Data-driven models for control of biomechanical bodies
Closed-loop neural controllers with biologically grounded sensory feedback for realistic locomotion in Drosophila.
Closed-loop neural controllers with biologically grounded sensory feedback for realistic locomotion in Drosophila.
Network structure shapes inhibitory network dynamics and representational transformations across cerebellar circuits.
How feedback, intrinsic dynamics, and controllability constrain learning timescales for fast adaptation.
Fast adaptation via input-driven reorganization of dynamics, contextual inference, and flexible inter-area associations.
Computational signatures of reinforcement learning when state inference is uncertain due to noisy perception.
Identifying nonlinear dynamics from data, and aligning neural population activity across sessions.