Spike Train Decoding Without Spike Sorting

Spike Train Decoding Without Spike Sorting

We propose a novel paradigm for spike train decoding, which avoids entirely spike sorting based on waveform measurements. This paradigm directly uses the spike train collected at recording electrodes from thresholding the bandpassed voltage signal. Our approach is a paradigm, not an algorithm, since it can be used with any of the current decoding algorithms, such as population vector or likelih...

A Brief Look into Spike Sorting Methods

Spike sorting is a class of techniques used in the analysis of electrophysiological data. Studying the dynamics of neural activity via electrical recording relies on the ability to detect and sort neural spikes recorded from a number of neurons by the same electrode. This article reviews methods for detecting and classifying action potentials, a problem commonly referred to as spike sorting.

Spike Train

Spike sorting

Figure 1. Extracellular recordings and spike sorting. (A) The extracellular activity of neurons is recorded with microwires inserted in the brain. The spikes of neurons close-by the electrode tip (in red and blue) can be separated via spike sorting; neurons further away (in dark grey) can be detected but not sorted, thus generating the multiunit activity; more distant neurons (in light gray) co...

Spiking Neural Networks for Cortical Neuronal Spike Train Decoding

Recent investigation of cortical coding and computation indicates that temporal coding is probably a more biologically plausible scheme used by neurons than the rate coding used commonly in most published work. We propose and demonstrate in this letter that spiking neural networks (SNN), consisting of spiking neurons that propagate information by the timing of spikes, are a better alternative t...