Sequential estimation of intrinsic activity and synaptic input in single neurons by particle filtering with optimal importance density

Sequential estimation of intrinsic activity and synaptic input in single neurons by particle filtering with optimal importance density

Abstract This paper deals with the problem of inferring the signals and parameters that cause neural activity to occur. The ultimate challenge being to unveil brain’s connectivity, here we focus on a microscopic vision of the problem, where single neurons (potentially connected to a network of peers...

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Bibliographic Details
Main Authors: Pau Closas, Antoni Guillamon
Format: Article
Language:English
Published: SpringerOpen 2017-09-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
State-space models
Inference and learning
Particle filtering
Synaptic conductance estimation
Spiking neuron
Conductance-based model
Online Access:http://link.springer.com/article/10.1186/s13634-017-0499-3

Internet

http://link.springer.com/article/10.1186/s13634-017-0499-3

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