Our research focuses on understanding the brain using computational models and simulations, and applying this knowledge to the task of building intelligent robotic systems and brain-computer interfaces (BCIs). We utilize data and techniques from a variety of fields, ranging from neuroscience and psychology to machine learning and statistics. Current efforts are directed at: (1) understanding probabilistic information processing and learning in the brain, (2) building biologically-inspired robots that can learn through experience and imitation, and (3) developing interfaces for controlling computers and robots using brain- and muscle-related signals.

Collaborators

Publications

A Hierarchical Architecture for Adaptive Brain-Computer Interfacing A Hierarchical Architecture for Adaptive Brain-Computer Interfacing
Mike Chung, Willy Cheung, Reinhold Scherer and Rajesh Rao
International Joint Conference on Artificial Intelligence, 2011. Full Paper (PDF)
Predictive Coding Predictive Coding
Yanping Huang and Rajesh Rao
Wiley Interdisciplinary Reviews, 2011. Journal Article (PDF)
A rational decision making framework for inhibitory control
Pradeep Shenoy, Rajesh Rao and Angela Yu
Annual Conference on Neural Information Processing Systems, 2010. Full Paper (PDF)
Decision Making under Uncertainty: A Neural Model based on Partially Observable Markov Decision Processes
Rajesh Rao
Frontiers in Computational Neuroscience, 2010. Journal Article