Optimum signal in a simple neuronal model with signal-dependent noise |
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Authors: | Priscilla E Greenwood Petr Lánský |
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Institution: | (1) Department of Mathematics and Statistics, Arizona State University, Tempe, AZ 85287, USA;(2) Institute of Physiology, Academy of Sciences of the Czech Republic, Víde ská 1083, 142 20 Prague 4, Czech Republic |
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Abstract: | How does the information about a signal in neural threshold crossings depend on the noise acting upon it? Two models are explored, a binary McCulloch and Pitts (threshold exceedance) model and a model of waiting time to exceedance--a discrete-time version of interspike intervals. If noise grows linearly with the signal, we find the best identification of the signal in terms of the Fisher information is for signals that do not reach the threshold in the absence of noise. Identification attains the same precision under weak and strong signals, but the coding range decreases at both extremes of signal level. We compare the results obtained for Fisher information with those using related first and second moment measures. The maximum obtainable information is plotted as a function of the ratio of noise to signal. |
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