Action Potential Energetics at the Organismal Level Reveal a Trade-Off in Efficiency at High Firing Rates

The energetic costs of action potential (AP) production constrain the evolution of neural codes and brain networks. Cellular-level estimates of AP-related costs are typically based on voltage-dependent Na+ currents that drive active transport by the Na+/K+ ATPase to maintain the Na+ and K+ ion concentration gradients necessary for AP production. However, these estimates of AP cost have not been verified at the organismal level. Electric signaling in the weakly electric fish Eigenmannia virescens requires that specialized cells in an electric organ generate APs with large Na+ currents at high rates (200–600 Hz). We measured these currents using a voltage-clamp protocol and then estimated the energetic cost at the cellular level using standard methods. We then used this energy-intensive signaling behavior to measure changes in whole-animal energetics for small changes in electric discharge rate. At low rates, the whole-animal measure of AP cost was similar to our cellular-level estimates. However, AP cost increased nonlinearly with increasing firing rates. We show, with a biophysical model, that this nonlinearity can arise from the increasing cost of maintaining AP amplitude at high rates. Our results confirm that estimates of energetic costs based on Na+ influx are appropriate for low baseline firing rates, but that extrapolating to high firing rates may underestimate true costs in cases in which AP amplitude does not decrease. Moreover, the trade-off between energetic cost and firing rate suggests an additional constraint on the evolution of high-frequency signaling in neuronal systems.

[1]  Derrick J. Zwickl,et al.  Molecular evolution of communication signals in electric fish , 2008, Journal of Experimental Biology.

[2]  Walter Heiligenberg,et al.  Neural Nets in Electric Fish , 1991 .

[3]  T. Sejnowski,et al.  Metabolic cost as a unifying principle governing neuronal biophysics , 2010, Proceedings of the National Academy of Sciences.

[4]  P. Lennie The Cost of Cortical Computation , 2003, Current Biology.

[5]  S. Laughlin,et al.  Energy limitation as a selective pressure on the evolution of sensory systems , 2008, Journal of Experimental Biology.

[6]  Energy-Efficient Action Potentials in Hippocampal , 2009 .

[7]  Philip K. Stoddard,et al.  Circadian and Social Cues Regulate Ion Channel Trafficking , 2009, PLoS biology.

[8]  Jörg R. P. Geiger,et al.  Energy-Efficient Action Potentials in Hippocampal Mossy Fibers , 2009, Science.

[9]  John E. Lewis,et al.  The energetics of electric organ discharge generation in gymnotiform weakly electric fish , 2013, Journal of Experimental Biology.

[10]  Carl D. Hopkins,et al.  Electric Communication: Functions in the Social Behavior of Eigenmannia Virescens , 1974 .

[11]  D. Attwell,et al.  Updated Energy Budgets for Neural Computation in the Neocortex and Cerebellum , 2012, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[12]  L. Kaczmarek,et al.  A sodium-activated potassium channel supports high-frequency firing and reduces energetic costs during rapid modulations of action potential amplitude. , 2013, Journal of neurophysiology.

[13]  H. Zakon,et al.  Conductances contributing to the action potential of Sternopygus electrocytes , 1993, Journal of Comparative Physiology A.

[14]  Adam P. Hill,et al.  Warm Body Temperature Facilitates Energy Efficient Cortical Action Potentials , 2012, PLoS Comput. Biol..

[15]  S. Laughlin,et al.  An Energy Budget for Signaling in the Grey Matter of the Brain , 2001, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[16]  H. Scheich Neural basis of communication in the high frequency electric fish,Eigenmannia virescens (Jamming Avoidance Response) , 2004, Journal of comparative physiology.

[17]  Simon B. Laughlin,et al.  Action Potential Energy Efficiency Varies Among Neuron Types in Vertebrates and Invertebrates , 2010, PLoS Comput. Biol..

[18]  P. Stoddard,et al.  Sex differences in energetic costs explain sexual dimorphism in the circadian rhythm modulation of the electrocommunication signal of the gymnotiform fish Brachyhypopomus pinnicaudatus , 2008, Journal of Experimental Biology.

[19]  P. Moller Electric fishes : history and behavior , 1995 .

[20]  Rüdiger Krahe,et al.  Electrical signalling of dominance in a wild population of electric fish , 2011, Biology Letters.

[21]  S. Laughlin,et al.  Fly Photoreceptors Demonstrate Energy-Information Trade-Offs in Neural Coding , 2007, PLoS biology.

[22]  I. Schwartz,et al.  The fine structure of electrocytes in weakly electric teleosts , 1975, Journal of neurocytology.

[23]  G. Stuart,et al.  State and location dependence of action potential metabolic cost in cortical pyramidal neurons , 2012, Nature Neuroscience.

[24]  J. Steffensen Some errors in respirometry of aquatic breathers: How to avoid and correct for them , 2008, Fish Physiology and Biochemistry.