Multi-unit spike discrimination using wavelet transforms.
A new spike discrimination procedure addressing the specific problem of spike superposition is described. The method, based on a shift-invariant wavelet transform and its amplitude-and-phase representation, has the advantage of both reducing the effect of noise present in the data and correcting the latency of specific components in a waveform. When spikes overlap and produce unknown patterns, the procedure extracts the constituent spikes and also estimates their exact time of occurrence. Fast implementation algorithms, having complexity of at most O (N log N), allow the use of the method in real-time applications.
Zouridakis
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Department of Neurosurgery, University of Texas-Houston Medical School 77030, USA.
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D000200:Action Potentials; D000465:Algorithms; D000818:Animals; D003400:Astacoidea; D004569:Electroencephalography / Q000379:methods; D004594:Electrophysiology / Q000379:methods*; D008954:Models, Biological; D009474:Neurons / Q000502:physiology*