Social risk coding by amygdala activity and connectivity with dorsal anterior cingulate cortex.

Risk is a fundamental factor affecting individual and social economic decisions, but its neural correlates are largely unexplored in the social domain. The amygdala, together with the dorsal anterior cingulate cortex (dACC), is thought to play a central role in risk taking. Here, we investigated in human volunteers (n=20; 11 females) how risk (defined as variance of reward probability distributions) in a social situation affects decisions and concomitant neural activity as measured with fMRI.

Tipping the balance between fairness and efficiency through temporoparietal stimulation.

Maximizing the welfare of society requires distributing goods between groups of people with different preferences. Such decisions are difficult because different moral principles impose irreconcilable solutions. For example, utilitarian efficiency (maximize overall outcome across individuals) may need trade-off against Rawlsian fairness norms (maximize the outcome for the worst-off individual).

Causal involvement of dorsomedial prefrontal cortex in learning the predictability of observable actions.

Social learning is well established across species. While recent neuroimaging studies show that dorsomedial prefrontal cortex (DMPFC/preSMA) activation correlates with observational learning signals, the precise computations that are implemented by DMPFC/preSMA have remained unclear. To identify whether DMPFC/preSMA supports learning from observed outcomes or observed actions, or possibly encodes even a higher order factor (such as the reliability of the demonstrator), we downregulate DMPFC/preSMA excitability with continuous theta burst stimulation (cTBS) and assess different forms of observational learning.

Neural Representation of Valenced and Generic Probability and Uncertainty.

Representing the probability and uncertainty of outcomes facilitates adaptive behavior by allowing organisms to prepare in advance and devote attention to relevant events. Probability and uncertainty are often studied only for valenced (appetitive or aversive) outcomes, raising the question of whether the identified neural machinery also processes the probability and uncertainty of motivationally neutral outcomes. Here, we aimed to dissociate valenced from valence-independent (i.

Neural Reward Representations Enable Utilitarian Welfare Maximization.

From deciding which meal to prepare for our guests to trading off the proenvironmental effects of climate protection measures against their economic costs, we often must consider the consequences of our actions for the well-being of others (welfare). Vexingly, the tastes and views of others can vary widely. To maximize welfare according to the utilitarian philosophical tradition, decision-makers facing conflicting preferences of others should choose the option that maximizes the sum of the subjective value (utility) of the entire group.