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Clustering neural spike trains with transient responses
2008
2008 47th IEEE Conference on Decision and Control
The detection of transient responses, i.e. nonstationarities, that arise in a varying and small fraction of the total number of neural spike trains recorded from chronically implanted multielectrode grids becomes increasingly difficult as the number of electrodes grows. This paper presents a novel application of an unsupervised neural network for clustering neural spike trains with transient responses. This network is constructed by incorporating projective clustering into an adaptive resonance
doi:10.1109/cdc.2008.4738729
dblp:conf/cdc/HunterWM08
fatcat:mzxmldn45rbk5ayuafufkkz7p4