Conference Agenda

Mental disorders are commonly characterized by deficits in social motivation, social learning and social interactions. Vice versa, social interactions are part of the psychosocial treatments of psychiatric disorders. Thus, understanding the role of social interactions in clinically relevant conditions is essential for optimizing diagnosis and treatments. Our symposium brings together scientists from four different countries (Germany, Canada, United Kingdom, Switzerland) who present their research on different aspects of social interactions in health and disease, and discuss potential clinical applications. The first two talks focus on the basis of social interactions such as neurochemical processes (Jennifer Cook) as well as learning about the intentions of others and the underlying neural circuitries (Christoph Korn). Next, we will discuss the relationship between individual neural processing of social inferences and social contacts in the real world (Anita Tusche). Following up on this, the junior-scientist presentation focuses on the effects of every-day life social interactions on anxiety and depression (Annalena Jachnik). The final talk of the symposium gives insights into another significant aspect of social interactions, namely non-verbal communication, and its alteration in schizophrenia and depression (Anastasia Pavlidou). Collectively, the presentations of the experts will shed light onto the psychological and neurobiological mechanisms that drive social interactions, highlight their connection to psychopathology, and demonstrate how social interactions can be shaped in clinical applications or promote mental well-being.

Autism and Parkinson’s are traditionally associated with social and motor differences, respectively, but they share overlapping features—including motor differences in Autism and social differences in Parkinson’s. Despite this, the biological basis of overlapping social and motor differences remains unclear. Both Autism and Parkinson’s have been linked to differences in the dopamine system, suggesting that dopamine system variation might be linked to both social and motor differences. To investigate this, we conducted a series of studies examining the role of dopamine in social and motor function through dopaminergic drug manipulation.

Our research demonstrated that dopamine influences how we learn from direct experience versus secondary sources, whether social or non-social (Rybicki et al., 2022). Blocking dopamine D2/D3 receptors with haloperidol impaired participants’ ability to interpret others' mental states, highlighting dopamine’s role in understanding thoughts and intentions (Schuster et al., 2024). Further studies revealed a baseline-dopamine-level-dependent effect of haloperidol on emotion recognition: People with lower dopamine improved when given haloperidol, while those with higher dopamine were less accurate in emotion recognition (Schuster et al., 2022). In addition to these social functions, dopamine was shown to influence not just movement speed but also adaptive modulation of speed (meta-modulation), challenging traditional views linking dopamine only to movement vigour (Hickman et al., 2024). Nevertheless, whilst we confirmed that dopamine influences both movement and social cognition, no evidence was found that the effects on social cognition were mediated through body movement. This research suggests that dopaminergic modulation independently affects movement and social cognition.

Adequately navigating social interactions requires learning about others’ intentions, i.e., whether they intend to cooperate or compete. However, in many contexts, individuals can only observe others’ outcomes, leaving the information about their intentions, goals, and capacities ambiguous and incomplete. One motivation to develop a task that captures intention learning under such ambiguous situations is that this learning becomes even more challenging for people with personality disorders, as they already have difficulties in inferring others’ internal mental states. Here, we tested healthy participants in a set of studies (3 behavioral experiments, N = 99 in total; one fMRI experiment, N = 32). We designed variants of sequential social decision-making tasks to investigate how individuals navigate ambiguous situations in which others’ internal intentions and the influence of the external environment are congruent or incongruent. That is, participants need to infer whether the observed outcomes are determined by the external environment or the inherent intentions of others. Our results revealed a negativity bias: participants learned competitive intentions better than cooperative intentions in incongruent conditions. Variants of Rescorla-Wagner models and Bayesian learning frameworks described the intention learning process. The bilateral dorsolateral prefrontal cortex, dorsomedial prefrontal cortex and temporoparietal junction were involved in the interaction of ambiguity, intention and outcome. Taken together, our results underscore the challenges of deciphering different intentions in ambiguous environments and the critical role of a negativity bias. Our task is promising as a tool to test and understand social dysfunctions, for example in patients with personality disorders.

