2018/04/12 by Andrew W. Eckford, Peter Thomas, Eckford, Andrew W. +1 · 1 citation
Engineering · Neuroscience · #FOS: Biological sciences #FOS: Computer and information sciences #Information Theory (cs.IT) #Molecular Communication and Nanonetworks #Molecular Networks (q-bio.MN) #Neural dynamics and brain function #Photoreceptor and optogenetics research
paper · pdf · doi:10.48550/arxiv.1804.04533
openalex publication_date 2018/04/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Biological systems transduce signals from their surroundings through a myriad\nof pathways. In this paper, we describe signal transduction as a communication\nsystem: the signal transduction receptor acts as the receiver in this system,\nand can be modeled as a finite-state Markov chain with transition rates\ngoverned by the input signal. Using this general model, we give the mutual\ninformation under IID inputs in discrete time, and obtain the mutual\ninformation in the continuous-time limit. We show that the mutual information\nhas a concise closed-form expression with clear physical significance. We also\ngive a sufficient condition under which the Shannon capacity is achieved with\nIID inputs. We illustrate our results with three examples: the light-gated\nChannelrhodopsin-2 (ChR2) receptor; the ligand-gated nicotinic acetylcholine\n(ACh) receptor; and the ligand-gated Calmodulin (CaM) receptor. In particular,\nwe show that the IID capacity of the ChR2 receptor is equal to its Shannon\ncapacity. We finally discuss how the results change if only certain properties\nof each state can be observed, such as whether an ion channel is open or\nclosed.\n