Nicoletti Giorgio, Busiello Daniel Maria
Laboratory of Interdisciplinary Physics, Department of Physics and Astronomy "G. Galilei," University of Padova, Padova 35121, Italy.
Institute of Physics, École Polytechnique Fédérale de Lausanne-EPFL, 1015 Lausanne, Switzerland.
Phys Rev E. 2022 Jul;106(1-1):014153. doi: 10.1103/PhysRevE.106.014153.
Biochemistry, ecology, and neuroscience are examples of prominent fields aiming at describing interacting systems that exhibit nontrivial couplings to complex, ever-changing environments. We have recently shown that linear interactions and a switching environment are encoded separately in the mutual information of the overall system. Here we first generalize these findings to a broad class of nonlinear interacting models. We find that a new term in the mutual information appears, quantifying the interplay between nonlinear interactions and environmental changes, and leading to either constructive or destructive information interference. Furthermore, we show that a higher mutual information emerges in out-of-equilibrium environments with respect to an equilibrium scenario. Finally, we generalize our framework to the case of continuously varying environments. We find that environmental changes can be mapped exactly into an effective spatially varying diffusion coefficient, shedding light on modeling of biophysical systems in inhomogeneous media.
生物化学、生态学和神经科学是旨在描述与复杂多变环境呈现非平凡耦合的相互作用系统的突出领域的例子。我们最近表明，线性相互作用和切换环境分别编码在整个系统的互信息中。在此，我们首先将这些发现推广到一类广泛的非线性相互作用模型。我们发现互信息中出现了一个新项，它量化了非线性相互作用与环境变化之间的相互作用，并导致建设性或破坏性的信息干扰。此外，我们表明，相对于平衡场景，在非平衡环境中会出现更高的互信息。最后，我们将我们的框架推广到环境连续变化的情况。我们发现环境变化可以精确地映射到一个有效的空间变化扩散系数，这为非均匀介质中生物物理系统的建模提供了启示。
