Evidence map›Paper›PMID 22434069›Full record

ReviewJournal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism2012

Updated energy budgets for neural computation in the neocortex and cerebellum.

Clare Howarth, Padraig Gleeson, David Attwell

Open access · bronzeAbstract readReview
In one paragraph

Review in Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 383 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
383citing papers in PubMed, 2 pooled it
13.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

383 citing papers in PubMed, 2 syntheses or guidelines pooled it, 729 citations in OpenAlex.

  1. Pooled it
  2. CONature communications · 2022
    Pooled it
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Learning Shapes the Energy Cost of Neural Tasks.bioRxiv : the preprint server for biology · 2026
    Article
  10. Metabolism-weighted brain connectome reveals synaptic integration and vulnerability to neurodegeneration.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  11. Review
  12. Article
  13. Article
  14. Sex differences in brain glucose metabolism and Alzheimer's disease risk and progression.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Review
  15. Article
  16. Task-evoked deactivations: dissociation between BOLD fMRI and FDG.bioRxiv : the preprint server for biology · 2026
    Article
  17. Article
  18. Article
  19. Article
  20. Article

323 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Clare HowarthBrain Research Centre, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada. clare.howarth@oncology.ox.ac.uk
Padraig Gleeson
David Attwell
University College London · GBUniversity of British Columbia · CA

Funding

Wellcome TrustWellcome Trust 075232Wellcome Trust 086699
6 · The paper itself

Abstract

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.

Indexed as

Models, NeurologicalAction PotentialsAnimalsCerebellumEnergy MetabolismHumansNeocortex

Identifiers

PMID22434069
PMCPMC3390818
OpenAlexW2041158750

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.