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  • Research Article
  • Open Access

Reconstruction of Sensory Stimuli Encoded with Integrate-and-Fire Neurons with Random Thresholds

EURASIP Journal on Advances in Signal Processing20092009:682930

https://doi.org/10.1155/2009/682930

  • Received: 1 January 2009
  • Accepted: 4 April 2009
  • Published:

Abstract

We present a general approach to the reconstruction of sensory stimuli encoded with leaky integrate-and-fire neurons with random thresholds. The stimuli are modeled as elements of a Reproducing Kernel Hilbert Space. The reconstruction is based on finding a stimulus that minimizes a regularized quadratic optimality criterion. We discuss in detail the reconstruction of sensory stimuli modeled as absolutely continuous functions as well as stimuli with absolutely continuous first-order derivatives. Reconstruction results are presented for stimuli encoded with single as well as a population of neurons. Examples are given that demonstrate the performance of the reconstruction algorithms as a function of threshold variability.

Keywords

  • Hilbert Space
  • Continuous Function
  • Information Technology
  • Quantum Information
  • Optimality Criterion

Publisher note

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Authors’ Affiliations

(1)
Department of Electrical Engineering, Columbia University, New York, NY 10027, USA

Copyright

© A. A. Lazar and E. A. Pnevmatikakis. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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