A unified framework and method for automatic neural spike identification.
about
Past, present and future of spike sorting techniquesSpike sorting for large, dense electrode arraysUnified selective sorting approach to analyse multi-electrode extracellular data.Improving data quality in neuronal population recordings.Spike Detection for Large Neural Populations Using High Density Multielectrode Arrays.A real-time spike classification method based on dynamic time warping for extracellular enteric neural recording with large waveform variabilitySorting Overlapping Spike Waveforms from Electrode and Tetrode Recordings.Recent progress in multi-electrode spike sorting methods.Inferring sparse representations of continuous signals with continuous orthogonal matching pursuit.Bayes optimal template matching for spike sorting - combining fisher discriminant analysis with optimal filtering.Spike sorting of synchronous spikes from local neuron ensembles.Automated long-term recording and analysis of neural activity in behaving animals.High-dimensional cluster analysis with the masked EM algorithm.A Fully Automated Approach to Spike Sorting.The Impact of Anesthetic State on Spike-Sorting Success in the Cortex: A Comparison of Ketamine and Urethane Anesthesia.
P2860
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P2860
A unified framework and method for automatic neural spike identification.
description
2013 nî lūn-bûn
@nan
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
2013年论文
@zh
2013年论文
@zh-cn
name
A unified framework and method for automatic neural spike identification.
@en
type
label
A unified framework and method for automatic neural spike identification.
@en
prefLabel
A unified framework and method for automatic neural spike identification.
@en
P2860
P1476
A unified framework and method for automatic neural spike identification.
@en
P2093
Chaitanya Ekanadham
Daniel Tranchina
P2860
P356
10.1016/J.JNEUMETH.2013.10.001
P577
2013-10-30T00:00:00Z