Quantifying social roles in multi-animal videos using subject-aware deep-learning.

Analyzing social behaviors is critical for many fields, including neuroscience, psychology, and ecology. While computational tools have been developed to analyze videos containing animals engaging in limited social interactions under specific experimental conditions, automated identification of the social roles of freely moving individuals in a multi-animal group remains unresolved. Here we describe a deep-learning-based system - named LabGym2 - for identifying and quantifying social roles in multi-animal groups.

Early-life sleep disruption impairs subtle social behaviours in prairie voles: a pose-estimation study.

Early-life sleep disruption (ELSD) has been shown to have long-lasting effects on social behaviour in adult prairie voles (), including impaired expression of pair bonding during partner preference testing. However, due to the limitations of manual behaviour tracking, the effects of ELSD across the time course of pair bonding have not yet been described, hindering our ability to trace mechanisms. Here, we used pose estimation to track prairie voles during opposite-sex cohabitation, the process leading to pair bonding.

Early life sleep disruption has long lasting, sex specific effects on later development of sleep in prairie voles.

In mammals, sleep duration is highest in the early postnatal period of life and is critical for shaping neural circuits that control the development of complex behaviors. The prairie vole is a wild, highly social rodent that serves as a unique model for the study of complex, species-typical social behaviors. Previous work in our laboratory has found that early life sleep disruption (ELSD) in prairie voles during a sensitive window of postnatal development leads to long lasting changes in social and cognitive behaviors as well as structural changes in excitatory and inhibitory neural circuits in the brain.

Development of highly sensitive, flexible dual L-glutamate and GABA microsensors for in vivo brain sensing.

Real-time tracking of neurotransmitter levels in vivo has been technically challenging due to the low spatiotemporal resolution of current methods. Since the imbalance of cortical excitation/inhibition (E:I) ratios are associated with a variety of neurological disorders, accurate monitoring of excitatory and inhibitory neurotransmitter levels is crucial for investigating the underlying neural mechanisms of these conditions. Specifically, levels of the excitatory neurotransmitter L-glutamate, and the inhibitory neurotransmitter GABA, are assumed to play critical roles in the E:I balance.