Apathy is a highly prevalent and disabling neuropsychiatric syndrome, but its multi-dimensional structure is a challenge for progress towards better identification and treatment. A crucial unresolved question is whether social disengagement reflects a distinct deficit in social motivation or a by-product of diminished initiative or emotional blunting. Previous studies have been constrained by modest sample sizes and limited use of apathy-specific instruments or phenotypically narrow cohorts. Here, we analysed item-level data from 11,243 individuals recruited across multiple centres, including 1154 neurological patients with Alzheimer’s disease, Parkinson’s disease, frontotemporal dementia, autoimmune encephalitis and small vessel disease, alongside people with depression and healthy adults. Across exploratory and confirmatory factor analyses, symptom-level network modelling, and lifespan analyses, social apathy consistently emerged as a coherent and separable dimension. This pattern was preserved across health, psychiatric, and neurocognitive cohorts, from adolescence through late life. Recognising social apathy as an independent domain reframes a central aspect of mental health—the motivation to connect, care, and act for others—and provides a foundation for more precise assessment and for interventions targeting both social and neurobiological mechanisms.

Background:Anhedonia-a core symptom of Major Depressive Disorder-is associated with poorer clinical outcomes, lower quality of life, and disrupted reward processing. However, putative relationships among self-reported anhedonia, well-being and anhedonic phenotypes (specifically, reward learning) remain largely unexplored. The main goal of the current study was to fill this gap in a large online adult community sample (N = 478). Methods:To evaluate how different approaches to assessing anhedonia may capture these relationships, we administered the Probabilistic Reward Task (PRT) to probe reward learning and two clinical scales: the Snaith-Hamilton Pleasure Scale (SHAPS) and the Dimensional Anhedonia Rating Scale (DARS). In a first step, the SHAPS was administered to identify anhedonic vs. non-anhedonic individuals, who then performed an online PRT. Results:Both scales were significantly associated with lower self-reported quality of life (QoL), as measured by the Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (QLESQ-SF), with the SHAPS showing a stronger relationship to both QoL and reward learning. Follow-up computational modeling indicated the anhedonic group showed a significantly higher level of uncertainty while completing the PRT compared to the non-anhedonic group. Moreover, trial-by-trial analyses revealed group differences in PRT response patterns, such that anhedonic individuals were less likely to incorrectly indicate that they had seen the more frequently rewarded "rich" stimulus on trials that actually presented the less frequently rewarded "lean" stimulus. Conclusions:Findings highlight the utility of combining subjective and behavioral measures to better understand the impact of anhedonia on daily functioning and reinforcement learning processes.

BACKGROUND:Anhedonia and rumination, a form of repetitive negative thinking (RNT), are key features of depression associated with poor treatment outcomes, chronic disease progression, and an increased risk of suicidality. Although their interaction is thought to sustain depressive states, the state-level mechanisms linking these symptoms remain poorly understood. METHODS:In this multilevel, randomized within-subjects study, 62 individuals (n = 38 females) with varying levels of depressive symptoms completed the Probabilistic Reward Task (PRT) under two conditions: experimentally induced RNT and an active control. Concurrent electroencephalography was employed to assess electroencephalographic markers of reward functioning. RESULTS:RNT significantly attenuated both reward response bias and feedback-related positivity (FRP) amplitudes, with the most pronounced effects in individuals with more severe depressive symptoms. These effects were not attributable to differences in task difficulty or perceptual cortical processing of PRT stimuli, supporting the specificity of RNT's impact on reward-related processes. CONCLUSIONS:RNT may transiently disrupt behavioral and neural indicators of reward functioning. These findings suggest that cognitive states such as RNT can exacerbate or reveal the latent reward-processing deficits typically observed in individuals with anhedonia. This state-dependent sensitivity highlights the potential utility of targeting RNT to restore reward processing in depression.