The ability to infer others' thoughts and feelings is fundamental to social interaction, yet its relationship with real-world social behavior and loneliness remains unclear. Using fMRI, we investigated whether neural activation during social inference predicts social connectivity and subjective loneliness. Across three neurotypical samples (total n = 126) and one autistic sample (n = 23), we found that activation patterns in the right posterior superior temporal sulcus (pSTS) during social inference robustly predicted social network size, but not non-social inference. These findings generalized across individuals and were cross-validated within and between groups. Additionally, pSTS activation correlated with autism-like traits and symptom severity. In an independent sample of older adults (n = 56), neural responses during social inference also predicted subjective loneliness, suggesting that similar neural mechanisms underlie both objective and subjective social disconnection. These results demonstrate that brain activity during social inference serves as a meaningful neural marker of social integration and well-being. Importantly, our findings generalize across neurotypical and atypical populations and across the lifespan, highlighting the crucial role of social cognition in maintaining social bonds and mitigating loneliness.

Social interactions and social support can buffer anxiety and negative emotions. Patients suffering from depression and anxiety disorders might benefit from such social buffering effects. Previous research has mainly focused on healthy participants in laboratory settings and it is unclear whether the observed effects apply to everyday life. Furthermore, social support is multidimensional, with different types potentially having distinct effects on outcome variables like anxiety and mood. This study investigated the effects of social support types on state social anxiety during social interactions and mood directly after social interactions in everyday life of patients with depression and anxiety disorders and healthy controls. Using smartphone-based Ecological Momentary Assessment (EMA), participants reported on social interaction characteristics, the received support, and their anxiety and mood levels based on six survey prompts per day on five consecutive days. Preliminary data of N=28 patients and N=38 controls showed that patients experienced higher state social anxiety during social interactions and more depressive mood afterwards compared to controls. Greater emotional and esteem support were associated with lower anxiety, while higher informational support was linked to increased anxiety during social interactions, although it had a beneficial effect on patients’ general mood compared to controls. Furthermore, emotional support had a positive effect on general mood and esteem support was linked to lower depressive mood after social interactions. This study highlights the benefits of EMA research, specifically in clinical samples, and characterizes the effects of types of everyday-life social support on prevalent symptoms of anxiety and depression disorders.

Gestures are visible bodily movements used alone or in conjunction with speech to convey meaning, intentions and emotions and are an integral part for successful social communication. Clinical research often focuses on specific disorder deficits in relation to gesture performance accuracy, however emerging evidence suggests that gesture deficits may transcend diagnostic boundaries. Understanding the transdiagnostic nature of gesture deficits is important as it might clarify the shared and distinct mechanisms associated with these deficits.

Gesture performance accuracy was evaluated across three clinical adult populations: schizophrenia spectrum disorder, major depressive disorder, and autism spectrum disorder. The Test-of-Upper-Limb-Apraxia (TULIA) was used to assess gesture performance accuracy. TULIA includes two domains: imitation, where participants perform gestures after a visual demonstration, and pantomime, where gestures follow a verbal command. Within these domains, gestures are categorized as meaningless (novel), intransitive (communicative), or transitive (tool-based).

We observed consistent overall gesture deficits across all three clinical populations. However, when investigating gesture deficits within domains and categories notable differences emerged. Patients with schizophrenia showed greater disturbances in the pantomime meaningless category, while patients with depression had deficits in all categories but the pantomime meaningless. Further, individuals with autism showed greater deficits in tool-based gestures irrespective of domain.

Our results suggest that the identified gesture deficit represents a transdiagnostic feature. The observed differences in specific domains and/or categories suggest that they likely arise from distinct underlying mechanisms specific to each disorder. These results underscore the importance of considering both shared and individual characteristics of clinical impairments.