Informational entropies, although proved to be useful in the evaluation of nervous function, are suitable just if we assume that nervous activity takes place under ergo dic conditions. However, widespread claims suggest that the brain operates in a non-ergodic framework. Here we show that a topological concept, namely the Borsuk-Ulam theorem, is able to wipe away this long-standing limit of both Shannon entropy and its generalizations, such as Rényi’s. We demonstrate that both ergodic and non-ergodic informational entropies can be evaluated and quantified through topological methods, in order to improve our knowledge of central nervous system function.
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[v1] 2016-10-04 03:49:52
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