Processing uncertainty may be pathognomonic (characteristic of a disease) for some psychiatric conditions. Some people expect the world to change, even when it doesn’t. This tendency is central to paranoia, where individuals often anticipate threat or change without clear evidence. But what determines whether these beliefs translate into behavior? One possibility is that metacognitive structure – the coherence and depth with which one articulates their own thinking – acts as a buffer. An agent may endorse a belief but have sufficient accessory hypotheses to insulate it from action. To test this, we used metacognitive prompting in GPT-4 to score individual reflections on open-ended questions (e.g., did you use any particular strategy?) after completing a probabilistic reversal learning task. Individuals with higher paranoia demonstrate lower metacognitive structure (t = 5.98, p < 0.001), with metacognition attenuating the relationship between volatility belief and switching behavior (Δ = –15 pp, p < 0.001) even after controlling for reflection verbosity and general cognitive ability. These findings suggest that metacognition protects against uncertainty-driven instability, pointing to a key mechanism by which reflection protects against cognition under change. This work provides a novel framework to measure metacognition from behavioral task debrief questions.

BACKGROUND:Apathy, depression and anhedonia are clinically overlapping constructs, which hinders diagnostic clarity and treatment development. This study aimed to comprehensively characterise these syndromes to identify a core set of non-redundant symptoms that maximally dissociate them and to investigate the psychological nature of key distinguishing features. METHODS:Data from seven datasets (N=4578) of healthy individuals and patients with major depressive disorder were analysed using the Apathy Motivation Index, Beck Depression Inventory and Snaith-Hamilton Pleasure Scale. A machine-learning algorithm identified the most informative, non-redundant items for dissociating 'pure' apathy, depression and anhedonia. The nature of emotional apathy was further investigated with follow-up studies. RESULTS:Although substantial symptom overlap existed, 'pure' syndromes were present. Factor analysis revealed a robust five-factor structure, separating depression, anhedonia and three distinct apathy domains (behavioural, social and emotional). Machine learning identified 10 core symptoms that differentiated the pure syndromes with high accuracy (area under the curve >0.90) and could also identify well the presence of each syndrome in individuals suffering from two or more syndromes. Emotional apathy negatively correlated with depression and was specifically associated with reduced affective empathy and a diminished sensitivity to the intensity of negative facial emotions, rather than with alexithymia or antidepressant-induced emotional blunting. CONCLUSIONS:Apathy, depression and anhedonia are dissociable constructs with distinct symptom signatures. Emotional apathy is a unique dimension which provides a novel target for research. A 10-item Apathy-Depression-Anhedonia Measure developed here provides a pragmatic tool for rapid, precise phenotyping to guide more personalised therapeutic strategies.

Past research on option generation, the mental process of creating possible courses of action for goal-directed behaviors, focused extensively on the outcomes of the process, specifically, the quantity and quality of options generated. Accordingly, various effects were introduced to describe and categorize observed trends in option properties, yet these studies utilize differing task designs. This paper focuses on the "quantity-breeds-quality", "less-is-more", and the concomitant "Take The First" (TTF) heuristics. We conducted a secondary analysis of data from a culture-free, education-independent, and quantitative option generation task and compared the results to those predicted by the heuristics to discuss how study characteristics are well-aligned with the heuristics they investigate. To bolster ecological validity and reflect a more diverse range of cognitive experiences beyond the neurotypical population, 44 healthy individuals and 54 patients with Major Depressive Disorder were asked to generate as many different paths as they could between two fixed points on a touchscreen computer in 1.5 min, and the generated options were quantified based on three metrics of interest: fluency, uniqueness, and diversity. For both groups, the mean uniqueness, maximum uniqueness, and diversity of an individual's paths were negatively correlated with an increase in fluency, in line with the less-is-more effect yet conflicting with the results predicted by the quantity-breeds-quality effect. In addition, normalized path uniqueness decreased with the path index, contrary to the results predicted by the TTF heuristic. The results were analyzed with reference to the three heuristics, to discuss possible task characteristics that cause a particular heuristic to apply, and demonstrate the fundamental differences between real-life decision-making scenarios and knowledge-independent tasks.

