An Energy Budget for the Olfactory Glomerulus

Nawroth, Janna; Greer, Charles A.; Chen, Wei R.; Laughlin, Simon B.; Shepherd, Gordon M.

doi:10.1523/jneurosci.1415-07.2007

Cited by 68 publications

(72 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nevertheless, many energy budgets incorporate the assumption that the energy consumption of mammalian action potentials is equivalent to that of the squid giant axon action potential [e.g. 9, [37][38][39]. Following the discovery that mammalian action potentials consume far less energy, these energy budgets had to be revised because they overemphasized the action potential energy consumption [28,40].…”

Section: Re-evaluation Of Energy Budgetsmentioning

confidence: 99%

Neuronal energy consumption: biophysics, efficiency and evolution

Niven

2016

Current Opinion in Neurobiology

122

View full text Add to dashboard Cite

Electrical and chemical signaling within and between neurons consumes energy. Recent studies have sought to refine our understanding of the processes that consume energy and their relationship to information processing by coupling experiments with computational models and energy budgets. These studies have produced insights into both how neurons and neural circuits function, and why they evolved to function in the way they do. Introduction Neurons consume energy. Appreciating that they do so is essential for understanding and interpreting the function and evolution of neurons, neural circuits and, ultimately, whole brains. Yet we must go beyond mere appreciation by relating specific molecular components and processes to the energy they consume and the work they contribute to processing information and generating behavior. This permits determination of both 'how' and 'why' processes consume energy, and an understanding of the key trade-offs that have influenced neural evolution (reviewed in [1,2]). Although neuronal energy consumption has been studied for over 80 years [3,4], conceptual and methodological breakthroughs [5][6][7][8][9] have prompted renewed interest in the causes and consequences of neuronal energy consumption over the last ~20 years. Here I review this recent progress in our understanding of how the physiology and anatomy of neurons and neural circuits reflect fundamental relationships between energy consumption, biophysics and performance. Addresses

show abstract

Section: Re-evaluation Of Energy Budgetsmentioning

confidence: 99%

Neuronal energy consumption: biophysics, efficiency and evolution

Niven

2016

Current Opinion in Neurobiology

122

View full text Add to dashboard Cite

show abstract

“…Recently, three energy budgets have been produced that attempt to divide the total energy consumption of neural tissue into its constituent components (Attwell and Laughlin, 2001 2003; Nawroth et al, 2007). For example, Attwell and Laughlin (Attwell and Laughlin, 2001) divide the energy consumption of a single action potential in rat grey matter into the voltage-gated currents producing the action potential, pre-synaptic Ca 2+ entry at the synapse, the recycling of glutamate released into the synaptic cleft and loading of vesicles, vesicle endo-and exocytosis and the activation of post-synaptic receptors (NMDA, non-NMDA and mGluR) (Fig.…”

Section: The Energetic Cost Of Neural Tissuementioning

confidence: 99%

“…Several studies have now shown that there are high energetic costs incurred by neural tissue, including that of sensory systems, both whilst processing information and at rest (Ames et al, 1992;Attwell and Laughlin, 2001;Lennie, 2003;Niven et al, 2003a;Nawroth et al, 2007;Niven et al, 2007). There are also likely to be considerable energetic costs associated with the development and carriage of nervous systems.…”

Section: Introductionmentioning

confidence: 99%

Energy limitation as a selective pressure on the evolution of sensory systems

Niven

Laughlin

2008

Journal of Experimental Biology

929

779

View full text Add to dashboard Cite

SummaryEvolution of animal morphology, physiology and behaviour is shaped by the selective pressures to which they are subject. Some selective pressures act to increase the benefits accrued whilst others act to reduce the costs incurred, affecting the cost/benefit ratio. Selective pressures therefore produce a trade-off between costs and benefits that ultimately influences the fitness of the whole organism. The nervous system has a unique position as the interface between morphology, physiology and behaviour; the final output of the nervous system is the behaviour of the animal, which is a product of both its morphology and physiology. The nervous system is under selective pressure to generate adaptive behaviour, but at the same time is subject to costs related to the amount of energy that it consumes. Characterising this trade-off between costs and benefits is essential to understanding the evolution of nervous systems, including our own. Within the nervous system, sensory systems are the most amenable to analysing costs and benefits, not only because their function can be more readily defined than that of many central brain regions and their benefits quantified in terms of their performance, but also because recent studies of sensory systems have begun to directly assess their energetic costs. Our review focuses on the visual system in particular, although the principles we discuss are equally applicable throughout the nervous system. Examples are taken from a wide range of sensory modalities in both vertebrates and invertebrates. We aim to place the studies we review into an evolutionary framework. We combine experimentally determined measures of energy consumption from whole retinas of rabbits and flies with intracellular measurements of energy consumption from single fly photoreceptors and recently constructed energy budgets for neural processing in rats to assess the contributions of various components to neuronal energy consumption. Taken together, these studies emphasize the high costs of maintaining neurons at rest and whilst signalling. A substantial proportion of neuronal energy consumption is related to the movements of ions across the neuronal cell membrane through ion channels, though other processes such as vesicle loading and transmitter recycling also consume energy. Many of the energetic costs within neurons are linked to 3Na + /2K + ATPase activity, which consumes energy to pump Na + and K + ions across the cell membrane and is essential for the maintenance of the resting potential and its restoration following signalling. Furthermore, recent studies in fly photoreceptors show that energetic costs can be related, via basic biophysical relationships, to their function. These findings emphasize that neurons are subject to a law of diminishing returns that severely penalizes excess functional capacity with increased energetic costs. The high energetic costs associated with neural tissue favour energy efficient coding and wiring schemes, which have been found in numerous sensory systems. We discus...

show abstract

“…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.…”

Section: Introductionmentioning

confidence: 97%

Updated Energy Budgets for Neural Computation in the Neocortex and Cerebellum

Howarth

Gleeson²,

Attwell³

2012

J Cereb Blood Flow Metab

613

586

View full text Add to dashboard Cite

The brain's energy supply determines its information processing power, and generates functional imaging signals. The energy use on the different subcellular processes underlying neural information processing has been estimated previously for the grey matter of the cerebral and cerebellar cortex. However, these estimates need reevaluating following recent work demonstrating that action potentials in mammalian neurons are much more energy efficient than was previously thought. Using this new knowledge, this paper provides revised estimates for the energy expenditure on neural computation in a simple model for the cerebral cortex and a detailed model of the cerebellar cortex. In cerebral cortex, most signaling energy (50%) is used on postsynaptic glutamate receptors, 21% is used on action potentials, 20% on resting potentials, 5% on presynaptic transmitter release, and 4% on transmitter recycling. In the cerebellar cortex, excitatory neurons use 75% and inhibitory neurons 25% of the signaling energy, and most energy is used on information processing by non-principal neurons: Purkinje cells use only 15% of the signaling energy. The majority of cerebellar signaling energy use is on the maintenance of resting potentials (54%) and postsynaptic receptors (22%), while action potentials account for only 17% of the signaling energy use.

show abstract

An Energy Budget for the Olfactory Glomerulus

Cited by 68 publications

References 63 publications

Neuronal energy consumption: biophysics, efficiency and evolution

Neuronal energy consumption: biophysics, efficiency and evolution

Energy limitation as a selective pressure on the evolution of sensory systems

Updated Energy Budgets for Neural Computation in the Neocortex and Cerebellum

Contact Info

Product

Resources

About