%0 Journal Article
%T Reconstruction of Sensory Stimuli Encoded with Integrate-and-Fire Neurons with Random Thresholds
%A Aurel A. Lazar
%A Eftychios A. Pnevmatikakis
%J EURASIP Journal on Advances in Signal Processing
%D 2009
%I Springer
%R 10.1155/2009/682930
%X 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.
%U http://dx.doi.org/10.1155/2009/682930