ArticleEntropy (Basel, Switzerland)2018
Intrinsic Computation of a Monod-Wyman-Changeux Molecule.
Article in Entropy (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Causal states are minimal sufficient statistics of prediction of a stochastic process, their coding cost is called statistical complexity, and the implied causal structure yields a sense of the process' "intrinsic computation". We discuss how statistical complexity changes with slight changes to the underlying model- in this case, a biologically-motivated dynamical model, that of a Monod-Wyman-Changeux molecule. Perturbations to kinetic rates cause statistical complexity to jump from finite to infinite. The same is not true for excess entropy, the mutual information between past and future, or for the molecule's transfer function. We discuss the implications of this for the relationship between intrinsic and functional computation of biological sensory systems.
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