Intrinsic Computation of a Monod-Wyman-Changeux Molecule
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entropy-20-00599.pdf
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1.07 MB
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Adobe PDF
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8b3ac634890f2b55dc2f36befaca6e4c
Author(s)
Marzen, Sarah E.
Date Issued
August 2018
Journal
Entropy
Publisher
MDPI AG
Citation
Marzen, Sarah. "Intrinsic Computation of a Monod-Wyman-Changeux Molecule." Entropy 20, 8 (August 2018): 599 © 2018 The Authors
Version
Final published version
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. Keywords: statistical complexity; intrinsic computation; excess entropy
MIT Department
Massachusetts Institute of Technology. Department of Physics
Terms of Use
Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.3390/e20080599
