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Spike sorting using locality preserving projection with gap statistics and landmark-based spectral clustering
journal contribution
posted on 2014-12-30, 00:00 authored by Thanh Thi Nguyen, Abbas KhosraviAbbas Khosravi, Douglas CreightonDouglas Creighton, Saeid NahavandiUnderstanding neural functions requires knowledge from analysing electrophysiological data. The process of assigning spikes of a multichannel signal into clusters, called spike sorting, is one of the important problems in such analysis. There have been various automated spike sorting techniques with both advantages and disadvantages regarding accuracy and computational costs. Therefore, developing spike sorting methods that are highly accurate and computationally inexpensive is always a challenge in the biomedical engineering practice.
History
Journal
Journal of neuroscience methodsVolume
238Pagination
43 - 53Publisher
Elsevier BVLocation
Amsterdam, NetherlandsPublisher DOI
ISSN
0165-0270eISSN
1872-678XLanguage
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2014, Elsevier BVUsage metrics
Categories
No categories selectedKeywords
Feature extractionGap statisticsLandmark-based spectral clusteringLocality preserving projectionSpike sortingSuperparamagnetic clusteringWavelet transformationScience & TechnologyLife Sciences & BiomedicineBiochemical Research MethodsNeurosciencesBiochemistry & Molecular BiologyNeurosciences & NeurologyRECORDINGSCLASSIFICATION