Abstract
The signal activity in a neural net will be constrained both by its physical structure and by environmental constraints. By monitoring its signal activity a neural system can build up a simultaneous functional order that encodes these constraints. We have previously (Part I) presented two models that construct a simultaneous functional order in a collection of neural elements using either signal-covariances or signal-coincides. In this paper we present the results of simulation experiments that were performed to study the influence of the physical constraints of a neural system on the simultaneous functional order produced by both models. In the simulation experiments we used a one-dimensional detector array. We delineate the physical constraints such an array has to satisfy in order to induce a functional order relation that allows an isomorphism with a geometrical order. We show that for an appropriate choice of the system parameters both models can produce a simultaneous functional order with sufficient internal coherence to allow isomorphisms with a triangulation. In this case the dimensionality and the coherence of the detector array are objectively available to the system itself.
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Toet, A., Blom, J. & Koenderink, J.J. The construction of a simultaneous functional order in nervous systems. Biol. Cybern. 58, 275–286 (1988). https://doi.org/10.1007/BF00364132
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DOI: https://doi.org/10.1007/BF00364132