Multimodal Framework for Sensation to Action Transformation

Our team has pioneered the use of accurate biologically inspired models of brain and spinal cord for understanding the neural control of movement and perception. These models can explain the coordination of complex body parts during reaching and walking, how we perceive them, and how vision help us navigate the world. However, these models are complex and difficult to tailor to individuals.

We propose to create a novel mathematical framework that will use artificial neural networks to solve this problem. We plan to pre-train smaller networks using experimental data and known biological and physical laws and then daisy chain them together to describe more complex emergent behavior.