Intrinsic computation of a Monod-Wyman-Changeux molecule
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 variations on a biologically-motivated dynamical model, that of a Monod-Wyman-Changeux molecule. Perturbations to nonexistent transitions cause statistical complexity to jump from finite to infinite, while perturbations to existent transitions cause relatively slight variations in the statistical complexity. The same is not true for excess entropy, the mutual information between past and future. We discuss the implications of this for the relationship between intrinsic and useful computation of biological sensory systems.
Keywords
Cite
@article{arxiv.1705.04893,
title = {Intrinsic computation of a Monod-Wyman-Changeux molecule},
author = {Sarah Marzen},
journal= {arXiv preprint arXiv:1705.04893},
year = {2018}
}
Comments
The main claim of the paper is actually incorrect due to a huge technical error, and although there are still correct results in this paper, this paper as written should be withdrawn