Algorithms and neural mechanisms of social and collective behavior

Neuroscience experiments have been classically performed under highly controlled conditions in isolated animals, largely ignoring that, in the wild, many animals usually socially interact in heterogeneous groups. To understand the algorithmic computations and neural mechanisms of such naturalistic behavior, it is therefore important to include social contexts in our theoretical analyses and experimental pipelines. The emerging research field of the study of the algorithms and neural mechanisms of social and collective behavior has recently made major technological breakthroughs, ranging from sophisticated closed-loop virtual reality systems to novel physiological recording methods. These advances make it now feasible to systematically dissect how collective behavior benefits group decision-making performance, which sensory cues animals use to recognize each other, which algorithms govern collective behavior, and how nervous systems combine, potentially conflicting, sensory input. Our proposed satellite workshop aims to bring together leading researchers who have significantly contributed to addressing these questions. We have selected speakers based on an emphasis on a broad perspective across model systems, ranging from insects to fish, to rodents, and primates. This diversity will allow us to identify general principles across species. We have also finely balanced the level of theory and experiment, so the audience can benefit from extensive discussions on developing and applying computational methods to better understand and predict neural and behavioral data.