ePoster

Deciphering social and solitary behaviors in mice: Insights from a data-driven approach to behavior decomposition

Marti Ritter, Serena Deiana, Roberto Arban, Carsten Wotjak, Bastian Hengerer, Amarender Bogadhi
FENS Forum 2024(2024)
Messe Wien Exhibition & Congress Center, Vienna, Austria

Conference

FENS Forum 2024

Messe Wien Exhibition & Congress Center, Vienna, Austria

Resources

Authors & Affiliations

Marti Ritter, Serena Deiana, Roberto Arban, Carsten Wotjak, Bastian Hengerer, Amarender Bogadhi

Abstract

Investigation of social behavior in mice is increasingly relevant to understand associated brain circuits and thereby develop treatments for psychiatric symptoms such as social withdrawal. Importantly, a data-driven description of social behavior and how the behavioral repertoire of mice differs in solitary vs. social context is lacking. Here, we aim to identify, in a data-driven manner, recurring behavioral patterns (“syllables”) that are unique to social and solitary contexts.We recorded videos of male C57BL/6j mice, in two epochs of 90 minutes duration, either in a social context (n=4) or in a solitary context (n=4) and tracked their pose through key-points extracted through the software SLEAP to fit a KeyPoint-MoSeq (KPM) model and extract behavioral syllables. The resulting syllables were named through visual inspection controlling for quality and replicability.Our preliminary results reveal behavioral syllables that are preferentially expressed in social or solitary contexts. Rearing behavior and jumps along the walls are predominant in social contexts while stationary behaviors are prevalent in solitary contexts. We also observed that the expression of the syllables in the social context follows a temporal pattern, where active movement behaviors are enriched in the first epoch while stationary and grooming behaviors are increased in the second epoch.These preliminary findings suggest that mice preferentially express certain behaviors in social or solitary contexts in a time dependent manner. We plan to validate these findings in multiple datasets and further evaluate the temporal organization of syllables in social and solitary contexts.

Unique ID: fens-24/deciphering-social-solitary-behaviors-c6ca982c