Homotopy Theoretic and Categorical Models of Neural Information Networks

We propose a mathematical formalism for neural information networks endowed with assignments of resources (computational or metabolic or informational), suitable for describing assignments of concurrent or distributed computing architectures and associated binary codes, governed by a categorical form of the Hopfield network dynamics, and measures of informational complexity in the form of a cohomological version of integrated information.

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