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Quantifying control of brain energy supply by the neuron-glia-vasculature unit

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Brain energy supply and information flow

Unlike in other tissues, a complex flow of information between brain cells regulates blood supply. Elucidation of the mechanisms coupling brain energy supply to energy use is essential for understanding mechanisms of neuropsychiatric disorders.

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Alterations in neurometabolic function are detected in many neurological disorders such as depression, Alzheimer's disease and schizophrenia. The EU-funded 'Quantifying control of brain energy supply by the neuron-glia-vasculature unit' (BRAINENERGYCONTROL) project investigated the relationship between information flow in neuronal circuits and the trafficking of metabolites between neurons and glial cells. To achieve their objectives, scientists used a combination of mathematical modelling and in vitro imaging experiments. One important project discovery demonstrated that efficient transmission of information at a synapse in the presence of noise requires a low release probability at synapses. It is the optimal solution to maximise information transmitted per metabolic cost. This provides an explanation for the previously poorly understood fact that synapses are unreliable, often releasing neurotransmitters in only 25 % of the times that a presynaptic action potential arrives. Similarly, experiments in rat lateral geniculate nucleus relay cells showed that the amplitude of postsynaptic currents is set to maximise the ratio of information transmitted in relation to postsynaptic energy consumption. These results suggest the existence of homeostatic mechanisms that regulate both energy consumption and information transfer at synapses. The project’s results extend our understanding of brain energy use by examining adenosine triphosphate (ATP) consumption in non-signalling tasks in the brain which could consume up to 50 % of the brain's ATP. Researchers found that most of this non-signalling energy use is expended on turnover of the actin and microtubule cytoskeleton. In conclusion, BRAINENERGYCONTROL presented a model of metabolic interactions of the neuron-glia-vasculature ensemble. This model provides a template for large-scale simulations of this ensemble and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur.

Keywords

Brain energy supply, brain cells, neurometabolic function, neuron-glia-vasculature, synapses

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