The NEURON simulation environment
Neural Computation
Neural Computation
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We investigate whether the inactivation properties of Na^+ channels in squid giant axons show evidence of having been optimized by evolution so as to reduce the energy expenditure associated with propagating action potentials. Using Hodgkin-Huxley-type models of the squid giant axon and varying the voltage dependence and overall scaling of the Na^+ inactivation rate, we find that faster inactivation rates correspond to less costly and more energy-efficient action potentials. However, and in contrast to the case when the ionic conductances and axon diameters are varied, the metabolic energy consumption does not have a minimum when restricted to an isovelocity curve in the phase space associated with these inactivation parameters. This failure-to-optimize encourages other hypotheses about the evolution and functionality of inactivation, such as its effects on information rates.