Computing with Neural Ensembles
Anne W. Deane Professor of Neuroscience
Depts. of Neurobiology, Biomedical Engineering, and Psychology and Neuroscience
Co-Director, Duke Center for Neuroengineering
In this talk, I will review a series of recent experiments
demonstrating the possibility of using real-time computational
models to investigate how ensembles of neurons encode motor
information. These experiments have revealed that brain-machine
interfaces can be used not only to study fundamental aspects of neural
ensemble physiology, but they can also serve as an experimental
paradigm aimed at testing the design of modern neuroprosthetic
devices. I will also describe evidence indicating that continuous
operation of a closed-loop brain machine interface, which utilizes a
robotic arm as its main actuator, can induce significant changes in
the physiological properties of neurons located in multiple motor and
sensory cortical areas. This raises the hypothesis of whether the
properties of a robot arm, or any other tool, can be assimilated by
neuronal representations as if they were simple extensions of the
subject's own body.
