissimilar experiences of anhedonia in depression and schizophrenia.

We performed a review of the published literature on the subject using PubMed. We conducted a search using ‘anhedonia’, ‘schizophrenia’, and ‘depression’ as keywords.

There is different and diverging evidence on the matter. Historical reports associated schizophrenia with trait anhedonia, and depression with state anhedonia. More recently, some authors correlated appetitive anhedonia (lack of interest/desire) with schizophrenia, and consummatory anhedonia (lack of pleasure/enjoyment) with depression, but this was not corroborated by other studies. However, in line with it, there are findings of a normal physiological response to pleasurable stimuli among schizophrenics. Some authors propose that, in schizophrenia, this symptom might not represent an inability to feel pleasure but rather a deficient expression of its experience, as a part of blunted affect. Reward models highlight a deficit in reward learning in depression, but disorganization of reward processing and a focus on irrelevant clues in schizophrenia, which prevent patients from pursuing a pleasurable experience.

There are still limited studies comparing the experience of anhedonia in depression and schizophrenia. There seem to be significant differences between the two, but further studies are needed. In particular, this could be important in screening schizophrenic patients for depression.

No significant relationships.