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Neurons exhibit high-frequency fluctuations of firing-rates which could either be noise or carry information. Rate coding models suggest that these irregularities are noise, but this seems to be an inadequate explanation for a common occurrence. If the nervous system used only rate codes to convey information, evolution should have developed a more consistent, regular firing rate.<ref>J. Leo van Hemmen, TJ Sejnowski. 23 Problems in Systems Neuroscience. Oxford Univ. Press, 2006. p.143-158.</ref> The theory of temporal coding offers another solution to the problem of noise by suggesting that the apparent randomness of spikes is not completely arbitrary, but instead encodes information. This solution supplies an explanation for the “noise” and allows for a more information-rich code. To model this idea, binary symbols can be used to mark the spikes: 1 for a spike, 0 for no spike. Temporal coding allows the sequence 000111000111 to mean something different than 001100110011, even though the mean rate of firing is the same for both sequences, at 6 spikes/10 msec.<ref name="Theunissen F 1995"/>
Until recently, scientists had put the most emphasis on rate encoding, or using the mean frequency of spikes to convey information about the stimulus. However, functions of the brain are more temporally precise than mere rate encoding would seem to allow. In other words, essential information would be lost due to the inability of the rate code to capture all the available information of the spike train. In addition, responses are
==Evidence==
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