Reconstruction, identification and implementation methods for spiking neural circuits

• Main Author: Florescu, Dorian, (Author)
• Format: eBook
• Language: English
• Published: Cham, Switzerland : Springer, 2017.
• Series: Springer theses.
• Subjects: Neural circuitry.; elektronické knihy; electronic books
• ISBN: 9783319570815; 9783319570808
• Physical Description: 1 online resource (xiv, 139 pages) : illustrations (some color)
• Item Description: "Doctoral thesis accepted by the University of Sheffield, Sheffield, UK."
• Access: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty

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 model.