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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 1–10 of 51 papers

TitleStatusHype
An automatic spike sorting algorithm based on adaptive spike detection and a mixture of skew-t distributionsCode1
Short and Sparse Deconvolution --- A Geometric ApproachCode1
Short-and-Sparse Deconvolution -- A Geometric ApproachCode1
Neural Clustering ProcessesCode1
Scalable 49-Channel Neural Recorder with an Event-Driven Ramp ADC and PCA Compression in 28 nm CMOS—0
A Real-time and Hardware Efficient Artfecat-free Spike Sorting Using Deep Spike Detection—0
SpikeSift: A Computationally Efficient and Drift-Resilient Spike Sorting Algorithm—0
FS-SS: Few-Shot Learning for Fast and Accurate Spike Sorting of High-channel Count Probes—0
Pulse Processing -- Overview and Challenges—0
SimSort: A Data-Driven Framework for Spike Sorting by Large-Scale Electrophysiology Simulation—0
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