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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
Neuromorphic Online Clustering and Classification—0
NeuSort: An Automatic Adaptive Spike Sorting Approach with Neuromorphic Models—0
On the Analysis of Multi-Channel Neural Spike Data—0
Power efficient Spiking Neural Network Classifier based on memristive crossbar network for spike sorting application—0
Pulse Processing -- Overview and Challenges—0
Scalable 49-Channel Neural Recorder with an Event-Driven Ramp ADC and PCA Compression in 28 nm CMOS—0
SimSort: A Data-Driven Framework for Spike Sorting by Large-Scale Electrophysiology Simulation—0
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
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