Entropy and local uncertainty of data from sensory neurons

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Abstract
We present an empirical comparison between neural interspike interval sequences obtained from two different kinds of sensory receptors. Both differ in their internal structure as well as in the strength of correlations and the degree of predictability found in the respective spike trains. As a further tool in this context, we suggest the local uncertainty, assigning a well-defined predictability to individual spikes. The local uncertainty is demonstrated to reveal significant patterns within the interspike interval sequences, even when its overall structure is (almost) random. Our approach is based on the concept of symbolic dynamics and information theory.