Journal article
Implications of iterative communication for biological system performance
Journal of theoretical biology, v 436, pp 93-104
07 Jan 2018
PMID: 28987465
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The performance of integrated biological systems can often be described by the behavior of component subunits: the proportion of subunits performing an activity, and the rate of recruitment to the activity, can be relevant to system performance. We develop a model for activation of subunits (receivers) to a task when activation requires repeated signals (iterative communication). The model predicts how system performance will be affected by the parameters of iterative communication. Receiver activation is influenced by the frequency of stimulation, by forgetting about past interactions, and by the number of stimuli needed to activate the receivers. These parameters, along with the probability of activated receivers returning to a de-activated state, modulate the system-wide time course of activation and the steady-state proportion of activated receivers. Parameters can interact to affect system-wide activation, and multiple parameter combinations can yield similar patterns of activation. Group performance is less variable at higher stimulation frequencies and in systems with greater numbers of receivers. Biological constraints on iterative communication, such as time and energy costs, may limit the parameter values that are feasible for a given system. Iterative communication parameters may be subject to natural selection at the system (group) level because they affect system performance.
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Details
- Title
- Implications of iterative communication for biological system performance
- Creators
- Michael P O'Connor - Drexel UniversitySean O'Donnell - Drexel University
- Publication Details
- Journal of theoretical biology, v 436, pp 93-104
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Biodiversity, Earth, and Environmental Science (BEES)
- Web of Science ID
- WOS:000415662800010
- Scopus ID
- 2-s2.0-85031754074
- Other Identifier
- 991019168098904721
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- Web of Science research areas
- Biology
- Mathematical & Computational Biology