Unsupervised waveform classification for multi-neuron recordings: a real-time, software-based system. I. Algorithms and implementation.
We describe a new, mostly software-based device for the sorting of waveforms in an extracellular multi-neuron recording situation. The sorting algorithm is largely unattended, and, after an initial 'learning' process, works in real time. Shape comparisons are based on up to 8 time points in the waveform; these points (the reduced feature set) are chosen automatically by analyzing the current incoming data stream. A feasibility version has been implemented on a LSI-11/2 system, using FORTRAN for set-up calculations and assembler for the real-time operations. Detailed comparisons with performance of other sorting devices are presented in the companion paper.
Salganicoff
M
M
Department of Physiology, University of Pennsylvania, Philadelphia 19104.
Sarna
M
M
Sax
L
L
Gerstein
G L
GL
D000465:Algorithms; D000818:Animals; D002415:Cats; D003056:Cochlear Nerve / Q000502:physiology; D003201:Computers; D004594:Electrophysiology / Q000379:methods; D009474:Neurons / Q000502:physiology*