Immersive Social Interaction Assay (ISIA) for Studying Voluntary and Long-Term Social Behavior in Mice

Social behavior is highly dynamic and context-dependent, yet many commonly used rodent social assays rely on short testing periods and simplified measures of proximity or investigation. Here, we present a detailed protocol for constructing and using the immersive social interaction assay (ISIA), a behavioral paradigm designed to capture prolonged, voluntary social interactions in freely moving mice. The ISIA apparatus consists of two modified standard rodent home-cage chambers connected by a 3D-printed tube with an adjustable inner diameter. This design enables flexible experimental control: a removable restrictor can confine a head-bar-implanted focal mouse to one chamber while permitting a freely moving conspecific to traverse the full apparatus, enabling assessment of social motivation. Animals can be recorded over extended time windows with familiar or novel conspecifics, in their home territory or in novel environments, and under varying thermal or enrichment conditions, while expressing a broad repertoire of affiliative and aggressive behaviors, including huddling and aggression. The apparatus can be readily integrated with machine learning-based tracking and behavioral classification pipelines for high-throughput analysis. This protocol describes step-by-step construction, setup, and experimental implementation of the ISIA, from apparatus construction and head-bar implantation to video-based behavioral analysis, with the goal of facilitating broader adoption of ethologically relevant behavioral assays in neuroscience research. Key features • The ISIA apparatus is modular and cost-effective, built from standard rodent housing and 3D-printed components. • Enables voluntary, prolonged social interactions in mice, preserving the ability to engage or withdraw and allowing assessment of social motivation. • Provides flexible experimental control over access between animals (e.g., via an adjustable restrictor) while maintaining naturalistic interaction dynamics. • Integrates with machine learning-based tracking pipelines for automated, high-throughput quantification of complex social behaviors.