Evolution of analog circuit models of ion channels

  • Authors:

  • Theodore W. Cornforth;Kyung-Joong Kim;Hod Lipson

  • Affiliations:

  • Department of Biological Statistics and Computational Biology, Cornell University, Ithaca;Department of Computer Engineering, Sejong University, Seoul, Republic of Korea;Department of Mechanical and Aerospace Engineering, Cornell University, Ithaca

  • Venue:
  • ICES'10 Proceedings of the 9th international conference on Evolvable systems: from biology to hardware
  • Year:
  • 2010

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Abstract

Analog circuits have long been used to model the electrical properties of biological neurons. For example, the classic Hodgkin-Huxley model represents ion channels embedded in a neuron's cell membrane as a capacitor in parallel with batteries and resistors. However, to match the predictions of the model with their empirical electrophysiological data, Hodgkin and Huxley described the nonlinear resistors using a complex system of coupled differential equations, a celebrated feat that required exceptional creativity and insight. Here, we use evolutionary circuit design to emulate such leaps of human creativity and automatically construct equivalent circuits for neurons. Using only direct electrophysiological observations, the system evolved circuits out of basic electronic components that accurately simulate the behavior of sodium and potassium ion channels. This approach has the potential to serve both as a modeling tool to reverse engineer complex neurophysiological systems and as an assistant in the task of hand-designing neuromorphic circuits.