부산대학교 도서관

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.