Attwell · Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism 2001 · theoretical / computational energy budget modeling · n=?

An energy budget for signaling in the grey matter of the brain.

Cited 3584 times in the scientific literature.

Level 5 - mechanism / opinion, no new human data

Mechanism-based computational modeling and energy budget analysis using published physiological data (Level 5 by CEBM / design analogy).

PubMed 11598490 · doi:10.1097/00004647-200110000-00001 · record verified 2026-08-30

What was done

Anatomical and physiological data were used to analyze energy expenditure across components of excitatory signaling in rodent grey matter, modeling the costs of action potentials, postsynaptic glutamate effects, resting potentials, and glutamate recycling.

What was found

Action potentials and postsynaptic effects of glutamate were predicted to consume 47% and 34% of signaling energy, respectively, while resting potential consumed 13% and glutamate recycling used 3%. An increase in activity of 1 action potential per cortical neuron per second was estimated to raise oxygen consumption by 145 mL/100 g grey matter per hour. The model predicts distributed coding with <=15% of neurons simultaneously active to minimize energy consumption, and indicates that functional magnetic resonance imaging signals are likely dominated by synaptic currents and action potential propagation.

Why it matters

This provides a quantitative framework connecting neural metabolic demands to sparse coding principles and the biophysical interpretation of functional neuroimaging signals.

Limits

The estimates are based on computational synthesis of existing anatomical and physiological data rather than new direct empirical measurements. The model is specific to rodent excitatory grey matter signaling and does not provide empirical sample sizes or direct human data.

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