Our results indicate that young females with high levels of depression symptoms expect to respond less positively to social situations and engage less in helping behaviour compared to those with low depressive symptomatology. Social anhedonia in depression may thus contribute to decreased engagement in rewarding social situations. This, in turn, may lead to social withdrawal and might maintain depression symptoms though a lack of exposure to positive social feedback.

Background Several studies have reported diminished learning from non-social outcomes in depressed individuals. However, it is not clear how depression impacts learning from social feedback. Notably, mood disorders are commonly associated with deficits in social functioning, which raises the possibility that potential impairments in social learning may negatively affect real-life social experiences in depressed subjects. Methods Ninety-two participants with high (HD; N = 40) and low (LD; N = 52) depression scores were recruited. Subjects performed a learning task, during which they received monetary outcomes or social feedback which they were told came from other people. Additionally, participants answered questions about their everyday social experiences. Computational models were fit to the data and model parameters were related to social experience measures. Results HD subjects reported a reduced quality and quantity of social experiences compared to LD controls, including an increase in the amount of time spent in negative social situations. Moreover, HD participants showed lower learning rates than LD subjects in the social condition of the task. Interestingly, across all participants, reduced social learning rates predicted higher amounts of time spent in negative social situations, even when depression scores were controlled for. Conclusion These findings indicate that deficits in social learning may affect the quality of everyday social experiences. Specifically, the impaired ability to use social feedback to appropriately update future actions, which was observed in HD subjects, may lead to suboptimal interpersonal behavior in real life. This, in turn, may evoke negative feedback from others, thus bringing about more unpleasant social encounters.

The increasing global prevalence of dementia and the lack of disease-modifying treatments give rise to the need for early detection of dementia-causing diseases to enable the development and targeted administration of preventative interventions. However, current methods that have potential for the early detection of dementia-causing diseases, such as positron emission tomography or cerebrospinal fluid sampling, are invasive and costly, which constitutes a barrier to the large-scale assessment of dementia risk. The Early Detection of Neurodegenerative diseases (EDoN) initiative was established by Alzheimer’s Research UK to address this challenge. As part of EDoN, digital data and low-burden clinical measures, such as blood tests, will be collected in thousands of people to create machine learning models that can detect specific dementia-causing diseases decades before noticeable cognitive symptoms arise. This effort will be supported by the development of a data platform and a digital toolkit (likely consisting of wearables and smartphone applications) that will collect active and passive physiological and behavioural measures (e.g. cognition, mood, heart rate, gait, sleep, and navigation). After extensive testing, EDoN aims to introduce the digital toolkit into annual health checks, which will allow for the early detection of dementia-causing diseases in a cost-effective, low-burden manner on a population-wide scale. Moreover, the information derived from the digital data will be used to inform lifestyle changes and to triage and stratify individuals into clinical trials or further targeted medical testing. As such, the outputs of the EDoN initiative will benefit the public, patients, carers, and clinicians, as well as the broader healthcare system and the pharmaceutical industry.

Background: Major depressive disorder is associated with altered social functioning and impaired learning, on both the behavioural and the neural level. These deficits are likely related, considering that successful social interactions require learning to predict other people's emotional responses. Yet, there is little research examining this relation.Methods: Forty-three individuals with high (HD; N=21) and low (LD; N=22) depression scores answered questions regarding their real-life social experiences and performed a social learning task during fMRI scanning. As part of the task, subjects learned associations between name cues and rewarding (happy faces) or aversive (fearful faces) social outcomes. Using computational modelling, behavioural and neural correlates of social learning were examined and related to real-life social experiences.Results: HD participants reported reduced motivation to engage in real-life social activities and demonstrated elevated uncertainty about social outcomes in the task. Moreover, HD subjects displayed altered encoding of social reward predictions in the insula, temporal lobe and parietal lobe. Interestingly, across all subjects, higher task uncertainty and reduced parietal prediction encoding were associated with decreased motivation to engage in real-life social activities. Limitations:The size of the included sample was relatively small. The results should thus be regarded as preliminary and replications in larger samples are called for. Conclusion:Taken together, our findings suggest that reduced learning from social outcomes may impair depressed individuals' ability to predict other people's responses in real life, which renders social situations uncertain. This uncertainty, in turn, may contribute to reduced social engagement (motivation) in depression.

We have previously shown that individuals with high depression scores demonstrate impaired behavioral and neural responses during social learning. Given that depression is associated with altered dopamine (DA) and serotonin (5-HT) functioning, the current study aimed to elucidate the role of these neurotransmitters in the social learning process using a dietary depletion manipulation. In a double-blind design, 70 healthy volunteers were randomly allocated to a 5-HT depletion (N=24), DA depletion (N = 24), or placebo (N = 22) group. Participants performed a social learning task during fMRI scanning, as part of which they learned associations between name cues and rewarding (happy faces) or aversive (fearful faces) social outcomes. Behaviorally, 5-HT depleted subjects demonstrated impaired social reward learning compared to placebo controls, with a marginal effect in the same direction in the DA depletion group. On the neural level, computational modelling-based fMRI analyses revealed that 5-HT depletion altered social reward prediction signals in the insula, temporal lobe, and prefrontal cortex, while DA depletion affected social reward prediction encoding only in the prefrontal cortex. These results indicate that 5-HT depletion impairs learning from social rewards, on both the behavioral and the neural level, while DA depletion has a less extensive effect. Interestingly, the behavioral and neural responses observed after 5-HT depletion in the current study closely resemble our previous findings in individuals with high depression scores using the same task. It may thus be the case that decreased 5-HT levels contribute to social learning deficits in depression.