Spike sorting using locality preserving projection with gap statistics and landmark-based spectral clustering
Data(s) |
30/12/2014
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Resumo |
Understanding 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. |
Identificador | |
Idioma(s) |
eng |
Publicador |
Elsevier BV |
Relação |
http://dro.deakin.edu.au/eserv/DU:30069971/nguyen-spikesortingusing-2014.pdf http://www.dx.doi.org/10.1016/j.jneumeth.2014.09.011 http://www.ncbi.nlm.nih.gov/pubmed/25256647 |
Direitos |
2014, Elsevier BV |
Palavras-Chave | #Feature extraction #Gap statistics #Landmark-based spectral clustering #Locality preserving projection #Spike sorting #Superparamagnetic clustering #Wavelet transformation #Science & Technology #Life Sciences & Biomedicine #Biochemical Research Methods #Neurosciences #Biochemistry & Molecular Biology #Neurosciences & Neurology #RECORDINGS #CLASSIFICATION |
Tipo |
Journal Article |