title: Statistical modelling of spike libraries for simulation of extracellular recordings in the cerebellum.
abstract: Brain machine interfaces with chronically implanted microelectrode arrays for signal acquisition require algorithms for successful detection and classification of neural spikes. During the design of such algorithms, signals with a priori known characteristics need to be present. A common way to establish such signals is to model the recording environment, simulate the recordings and store ground truth about spiking activity for later comparison. In this paper, we present a statistical method to expand the spike libraries that are used in a previously presented simulation tool for the purpose described above. The method has been implemented and shown to successfully provide quick access to a large assembly of synthetic extracellular spikes with realistic characteristics. Simulations of extracellular recordings using synthesized spikes have shown to possess characteristics similar to those of in-vivo recordings in the cat cerebellum.
authors.affiliation: Neuronano Research Center and at Dept. of Electrical and Information Technology, Lund University, Sweden. palmi.thor.thorbergsson@eit.lth.se
authors.forename: P T
authors.initials: PT
authors.lastname: Thorbergsson
authors.forename: M
authors.initials: M
authors.lastname: Garwicz
authors.forename: J
authors.initials: J
authors.lastname: Schouenborg
authors.forename: A
authors.initials: A
authors.lastname: Johansson
mesh_terms: D000200:Action Potentials; D000818:Animals; D002415:Cats; D002531:Cerebellum / Q000502:physiology*; D015233:Models, Statistical; D025341:Principal Component Analysis