Background: Exposure to adversity, including unpredictable environments, during early life is associated with neuropsychiatric illness in adulthood. One common factor in this sequela is anhedonia, the loss of responsivity to previously reinforcing stimuli. To accelerate the development of new treatment strategies for anhedonic disorders induced by early-life adversity, animal models have been developed to capture critical features of early-life stress and the behavioral deficits that such stressors induce. We have previously shown that rats exposed to the limited bedding and nesting protocol exhibited blunted reward responsivity in the probabilistic reward task, a touchscreen-based task reverse translated from human studies. Methods: To test the quantitative limits of this translational platform, we examined the ability of Bayesian computational modeling and probability analyses identical to those optimized in previous human studies to quantify the putative mechanisms that underlie these deficits with precision. Specifically, 2 parameters that have been shown to independently contribute to probabilistic reward task outcomes in patient populations, reward sensitivity and learning rate, were extracted, as were trial-by-trial probability analyses of choices as a function of the preceding trial. Results: Significant deficits in reward sensitivity, but not learning rate, contributed to the anhedonic phenotypes in rats exposed to early-life adversity. Conclusions: The current findings confirm and extend the translational value of these rodent models by verifying the effectiveness of computational modeling in distinguishing independent features of reward sensitivity and learning rate that complement the probabilistic reward task’s signal detection end points. Together, these metrics serve to objectively quantify reinforcement learning deficits associated with anhedonic phenotypes.

The neurobiological mechanisms underlying the placebo phenomenon in patients with major depressive disorder (MDD) remain largely unknown. The progressive rise in rates of placebo responses within clinical trials over the past two decades may impede the detection of a true signal and thus present a major obstacle in new treatment development. Understanding the mechanisms would have several important implications, including (1) identifying biomarkers of placebo responders (thereby identifying those individuals who could benefit therapeutically from such interventions), (2) opening new avenues for manipulating such mechanisms to maximize symptom reduction, and (3) refining treatments with approaches that decrease (in clinical trials) or increase (in clinical practice) the placebo response. Here we investigated the research question: is the dopaminergic system one of the neurobiological underpinnings of the placebo response within MDD? Inspired by preclinical and clinical findings that have implicated dopamine in the occurrence, prediction, and expectation of reward, we hypothesized that dopaminergic activity in the mesolimbic system is a critical mediator of placebo response in MDD. To test this hypothesis, we designed a double-blind, placebo-controlled, sequential parallel comparison design clinical trial aimed at maximizing placebo antidepressant response. We integrated behavioral, imaging, and hemodynamic probes of mesocorticolimbic dopaminergic pathways within the context of manipulations of psychological constructs previously linked to placebo responses (e.g., expectation of improvement). The aim of this manuscript is to present the rationale of the study design and to demonstrate how a cross-modal methodology may be utilized to investigate the role of reward circuitry in placebo response in MDD.

BACKGROUND: Loneliness and social isolation have detrimental consequences for mental health and act as vulnerability factors for the development of depressive symptoms, such as anhedonia. The mitigation strategies used to contain COVID-19, such as social distancing and lockdowns, allowed us to investigate putative associations between daily objective and perceived social isolation and anhedonic-like behavior. METHODS: Reward-related functioning was objectively assessed using the Probabilistic Reward Task. A total of 114 unselected healthy individuals (71% female) underwent both a laboratory and an ecological momentary assessment. Computational modeling was applied to performance on the Probabilistic Reward Task to disentangle reward sensitivity and learning rate. RESULTS: Findings revealed that objective, but not subjective, daily social interactions were associated with motivational behavior. Specifically, higher social isolation (less time spent with others) was associated with higher responsivity to rewarding stimuli and a reduced influence of a given reward on successive behavioral choices. CONCLUSIONS: Overall, the current results broaden our knowledge of the potential pathways that link (COVID-19- related) social isolation to altered motivational functioning.

