Journal article
A neural network-based spike discriminator
Journal of neuroscience methods, Vol.54(1), pp.9-22
09/01/1994
DOI: 10.1016/0165-0270(94)90155-4
PMID: 7815823
Abstract
A software routine to reconstruct individual spike trains from multi-neuron, single-channel extracellular recordings was designed. Using a neural network algorithm that automatically clusters and sorts the spikes, the only user input needed is the threshold level for spike detection and the number of unit types present in the recording. Adaptive features are included in the algorithm to allow for tracking of spike trains during periods of amplitude variation and also to identify noise spikes. The routine will operate on-line during extracellular studies of the cochlear nucleus in cats.
Details
- Title: Subtitle
- A neural network-based spike discriminator
- Creators
- John S. Oghalai - University of Wisconsin–MadisonW.Nick Street - University of Wisconsin–MadisonWilliam S. Rhode - University of Wisconsin–Madison
- Resource Type
- Journal article
- Publication Details
- Journal of neuroscience methods, Vol.54(1), pp.9-22
- Publisher
- Elsevier B.V
- DOI
- 10.1016/0165-0270(94)90155-4
- PMID
- 7815823
- ISSN
- 0165-0270
- eISSN
- 1872-678X
- Language
- English
- Date published
- 09/01/1994
- Academic Unit
- Bus Admin College; Nursing; Computer Science; Business Analytics
- Record Identifier
- 9984380517502771
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