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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

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