Analysis, classification, and coding of multielectrode spike trains with hidden Markov models

DOI10.1007/BF00239623zbMath0800.92083OpenAlexW2022448907MaRDI QIDQ1337302

V. Pereyra

Publication date: 30 October 1994

Published in: Biological Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00239623

Mathematics Subject Classification ID

Neural biology (92C20)

Related Items (8)

Extracting State Transition Dynamics from Multiple Spike Trains Using Hidden Markov Models with Correlated Poisson Distribution ⋮ Discrete- and Continuous-Time Probabilistic Models and Algorithms for Inferring Neuronal UP and DOWN States ⋮ Attractor-state itinerancy in neural circuits with synaptic depression ⋮ Neural Decoding with Kernel-Based Metric Learning ⋮ Spatial-temporal clustering of neural data using linked-mixtures of hidden Markov models ⋮ Determining Burst Firing Time Distributions from Multiple Spike Trains ⋮ Bayesian analysis of the multivariate poisson distribution ⋮ Chaotic diffusion of dissipative solitons: from anti-persistent random walks to hidden Markov models

Cites Work

• Sequential methods in pattern recognition and machine learning
• A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Analysis, classification, and coding of multielectrode spike trains with hidden Markov models