Across primates, volumes of specific brain regions relate to specific socio-ecological factors, bridging the gap between neuro-cognitive operations from laboratory studies and challenges primates face in their natural environment.

The Mouse Action Recognition System is a computational pipeline for automated classification of social behaviors in freely interacting mice, accompanied by a graphical interface for analysis of multimodal neuroscience datasets.

The human brain is capable of implementing inverse reinforcement learning, where an observer infers the hidden reward structure of a decision problem solely through observing another individual take actions.

An increased emphasis on falsification – the direct testing of strong hypotheses – will lead to faster progress in science by allowing well-specified hypotheses to be eliminated.

Experiments and modeling suggest that a mechanism involving positive and negative feedback can explain the relationship between the neural activity of socially interacting bats.

People's confidence in information and their neural correlates in key regions of the social brain are more stable when tracking social advice compared to non-social information.

Measures of visuocortical activity during aversive generalization learning revealed sharpened representations of facial identity, reflecting inhibitory interactions between neuronal populations that represent facial features associated with threat versus safety.

Children with autism often 'tune out' the voices in their environment and new results show that impaired processing of voices in the brain's reward system may underlie this social behavior.

A multidisciplinary approach sheds light on the fundamental mechanisms underlying social belief communication under uncertainty.

The Marmoset Apparatus for Automated Pulling provides a powerful and scalable experimental platform for studying behavioral and neural mechanisms underlying cooperation in freely moving marmosets.