Wednesday, April 2, 2025
4/2/2025
Mapping dynamic transitions across neural, behavioral, and social scales in interacting animals - Project Summary BBQS R34 – Zhang & Frohlich Mapping dynamic transitions across neural, behavioral, and social scales in interacting animals Human and animal behavior is shaped by many processes across spatiotemporal scales – from the activities of neurons to the dynamics of social interaction. Mapping behavior and brain dynamics across scales is key to a systemic understanding of cognition, neuropsychiatric disorders, and developing personalized interventions. In social neuroscience, the mapping between social behavior and brain dynamics was primarily achieved by constraining the behavior to a well-controlled, low-dimensional task space, where common linear statistical methods suffice to discover cross-scale relations. However, the complex, dynamic, and interactive nature of real-world social interaction is largely lost in such task-constrained settings. More recently, both human and animal social neuroscience began to embrace a multi-brain interactive approach, where brain activities were simultaneously recorded and found to be synchronized during live social interaction. Without task constraints, animals can adopt and transition between a diverse range of behavioral patterns, which are signs of nonlinear, high-dimensional dynamical systems. There is a critical need for a computational-experimental framework to characterize the complex dynamics of naturalistic interaction and connect them across neural and behavior scales. The main objective of this project is to develop a computational-experimental framework to construct multiscale models of naturalistic social interaction connecting the spiking dynamics of neurons, brain oscillations, body movements, and macroscopic behavioral states. To achieve this objective, the project will utilize simultaneously recorded behavioral and electrophysiology data from ferrets during naturalistic interaction. Ferrets are chosen as a model of dynamic social interaction for their high social skills and complex visuomotor communication, which allows for fine-grained characterization of social dynamics based on expressive body movements. At the neural level, ferrets’ frontoparietal networks exhibit similar oscillations to those of humans that were found to synchronize during social interaction, paving the way to future comparative studies. Animal data also provides the opportunity to include neuronal activity in the multiscale framework, which is not commonly accessible in humans. Computationally, the toolbox will build upon recent advances in topological time series analysis to extract states and transitions from complex dynamics at different scales of measurements, combined with computer vision techniques for motion tracking, machine learning for cross- scale mapping of state transitions, and expert annotations. This project integrates diverse perspectives from cognitive social neuroscience to nonlinear dynamics, computational topology, and machine learning. The project will significantly impact neuroscience by providing much-needed tools to examine multiscale relations in the brain and behavior in real-world settings and the future design of state-dependent treatments for neuropsychiatric and behavioral disorders, combining pharmacological treatments, brain stimulations, and psychosocial interventions.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).