Implications of iterative communication for biological system performance

• Published in: Journal of theoretical biology 2018-01, Vol.436, p.93-104
• Main Authors: O'Connor, Michael P., O'Donnell, Sean
• Format: Article
• Language: English
• Subjects: Activation; Communication; Computer Simulation; Division of labor; Forgetting; Markov process; Models, Theoretical; Recruitment; Social behavior; Stochastic Processes; Time Factors; Transition matrix
• ISSN: 0022-5193; 1095-8541
• DOI: 10.1016/j.jtbi.2017.09.025

•The function of integrated biological systems can depend on subunit activity.•Iterative communication (cumulative interactions) can activate subunits.•A matrix model predicts patterns of subunit activation.•Rate and proportion of activation are predicted by key model parameters.•Iterative communication parameters may be under system-level selection. 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.