title: A wavelet approach for on-line spike sorting in tetrode recordings.
abstract: A new method for spike sorting of tetrode recordings during data acquisition is introduced. For each tetrode channel, putative spikes are detected by means of a threshold, and then convolved with a cascade of wavelet filters. These transformed putative spikes are averaged and this average is used as a matched filter to find portions of signals that are likely to contain a spike. A collection of vectors containing the correlation coefficients between putative spikes and the matched filters is then clustered using K-Means. Centroids of the resulting clusters contain enough information to sort spikes recorded by all tetrode channels simultaneously. On-line sorting is achieved by measuring euclidean distance between putative new spikes and the cluster centroids.
authors.affiliation: Instituto de Ingeniería Biomédica, Facultad de Ingeniería, Universidad de Buenos Aires. Paseo Colón 850, Argentina. slew@fi.uba.ar
authors.forename: E
authors.initials: E
authors.lastname: De Benedetti
authors.forename: S E
authors.initials: SE
authors.lastname: Lew
authors.forename: B S
authors.initials: BS
authors.lastname: Zanutto
mesh_terms: D000200:Action Potentials / Q000502:physiology; D004594:Electrophysiology / Q000379:methods*; D012815:Signal Processing, Computer-Assisted