2 results match your criteria: "and Center for Neural Science New York University New York[Affiliation]"
Adv Neural Inf Process Syst
December 2011
Howard Hughes Medical Institute and Center for Neural Science New York University New York, NY 10003.
Efficient coding provides a powerful principle for explaining early sensory coding. Most attempts to test this principle have been limited to linear, noiseless models, and when applied to natural images, have yielded oriented filters consistent with responses in primary visual cortex. Here we show that an efficient coding model that incorporates biologically realistic ingredients - input and output noise, nonlinear response functions, and a metabolic cost on the firing rate - predicts receptive fields and response nonlinearities similar to those observed in the retina.
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January 2010
Howard Hughes Medical Institute, and Center for Neural Science New York University New York, NY 10003.
Optimal coding provides a guiding principle for understanding the representation of sensory variables in neural populations. Here we consider the influence of a prior probability distribution over sensory variables on the optimal allocation of neurons and spikes in a population. We model the spikes of each cell as samples from an independent Poisson process with rate governed by an associated tuning curve.
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