Title :
Evaluation of the stability of intracortical microelectrode arrays
Author :
Liu, Xindong ; McCreery, Douglas B. ; Bullara, Leo A. ; Agnew, William F.
Author_Institution :
Neural Eng. Program, Huntington Med. Res. Inst.s, Pasadena, CA, USA
fDate :
3/1/2006 12:00:00 AM
Abstract :
In order to use recorded neural activities from the brain as control signals for neuroprosthesis devices, it is important to maintain a stable interface between chronically implanted microelectrodes and neural tissue. Our previous paper introduced a method to quantify the stability of the recording microelectrodes. In this paper, the method is refined 1) by incorporating stereotypical behavioral patterns into the spike sorting program and 2) by using a classifier based on Bayes theorem for assigning the recorded action potentials to the underlying neural generators. An improved method for calculating stability index is proposed. The results for the stability of microelectrode arrays that differ in structure are presented.
Keywords :
Bayes methods; arrays; bioelectric potentials; brain; medical signal processing; microelectrodes; neurophysiology; prosthetics; signal classification; stability; Bayes classifier; action potentials; brain; chronically implanted microelectrodes; intracortical microelectrode array stability; neural generators; neural tissue; neuroprosthesis devices; recorded neural activities; spike sorting program; stereotypical behavioral patterns; Control systems; Electrodes; Implants; Microelectrodes; Neural engineering; Robots; Shafts; Sorting; Spinal cord injury; Stability; Brain–machine interface; cat cortex; chronic microelectrode implants; neuroprosthesis; stability; Action Potentials; Algorithms; Animals; Bayes Theorem; Cats; Cerebral Cortex; Cluster Analysis; Conditioning, Operant; Data Interpretation, Statistical; Electrodes, Implanted; Electrophysiology; Microelectrodes; Neurons;
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
DOI :
10.1109/TNSRE.2006.870495
