Visual Training for Population Vector Based Cortical Control

Authors:	He Jiping, Arizona State University, United States Helms Tillery Steve, Arizona State University, United States Wahnoun Remy, Arizona State University, United States
Topic:	8.2 Modelling & Control of Biomedical Systems
Session:	Identification of Biomedical System Dynamics
Keywords:	cortical coding; cortical control; neuroprosthetics; motor cortex; algorithm

Abstract

AWe have developed a method for training animals to control a variety of devices from cortical signals [1-4]. In this report we describe a protocol to parameterize a cortical control algorithm without an animal having to move its arm. Instead, a highly motivated animal observes a computer cursor moving towards a set of targets once each in a center-out task. From the neuronal activity recorded in this visual following task, we compute the set of preferred directions for the neurons. We find that the quality of fit in this early set of trials is highly predictive of each neuron’s contribution to the overall cortical control.