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Original Article

Korean J Physiol Pharmacol 2011; 15(6): 371-382

Published online December 28, 2011

Copyright © Korean J Physiol Pharmacol.

A Computational Model of the Temperature-dependent Changes in Firing Patterns in Aplysia Neurons

Nam Gyu Hyun1,*, Kwang-Ho Hyun2, Kwang-Beom Hyun2, Jin-Hee Han3, Kyungmin Lee4, and Bong-Kiun Kaang5,†

1Department of Physics, Jeju National University, Jeju 690-756, 2Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 3Department of Biological Sciences, KAIST Institute for the Bio Century (KIB), KAIST, Daejeon 305-701, 4Department of Anatomy, Graduate School of Medicine, Kyungpook National University, Daegu 700-422, 5National Creative Research Initiative Center for Memory, Departments of Biological Sciences and Brain and Cognitive Sciences, College of Natural Science, Seoul National University, Seoul 151-747, Korea

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.


We performed experiments using Aplysia neurons to identify the mechanism underlying the changes in the firing patterns in response to temperature changes. When the temperature was gradually increased from 11oC to 31oC the firing patterns changed sequentially from the silent state to beating, doublets, beating-chaos, bursting-chaos, square-wave bursting, and bursting-oscillation patterns. When the temperature was decreased over the same temperature range, these sequential changes in the firing patterns reappeared in reverse order. To simulate this entire range of spiking patterns we modified nonlinear differential equations that Chay and Lee made using temperature-dependent scaling factors. To refine the equations, we also analyzed the spike pattern changes in the presence of potassium channel blockers. Based on the solutions of these equations and potassium channel blocker experiments, we found that, as temperature increases, the maximum value of the potassium channel relaxation time constant, Քn(t) increases, but the maximum value of the probabilities of openings for activation of the potassium channels, n(t) decreases. Accordingly, the voltage-dependent potassium current is likely to play a leading role in the temperature-dependent changes in the firing patterns in Aplysia neurons.

Keywords: Aplysia, Bursting, Doublet, Temperature-dependent scaling factor, Computer simulation