In collaboration with the group of Tim Lei in the Department of Electrical Engineering at UC Denver, the group co-published a manuscript describing a novel spike sorting algorithm (Enhanced Growing Neural Gas, EGNG), which is computationally much less demanding than other existing algorithms. The lower demands on computing power will help with the development of small implantable stand-alone devices such as neural prosthesis.
Z. Mohammadi, J.M. Kincaid, S.H. Pun, A. Klug, C. Liu C, and T.C. Lei:
Computationally inexpensive enhanced growing neural gas algorithm for real-time adaptive neural spike clustering. Journal of Neural Engineering May 9. doi: 10.1088/1741-2552/ab208c, 2019.