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Spike Sorting

Spike sorting is a class of techniques used in the analysis of electrophysiological data. Spike sorting algorithms use the shape(s) of waveforms collected with one or more electrodes in the brain to distinguish the activity of one or more neurons from background electrical noise.

Papers

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Showing 21–30 of 51 papers

TitleStatusHype
SpikeDeep-Classifier: A deep-learning based fully automatic offline spike sorting algorithm—0
SpikeSift: A Computationally Efficient and Drift-Resilient Spike Sorting Algorithm—0
The functional mean-shift algorithm for mode hunting and clustering in infinite dimensions—0
Three-dimensional spike localization and improved motion correction for Neuropixels recordings—0
Unsupervised Spike Sorting Based on Discriminative Subspace Learning—0
Validation of neural spike sorting algorithms without ground-truth information—0
Variational Particle Approximations—0
68-Channel Highly-Integrated Neural Signal Processing PSoC with On-Chip Feature Extraction, Compression, and Hardware Accelerators for Neuroprosthetics in 22nm FDSOI—0
Evaluation of spike sorting algorithms: Simulations and application to human Subthalamic Nucleus recordings—0
Fast Convolutional Dictionary Learning off the Grid—0
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