Output Stream of Binding Neuron with Feedback

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Author(s): Alexander Vidybida (Bogolyubov Institute for Theoretical Physics, Ukraine)and Kseniya Kravchuk (Bogolyubov Institute for Theoretical Physics, Ukraine)
Copyright: 2011
Pages: 34
Source title: Knowledge-Based Intelligent System Advancements: Systemic and Cybernetic Approaches
Source Author(s)/Editor(s): Jerzy Jozefczyk (Wroclaw University of Technology, Poland)and Donat Orski (Wroclaw University of Technology, Poland)
DOI: 10.4018/978-1-61692-811-7.ch010

Keywords: Artificial Intelligence / Cybernetics / Information Science Reference / Media & Communications

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Abstract

The binding neuron (BN) output firing statistics is considered. The neuron is driven externally by the Poisson stream of intensity

. The influence of the feedback, which conveys every output impulse to the input with time delay

, on the statistics of BN's output spikes is considered. The resulting output stream is not Poissonian, and we look for its interspike intervals (ISI) distribution for the case of BN, BN with instantaneous,

, and delayed,

, feedback. For the BN with threshold 2 an exact mathematical expressions as functions of

and BN's internal memory,

are derived for the ISI distribution, output intensity and ISI coefficient of variation. For higher thresholds these quantities are found numerically. The distributions found for the case of instantaneous feedback include jumps and derivative discontinuities and differ essentially from those obtained for BN without feedback. Statistics of a neuron with delayed feedback has remarkable peculiarities as compared to the case of

. ISI distributions, found for delayed feedback, are characterized with jumps, derivative discontinuities and include singularity of Dirac's

-function type. The obtained ISI coefficient of variation is a unimodal function of input intensity, with the maximum value considerably bigger than unity. It is concluded that delayed feedback presence can radically alter neuronal output firing statistics.

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