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Back to Departmental Colloquium: Spring 2006

Departmental Colloquium


Date: Thursday, Feb 9, 2006

Time: 4:15PM

Location: JWB 335


Wei Wu

Univ. of Chicago

Title

Statistical Models of Neural Coding in Motor Cortex and Their Applications in Neural Prostheses

Abstract

Effective neural motor prostheses require a method for decoding neural activity representing desired movement. In particular, the accurate reconstruction of a continuous motion signal is necessary for the control of devices such as computer cursors, robots, or a patient’s own paralyzed limbs. In this talk, I will present our real-time system for such applications that uses statistical Bayesian inference techniques to estimate hand motion from the firing rates of multiple neurons in a monkey’s primary motor cortex. The Bayesian model is formulated in terms of the product of a likelihood and a prior. The likelihood term models the probability of neural firing rates given a particular hand motion. The prior term defines a probabilistic model of hand kinematics. Decoding was performed using a Kalman filter as well as a more sophisticated Switching Kalman filter. Particularly, I will show on-line neural control results in which a monkey exploits the Kalman filter to move a computer cursor with its brain. Aiming at more appropriate and accurate decoding, I will also present further investigations on movement direction encoding under Cartesian, Joint Angle, and Shoulder-Centered coordinate systems.

Probability Mathematical Biology

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