Dynamic patterns of correlated activity in the prefrontal cortex encode information about social behavior

Abstract

New technologies have made it possible to measure activity from many neurons simultaneously. Nevertheless, most studies still analyze the activity of simultaneously recorded neurons one-at-a-time, then group together neurons which increase their activity during similar behaviors into an ensemble. This notion of an ensemble ignores the ability of neurons to act collectively, and encode and transmit information in ways that are not reflected by their individual activity levels. We used microendoscopic GCaMP imaging to measure prefrontal activity while mice were either alone or engaged in social interaction. We developed new approaches, using neural network classifiers and surrogate (shuffled) datasets, to characterize how neurons synergistically transmit information about social behavior. Surrogate datasets which preserve behaviorally-specific patterns of coactivity (correlations) outperform those which preserve behaviorally-driven changes in activity levels but not correlated activity. This shows that prefrontal neurons act collectively to transmit information about socialization, because social behavior elicits increases in correlated activity that are not explained simply by the activity levels of the underlying neurons. Notably, this ability of correlated activity to enhance the information transmitted by neuronal ensembles is lost in mice lacking the autism-associated gene Shank3. These results show that synergy is an important concept for the coding of social behavior which can be disrupted in disease states, reveal a specific mechanism underlying this synergy (social behavior increases correlated activity within specific ensembles), and outlines methods for studying how neurons within an ensemble can work together to encode information.