Dopamine and serotonin in human substantia nigra track social context and value signals during economic exchange.

Dopamine and serotonin are hypothesized to guide social behaviours. In humans, however, we have not yet been able to study neuromodulator dynamics as social interaction unfolds. Here, we obtained subsecond estimates of dopamine and serotonin from human substantia nigra pars reticulata during the ultimatum game. Participants, who were patients with Parkinson's disease undergoing awake brain surgery, had to accept or reject monetary offers of varying fairness from human and computer players. They rejected more offers in the human than the computer condition, an effect of social context associated with higher overall levels of dopamine but not serotonin. Regardless of the social context, relative changes in dopamine tracked trial-by-trial changes in offer value-akin to reward prediction errors-whereas serotonin tracked the current offer value. These results show that dopamine and serotonin fluctuations in one of the basal ganglia's main output structures reflect distinct social context and value signals.

Aberrant neural computation of social controllability in nicotine-dependent humans.

Social controllability, defined as the ability to exert influence when interacting with others, is crucial for optimal decision-making. Inability to do so might contribute to maladaptive behaviors such as drug use, which often takes place in social settings. Here, we examined nicotine-dependent humans using fMRI, as they made choices that could influence the proposals from simulated partners. Computational modeling revealed that smokers under-estimated the influence of their actions and self-reported a reduced sense of control, compared to non-smokers. These findings were replicated in a large independent sample of participants recruited online. Neurally, smokers showed reduced tracking of forward projected choice values in the ventromedial prefrontal cortex, and impaired computation of social prediction errors in the midbrain. These results demonstrate that smokers were less accurate in estimating their personal influence when the social environment calls for control, providing a neurocomputational account for the social cognitive deficits in this population.

Computational mechanisms underlying illusion of control in delusional individuals.

Humans navigate complex situations that require the accurate estimation of the controllability of the environment. Aberrant controllability computation might lead to maladaptive behaviors and poor mental health outcomes. Illusion of control, which refers to a heightened sense of control while the environment is uncontrollable, is one such manifestation and has been conceptually associated with delusional ideation. Nevertheless, this association has not yet been formally characterized in a computational framework. To address this, we used a computational psychiatry approach to quantify illusion of control in human participants with high (n = 125) or low (n = 126) trait delusion. Participants played a two-party exchange game in which their choices either did ("Controllable condition") or did not ("Uncontrollable condition") influence the future monetary offers made by simulated partners. We found that the two groups behaved similarly in model-agnostic measures (i.e., offer size, rejection rate). However, computational modeling revealed that compared to the low trait delusion group, the high delusion group overestimated their influence ("expected influence" parameter) over the offers made by their partners under the Uncontrollable condition. Highly delusional individuals also reported a stronger sense of control than those with low trait delusion in the Uncontrollable condition. Furthermore, the expected influence parameter and self-reported beliefs about controllability were significantly correlated in the Controllable condition in individuals with low trait delusion, whereas this relationship was diminished in those with high trait delusion. Collectively, these findings demonstrate that delusional ideation is associated with aberrant computation of and belief about environmental controllability, as well as a belief-behavior disconnect.

Humans use forward thinking to exploit social controllability.

The controllability of our social environment has a profound impact on our behavior and mental health. Nevertheless, neurocomputational mechanisms underlying social controllability remain elusive. Here, 48 participants performed a task where their current choices either did (Controllable), or did not (Uncontrollable), influence partners' future proposals. Computational modeling revealed that people engaged a mental model of forward thinking (FT; i.e., calculating the downstream effects of current actions) to estimate social controllability in both Controllable and Uncontrollable conditions. A large-scale online replication study (n=1342) supported this finding. Using functional magnetic resonance imaging (n=48), we further demonstrated that the ventromedial prefrontal cortex (vmPFC) computed the projected total values of current actions during forward planning, supporting the neural realization of the forward-thinking model. These findings demonstrate that humans use vmPFC-dependent FT to estimate and exploit social controllability, expanding the role of this neurocomputational mechanism beyond spatial and cognitive contexts.

Emotional adaptation during a crisis: decline in anxiety and depression after the initial weeks of COVID-19 in the United States.

Crises such as the COVID-19 pandemic are known to exacerbate depression and anxiety, though their temporal trajectories remain under-investigated. The present study aims to investigate fluctuations in depression and anxiety using the COVID-19 pandemic as a model crisis. A total of 1512 adults living in the United States enrolled in this online study beginning April 2, 2020 and were assessed weekly for 10 weeks (until June 4, 2020). We measured depression and anxiety using the Zung Self-Rating Depression scale and State-Trait Anxiety Inventory (state subscale), respectively, along with demographic and COVID-related surveys. Linear mixed-effects models were used to examine factors contributing to longitudinal changes in depression and anxiety. We found that depression and anxiety levels were high in early April, but declined over time. Being female, younger age, lower-income, and previous psychiatric diagnosis correlated with higher overall levels of anxiety and depression; being married additionally correlated with lower overall levels of depression, but not anxiety. Importantly, worsening of COVID-related economic impact and increase in projected pandemic duration exacerbated both depression and anxiety over time. Finally, increasing levels of informedness correlated with decreasing levels of depression, while increased COVID-19 severity (i.e., 7-day change in cases) and social media use were positively associated with anxiety over time. These findings not only provide evidence for overall emotional adaptation during the initial weeks of the pandemic, but also provide insight into overlapping, yet distinct, factors contributing to depression and anxiety throughout the first wave of the pandemic.