The hypothalamic-midbrain neural circuits play an important role in social interactions involving aggression, defense, and mating. However, how population-averaged neural activity measured by multi-fiber photometry (MFP) for calcium fluorescence signals correlates with social behaviors is a fundamental question. This study proposed a state-space analysis framework to characterize mouse MFP data based on dynamic latent variable models. These models were validated on extensive MFP recordings during aggressive and mating behaviors in male-male and male-female interactions.

Using custom high-density multi-fiber arrays, they recorded the Ca²⁺ activity of estrogen receptor type 1-expressing populations from 13 brain regions in a well-defined social behavior network (SBN) from freely-moving mice. Recordings were made in a male mouse as it socially interacted with a female or male mouse in a chamber. The targeted SBN includes 5 hypothalamic regions, 5 amygdala regions, and 3 other regions outside of amygdala and hypothalamus. This dataset includes MFP recording and behavior annotation data, which provides a strategy to examine neural dynamics underlying social behaviors.