Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits / by Dorian Florescu

By:

Florescu, Dorian [aut]

Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Springer Theses, Recognizing Outstanding Ph.D. Research | SpringerLink Bücher | Springer eBook Collection EngineeringPublisher: Cham : Springer, 2017Description: Online-Ressource (XIV, 139 p. 42 illus., 27 illus. in color, online resource)ISBN:

9783319570815

Subject(s):

Additional physical formats: 9783319570808 | Druckausg.: 978-3-319-57080-8 | Printed edition: 9783319570808 MSC: MSC: *92-02 | 92C20 | 92B20 | 00A71 | 92-08LOC classification:

TK5102.9 TA1637-1638 TK7882.S65
TK5102.9
TA1637-1638
TK7882.S65

DOI: DOI: 10.1007/978-3-319-57081-5Online resources:

Summary: 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 a linear filter, given the input of the filter encoded with the same neuron modelSummary: Nomenclature -- Acronyms -- 1 Introduction -- 2 Time Encoding and Decoding in Bandlimited and Shift-Invariant Spaces -- 3 A Novel Framework for Reconstructing Bandlimited Signals Encoded by Integrate and-Fire Neurons -- 4 A Novel Reconstruction Framework in Shift-Invariant Spaces for Signals Encoded with Integrate-and-Fire Neurons -- 5 A New Approach to the Identification of Sensory Processing Circuits Based on Spiking Neuron Data -- 6 A New Method for Implementing Linear Filters in the Spike Domain -- 7 Conclusions and Future Work -- BibliographyPPN: PPN: 1658327527Package identifier: Produktsigel: ZDB-2-ENG

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