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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 11–20 of 51 papers

TitleStatusHype
L-Sort: On-chip Spike Sorting with Efficient Median-of-Median Detection and Localization-based Clustering—0
Inferring collective synchrony observing spiking of one or several neurons—0
E-Sort: Empowering End-to-end Neural Network for Multi-channel Spike Sorting with Transfer Learning and Fast Post-processingCode0
68-Channel Highly-Integrated Neural Signal Processing PSoC with On-Chip Feature Extraction, Compression, and Hardware Accelerators for Neuroprosthetics in 22nm FDSOI—0
L-Sort: An Efficient Hardware for Real-time Multi-channel Spike Sorting with Localization—0
Neuromorphic Online Clustering and Classification—0
NeuSort: An Automatic Adaptive Spike Sorting Approach with Neuromorphic Models—0
Adaptive SpikeDeep-Classifier: Self-organizing and self-supervised machine learning algorithm for online spike sorting—0
Edge computing on TPU for brain implant signal analysisCode0
Zydeco-Style Spike Sorting Low Power VLSI Architecture for IoT BCI Implants—0
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