Identification of cortical signals as commands for neuroprostheses

A fuzzy logic system is implemented in efforts to develop an effective control algorithm for a cortical signal controlled neural prosthesis. The system relates the neuronal activity of the motor cortex to velocity and direction of hand movement in 3-dimensional space. Cortical activity is recorded from chronically implanted multi-channel electrodes in the motor cortical area corresponding to arm movement. The movement trajectory is recorded by multiple optical sensors from rhesus monkeys during a center→out reaching task. The fuzzy logic rule base consists of rules generated from input-output pairs of the neuronal spike rates from 16 cortical neurons and the velocity of hand movement (in x, y and z directions) shifted by 100 msec. The developed fuzzy logic mapping can predict hand trajectories with correct direction. The performance is expected to improve with increased number of cortical neurons and more comprehensive rule base.