Evaluation of the stability of intracortical microelectrode arrays

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 14; no. 1; pp. 91 - 100
• Main Authors: Xindong Liu, McCreery, D.B., Bullara, L.A., Agnew, W.F.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2006; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Action Potentials - physiology; Algorithms; Animals; Bayes Theorem; Brain-machine interface; cat cortex; Cats; Cerebral Cortex - physiology; chronic microelectrode implants; Cluster Analysis; Conditioning, Operant - drug effects; Control systems; Data Interpretation, Statistical; Electrodes; Electrodes, Implanted; Electrophysiology; Implants; Microelectrodes; Neural engineering; Neurons - physiology; neuroprosthesis; Robots; Shafts; Sorting; Spinal cord injury; Stability
• ISSN: 1534-4320; 1558-0210
• DOI: 10.1109/TNSRE.2006.870495

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.