The Probabilistic Reward Task (PRT) is widely used to investigate the impact of Major Depressive Disorder (MDD) on reinforcement learning (RL), and recent studies have used it to provide insight into decision-making mechanisms affected by MDD. The current project used PRT data from unmedicated, treatment-seeking adults with MDD to extend these efforts by: (1) providing a more detailed analysis of standard PRT metrics—response bias and discriminability—to better understand how the task is performed; (2) analyzing the data with two computational models and providing psychometric analyses of both; and (3) determining whether response bias, discriminability, or model parameters predicted responses to treatment with placebo or the atypical antidepressant bupropion. Analysis of standard metrics replicated recent work by demonstrating a dependency between response bias and response time (RT), and by showing that reward totals in the PRT are governed by discriminability. Behavior was well-captured by the Hierarchical Drift Diffusion Model (HDDM), which models decision-making processes; the HDDM showed excellent internal consistency and acceptable retest reliability. A separate “belief” model reproduced the evolution of response bias over time better than the HDDM, but its psychometric properties were weaker. Finally, the predictive utility of the PRT was limited by small samples; nevertheless, depressed adults who responded to bupropion showed larger pre-treatment starting point biases in the HDDM than non-responders, indicating greater sensitivity to the PRT’s asymmetric reinforcement contingencies. Together, these findings enhance our understanding of reward and decision-making mechanisms that are implicated in MDD and probed by the PRT.

Deficits in motivational functioning including impairments in reward learning or reward sensitivity are common in psychiatric disorders characterized by anhedonia. Recently, anhedonic symptoms have been exacerbated by the pandemic caused by the Coronavirus disease 2019 (COVID-19) in the general population. The present study examined the putative associations between loss of smell (anosmia) and taste (ageusia) sensitivity, irrespective of COVID-19 infection, and anhedonia, measured by a signal-detection task probing the ability to modify behavior as a function of rewards (Probabilistic Reward Task; PRT). Tonic heart rate variability (HRV) was included in the model, due to its association with both smell and taste sensitivity as well as motivational functioning. The sample included 114 healthy individuals (81 females; mean age 22.2 years), who underwent a laboratory session in which dispositional traits, resting HRV and PRT performance were assessed, followed by a 4-days ecological momentary assessment to obtain daily measures of anosmia and ageusia. Lower levels of tonic HRV and lower momentary levels of smell and taste sensitivity were associated with impaired reward responsiveness and ability to shape future behavioral choices based on prior reinforcement experiences. Overall, the current results provide initial correlational evidence that could be fruitfully used to inform future experimental investigations aimed at elucidating the disruptive worldwide mental health consequences triggered by the pandemic.

Childhood-onset depression has adverse consequences that are sustained into adulthood, which increases the significance of detection in early childhood. The Children's Depression Inventory (CDI) is used globally in evaluating depressive symptom severity in adolescents, and its second version, the CDI-2, was developed by taking into account advances in childhood depression research. Prior research has reported inconsistencies in its factor structure across populations. In addition, the CDI-2 has not yet been empirically validated with Southeast Asian populations. This study sought to empirically validate the CDI-2's psychometric properties and evaluate its factorial structure with a Singaporean community sample of non-clinical respondents. A total sample of 730 Singaporean children aged between 8.5 and 10.5 years was used. Psychometric properties of the CDI-2, including internal consistency as well as convergent and discriminant validity, were assessed. Factor analyses were conducted to assess the developers' original two-factor structure for a Southeast Asian population. This two-factor structure was not supported in our sample. Instead, the data provided the best fit for a hierarchical two-factor structure with factors namely, socio-emotional problems and cognitive-behavioural problems. This finding suggests that socio-cultural and demographic elements influence interpretation of depressive symptoms and therefore the emerging factor structure of the construct under scrutiny. This study highlights the need to further examine the CDI-2 and ensure that its interpretation is culture-specific. More qualitative work could also bring to light the idiosyncratic understanding of depressive symptomatology, which would then guide culture-specific validation of the CDI-2.

