Bayesian Modeling and Classification of Neural Signals

DOI10.1162/neco.1994.6.5.1005zbMath0810.92004OpenAlexW2025462430MaRDI QIDQ4323336

Michael S. Lewicki

Publication date: 6 April 1995

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://authors.library.caltech.edu/13668/

zbMATH Keywords

efficient algorithmBayesian probability theoryaction potential shapesdecomposition of arbitrarily complex overlap sequencesextracellular neural waveformsform and number of spike shapes

Mathematics Subject Classification ID

Bayesian inference (62F15) Neural biology (92C20) Applications of statistics (62P99)

Related Items (7)

Automatic Spike Sorting Using Tuning Information ⋮ Bayes optimal template matching for spike sorting -- combining Fisher discriminant analysis with optimal filtering ⋮ A Detailed and Fast Model of Extracellular Recordings ⋮ Spike detection methods for polytrodes and high density microelectrode arrays ⋮ Real‐time signal processing for high‐density microelectrode array systems ⋮ Estimating the number of neurons in multi-neuronal spike trains ⋮ Fast simulation of extracellular action potential signatures based on a morphological filtering approximation

Cites Work

• Multidimensional binary search trees used for associative searching
• An Algorithm for Finding Best Matches in Logarithmic Expected Time
• Robust Estimation of the First-Order Autoregressive Parameter

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