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.
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