Abstract Background The association between major depressive disorder and motivation to invest cognitive effort for rewards is unclear. One reason might be that prior tasks of cognitive effort-based decision-making are limited by potential confounds such as physical effort and temporal delay discounting. Methods To address these interpretive challenges, we developed a new task – the Cognitive Effort Motivation Task – to assess one's willingness to exert cognitive effort for rewards. Cognitive effort was manipulated by varying the number of items (1, 2, 3, 4, 5) kept in spatial working memory. Twenty-six depressed patients and 44 healthy controls went through an extensive learning session where they experienced each possible effort level 10 times. They were then asked to make a series of choices between performing a fixed low-effort-low-reward or variable higher-effort-higher-reward option during the task. Results Both groups found the task more cognitively (but not physically) effortful when effort level increased, but they still achieved ⩾80% accuracy on each effort level during training and >95% overall accuracy during the actual task. Computational modelling revealed that a parabolic model best accounted for subjects' data, indicating that higher-effort levels had a greater impact on devaluing rewards than lower levels. These procedures also revealed that MDD patients discounted rewards more steeply by effort and were less willing to exert cognitive effort for rewards compared to healthy participants. Conclusions These findings provide empirical evidence to show, without confounds of other variables, that depressed patients have impaired cognitive effort motivation compared to the general population.

Option generation is a critical process in decision making, but previous studies have largely focused on choices between options given by a researcher. Consequently, how we self-generate options for behaviour remain poorly understood. Here, we investigated option generation in major depressive disorder and how dopamine might modulate this process, as well as the effects of modafinil (a putative cognitive enhancer) on option generation in healthy individuals. We first compared differences in self-generated options between healthy non-depressed adults [n = 44, age = 26.3 years (SD 5.9)] and patients with major depressive disorder [n = 54, age = 24.8 years (SD 7.4)]. In the second study, a subset of depressed individuals [n = 22, age = 25.6 years (SD 7.8)] underwent PET scans with 11C-raclopride to examine the relationships between dopamine D2/D3 receptor availability and individual differences in option generation. Finally, a randomized, double-blind, placebo-controlled, three-way crossover study of modafinil (100 mg and 200 mg), was conducted in an independent sample of healthy people [n = 19, age = 23.2 years (SD 4.8)] to compare option generation under different doses of this drug. The first study revealed that patients with major depressive disorder produced significantly fewer options [t(96) = 2.68, P = 0.009, Cohen's d = 0.54], albeit with greater uniqueness [t(96) = -2.54, P = 0.01, Cohen's d = 0.52], on the option generation task compared to healthy controls. In the second study, we found that 11C-raclopride binding potential in the putamen was negatively correlated with fluency (r = -0.69, P = 0.001) but positively associated with uniqueness (r = 0.59, P = 0.007). Hence, depressed individuals with higher densities of unoccupied putamen D2/D3 receptors in the putamen generated fewer but more unique options, whereas patients with lower D2/D3 receptor availability were likely to produce a larger number of similar options. Finally, healthy participants were less unique [F(2,36) = 3.32, P = 0.048, partial η2 = 0.16] and diverse [F(2,36) = 4.31, P = 0.021, partial η2 = 0.19] after taking 200 mg versus 100 mg and 0 mg of modafinil, while fluency increased linearly with dosage at a trend level [F(1,18) = 4.11, P = 0.058, partial η2 = 0.19]. Our results show, for the first time, that option generation is affected in clinical depression and that dopaminergic activity in the putamen of patients with major depressive disorder may play a key role in the self-generation of options. Modafinil was also found to influence option generation in healthy people by reducing the creativity of options produced.