Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Elements of information theory
Elements of information theory
Neuronal tuning: to sharpen or broaden
Neural Computation
Narrow versus wide turning curves: what's best for a population code?
Neural Computation
Population coding and decoding in a neural field: a computational study
Neural Computation
Representational accuracy of stochastic neural populations
Neural Computation
Optimal short-term population coding: when fisher information fails
Neural Computation
Multidimensional Encoding Strategy of Spiking Neurons
Neural Computation
Parameter extraction from population codes: A critical assessment
Neural Computation
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The efficiency of neuronal encoding in sensory and motor systems has been proposed as a first principle governing response properties within the central nervous system. We present a continuation of a theoretical study presented by Zhang and Sejnowski, where the influence of neuronal tuning properties on encoding accuracy is analyzed using information theory. When a finite stimulus space is considered, we show that the encoding accuracy improves with narrow tuning for one-and two-dimensional stimuli. For three dimensions and higher, there is an optimal tuning width.