Spiking neural circuits with dendritic stimulus processors. Encoding, decoding, and identification in reproducing kernel Hilbert spaces

DOI10.1007/S10827-014-0522-8zbMath1409.92012OpenAlexW1236573242WikidataQ51045657 ScholiaQ51045657MaRDI QIDQ1732652

Yevgeniy B. Slutskiy, Aurel A. Lazar

Publication date: 25 March 2019

Published in: Journal of Computational Neuroscience (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10827-014-0522-8

zbMATH Keywords

dendritic stimulus processorschannel identification machinestime encoding machinesspiking neural circuitsdendritic computationnonlinear stimulus processingVolterra CIMsVolterra TDMsVolterra TEMs

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20) Computational methods for problems pertaining to biology (92-08)

Related Items (3)

Identification of Linear and Nonlinear Sensory Processing Circuits from Spiking Neuron Data ⋮ Sparse functional identification of complex cells from spike times and the decoding of visual stimuli ⋮ Learning with Precise Spike Times: A New Decoding Algorithm for Liquid State Machines

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• Perfect Recovery and Sensitivity Analysis of Time Encoded Bandlimited Signals
• Population Encoding With Hodgkin–Huxley Neurons
• Functional Identification of Spike-Processing Neural Circuits

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