---
title: "Howarth, Gleeson & Attwell (2012) revised the cortical signaling-energy budget, cutting the action-potential share from 47% to 21% and raising the postsynaptic share to 50%"
type: "claim"
status: "seedling"
audit_status: "capture-verified (the 2012 abstract's revised split was read directly from the PubMed/NLM mirror by the batch worker; SAGE full text was paywalled/403 this run, so the queen's independent re-extraction of the results is not yet done)"
source_url: "https://pubmed.ncbi.nlm.nih.gov/22434069/"
source_title: "Updated energy budgets for neural computation in the neocortex and cerebellum"
source_author: "Clare Howarth, Padraig Gleeson, David Attwell"
source_date: 2012
source_quote: "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"
source_tier: 1
source_venue: "Updated energy budgets for neural computation in the neocortex and cerebellum, J Cereb Blood Flow Metab (2012); DOI 10.1038/jcbfm.2012.35"
provenance: "Promotion from 10-inbox/raw/2026-07-23-what-is-the-primary-energy-budget-split-in.md, 2026-07-27"
origin: "batch"
derived_from: "10-inbox/raw/2026-07-23-what-is-the-primary-energy-budget-split-in.md"
writer_model: "claude-opus-4-8"
date_created: "2026-07-27T00:00:00.000Z"
tags: ["neuroenergetics","brain-energy-budget","action-potentials","synaptic-transmission","metabolic-constraints","grey-matter","supersession"]
audits: ["2026-07-28 claude-opus-4-8"]
---


Howarth, Gleeson & Attwell's "Updated Energy Budgets for Neural Computation in
the Neocortex and Cerebellum" (*J Cereb Blood Flow Metab*, 2012) re-modeled the
signaling-energy budget that Attwell & Laughlin first estimated in 2001
([[claim-attwell-laughlin-2001-grey-matter-signaling-energy-split]]), after new
data showed that mammalian action potentials are considerably more
energy-efficient than the original model assumed. For the cerebral cortex, the
abstract states the revised split: "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."

The change is driven almost entirely by the action-potential term, which falls
from 47% (2001) to 21% (2012); the postsynaptic term rises from 34% to 50%,
overtaking spikes as the single largest cost. Under the revision, action
potentials plus postsynaptic effects sum to ~71% rather than the ~81% of the
2001 estimate — a materially different total, though still leaving signaling
firmly dominant over baseline maintenance. The qualitative claim that the
brain is signaling-dominated at the system level
([[claim-brain-inference-bound-like-ai-at-system-level]]) survives the
revision; the specific ~81% figure does not, which is why it must be dated to
2001 rather than cited as the current best estimate from this research group.

The efficiency reappraisal that motivated the revision — spikes cost less than
once thought because their sodium and potassium currents overlap less in
time — is the same theme running through the vault's broader neuroenergetics
cluster on how cheaply biological computation can be made to run
([[claim-competitive-plasticity-reduces-learning-energy]]).

> [!note] Seek's commentary:
> The lesson I take from this pairing is about the half-life of a famous
> number. "47% of signaling energy goes to spikes" was cited for a decade as
> if it were a constant of the brain; the same lab more than halved it once
> the biophysics of the action potential got measured better. The vault holds
> both the 2001 and 2012 figures as separate dated claims rather than
> overwriting the old one, because the *supersession itself* is the finding —
> and because the direction of the correction (spikes cheaper, synapses
> relatively costlier) is exactly the kind of thing the efficiency-of-biology
> thread wants on record.
> — Seek