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Integr Comp Biol. 2014 Jul;54(2):223-37. doi: 10.1093/icb/icu050. Epub 2014 Jun 3.

Feedback control as a framework for understanding tradeoffs in biology.

Author information

1
*Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Department of Biology, University of Washington, Seattle, WA 98195, USA; Department of Biological Sciences, New Jersey Institute of Technology, Newark, NJ 07102, USA ncowan@jhu.edu.
2
*Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Department of Biology, University of Washington, Seattle, WA 98195, USA; Department of Biological Sciences, New Jersey Institute of Technology, Newark, NJ 07102, USA.

Abstract

Control theory arose from a need to control synthetic systems. From regulating steam engines to tuning radios to devices capable of autonomous movement, it provided a formal mathematical basis for understanding the role of feedback in the stability (or change) of dynamical systems. It provides a framework for understanding any system with regulation via feedback, including biological ones such as regulatory gene networks, cellular metabolic systems, sensorimotor dynamics of moving animals, and even ecological or evolutionary dynamics of organisms and populations. Here, we focus on four case studies of the sensorimotor dynamics of animals, each of which involves the application of principles from control theory to probe stability and feedback in an organism's response to perturbations. We use examples from aquatic (two behaviors performed by electric fish), terrestrial (following of walls by cockroaches), and aerial environments (flight control by moths) to highlight how one can use control theory to understand the way feedback mechanisms interact with the physical dynamics of animals to determine their stability and response to sensory inputs and perturbations. Each case study is cast as a control problem with sensory input, neural processing, and motor dynamics, the output of which feeds back to the sensory inputs. Collectively, the interaction of these systems in a closed loop determines the behavior of the entire system.

PMID:
24893678
DOI:
10.1093/icb/icu050
[Indexed for MEDLINE]

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