Action Potential Energy Efficiency Varies Among Neuron Types in Vertebrates and Invertebrates

Abstract

The initiation and propagation of action potentials (APs) places high demands on the energetic resources of neural tissue. Each AP forces ATP-driven ion pumps to work harder to restore the ionic concentration gradients, thus consuming more energy. Here, we ask whether the ionic currents underlying the AP can be predicted theoretically from the principle of minimum energy consumption. A long-held supposition that APs are energetically wasteful, based on theoretical analysis of the squid giant axon AP, has recently been overturned by studies that measured the currents contributing to the AP in several mammalian neurons. In the single compartment models studied here, AP energy consumption varies greatly among vertebrate and invertebrate neurons, with several mammalian neuron models using close to the capacitive minimum of energy needed. Strikingly, energy consumption can increase by more than ten-fold simply by changing the overlap of the Na+ and K+ currents during the AP without changing the APs shape. As a consequence, the height and width of the AP are poor predictors of energy consumption. In the Hodgkin–Huxley model of the squid axon, optimizing the kinetics or number of Na+ and K+ channels can whittle down the number of ATP molecules needed for each AP by a factor of four. In contrast to the squid AP, the temporal profile of the currents underlying APs of some mammalian neurons are nearly perfectly matched to the optimized properties of ionic conductances so as to minimize the ATP cost.

Updated Energy Budgets for Neural Computation in the Neocortex and Cerebellum

“…This work updates our previous estimation of energy use associated with neural computation in the cerebral cortex (Attwell and Laughlin, 2001) and cerebellum (Howarth et al, 2010), incorporating recently published data demonstrating that action potentials are more energy efficient than previously assumed (Alle et al, 2009;Carter and Bean, 2009;Sengupta et al, 2010). Updating the models in this way supports most of the major conclusions of the original papers.…”

“…For the much smaller granule cells, which each receive a far smaller number of excitatory synaptic inputs (B4: Eccles et al, 1967), but have to maintain the resting potential of a very long (B4.5 mm) axon, most of the signaling energy ( Figure 3B) goes on the resting potential (71%, a significantly larger percentage than the previously calculated value of 55%: Howarth et al, 2010). Recent modeling studies have suggested that the temporal overlap between Na + and K + currents during a cerebellar granule cell action potential is negligible, resulting in an overlap factor of only 1.04, implying an extremely energy efficient action potential (Sengupta et al, 2010). As a result, granule cells are predicted to use only a small fraction of their energy on action potentials (10%; Figure 3B), much less than the previous prediction that 31% of granule cell signaling energy use is on action potentials (Howarth et al, 2010).…”

“…Here, we present an updated version of these calculations, incorporating recently published data (Alle et al, 2009;Carter and Bean, 2009;Sengupta et al, 2010) suggesting that action potentials are more energetically efficient than was previously assumed.…”

“…While these models provide interesting conclusions regarding the division of signaling energy use between the various processes occurring within a brain area or a specific cell type, recent work has suggested, both experimentally (Alle et al, 2009;Carter and Bean, 2009) and theoretically (Sengupta et al, 2010), that action potentials within mammalian neurons are more energetically efficient than previously thought. This is because the temporal overlap between Na + and K + currents during an action potential is much less than was estimated by Hodgkin (Alle et al, 2009;Carter and Bean, 2009), so that the factor by which the minimum charge entry (needed to polarize the membrane through the voltage of the action potential) must be multiplied to obtain the actual Na + entry ranges from as low as 1.04 (for cerebellar granule cells: Sengupta et al, 2010) to 2 (for Purkinje cells: Carter and Bean, 2009) compared with the value of 4 (Hodgkin, 1975), which has been commonly used. Previous models (Attwell and Laughlin, 2001;Nawroth et al, 2007;Howarth et al, 2010) have, therefore, overestimated the energy cost of action potentials in mammalian neurons.…”

Social complexity influences brain investment and neural operation costs in ants

“…The number of neurons in the MB and AL appear to be similar in our study species; O. smaragdina majors, however, have larger MB neurons (J. F. Kamhi, J. F. A. Traniello 2016, unpublished data). This appears counterintuitive, although neurons may be optimized to reduce ATP consumption [74] and thus COX activity, which is linked to neural activation [35] and not necessarily directly correlated with neuron size. Behavioural phenotype also may be related to brain metabolic activity [75].…”