We propose a hidden Markov model (HMM) based method for combined detecting and sorting of spikes, with the aim of improving the final decoding accuracy of BCIs.
Sep 15, 2008 · Our spike-sorting technique is based on hidden variables that each represent the phase of an action potential cycle of a cell. For didactic ...
In this paper, hidden Markov models (HMM) is studied for spike sorting. We notice that HMM state sequences have capability to represent spikes precisely and ...
Recently \cite{Herbst:2008kn} , introduced a spike sorting algorithm based on fitting a Hidden Markov Model to the joint firing of neurons producing a recorded ...
Hidden Markov models (HMMs) can serve as generative models for continuous extracellular data records. These models naturally combine the spike detection and ...
In this paper, hidden Markov models (HMM) is studied for spike sorting. We notice that HMM state sequences have capability to represent spikes precisely and ...
Dec 12, 2018 · Spike detection and spike sorting with a hidden Markov model improves offline decoding of motor cortical recordings.
Hidden Markov models (HMMs) can serve as generative models for continuous extracellular data records. These models naturally combine the spike detection and ...
In this work, we introduce an original idea based on Hidden Markov Models (HMM) which helps to improve the spike sorting stage. Our idea is a fast and simple ...
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In this paper, hidden Markov models (HMM) is studied for spike sorting. We notice that HMM state sequences have capability to represent spikes precisely and ...