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Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits
Paperback
Series: Springer Theses
Medical ReferenceTechnology & EngineeringGeneral Mathematics
ISBN13: 9783319860725
Publisher: Springer Nature
Published: Jul 25 2018
Pages: 139
Weight: 0.50
Height: 0.33 Width: 6.14 Depth: 9.21
Language: English
This work is motivated by the ongoing open question of how information in the outside world is represented and processed by the brain. Consequently, several novel methods are developed.
A new mathematical formulation is proposed for the encoding and decoding of analog signals using integrate-and-fire neuron models. Based on this formulation, a novel algorithm, significantly faster than the state-of-the-art method, is proposed for reconstructing the input of the neuron.
Two new identification methods are proposed for neural circuits comprising a filter in series with a spiking neuron model. These methods reduce the number of assumptions made by the state-of-the-art identification framework, allowing for a wider range of models of sensory processing circuits to be inferred directly from input-output observations.
A third contribution is an algorithm that computes the spike time sequence generated by an integrate-and-fire neuron model in response to the output of alinear filter, given the input of the filter encoded with the same neuron model.1 different editions
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