Journal
EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING
Volume -, Issue -, Pages -Publisher
SPRINGEROPEN
DOI: 10.1155/2009/682930
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Funding
- NIH [R01 DC008701-01]
- NSF [CCF-06-35252]
- Onassis Public Benefit Foundation
- NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS [R01DC008701] Funding Source: NIH RePORTER
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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. Copyright (C) 2009 A. A. Lazar and E. A. Pnevmatikakis.
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