Multi-state decoding of point-and-click control signals from motor cortical activity in a human with tetraplegia

Basic neural prosthetic control of a computer cursor has been recently demonstrated by Hochberg et al. (2006) using the BrainGate system (Cyberkinetics Neurotechnology Systems, Inc.). While these results demonstrate the feasibility of intracortically-driven prostheses for humans with paralysis, a practical cursor-based computer interface requires more precise cursor control and the ability to "click" on areas of interest. Here we present the first practical point and click device that decodes both continuous states (e.g. cursor kinematics) and discrete states (e.g. click states) from a single neural population in human motor cortex. We describe a probabilistic multi-state decoder and the necessary training paradigms that enable point and click cursor control by a human with tetraplegia using an implanted microelectrode array. We present results from multiple recording sessions and quantify the point and click performance