Brain power

The human brain is just 2% of the body’s weight, but 20% of its metabolic load (1⇓–3), and 10 times more expensive per gram than muscle. On the other hand, the brain manages to produce poetry, design spacecraft, and create art on an energy budget of ∼20 W, a paltry sum given that the computer on which this article is being typed requires 80 W. So where in the brain is power consumed, what is it used for, why is it so expensive relative to other costs of living, and how does it achieve its power efficiency relative to engineered silicon? Many classic papers have studied these questions. Attwell and Laughlin (4) developed detailed biophysical estimates suggesting that neural signaling and the postsynaptic effects of neurotransmitter release combined to account for 80% of the brain’s adenosine triphosphate (ATP) consumption, conclusions that are also supported by the overall physiology and anatomy of neural circuits (5, 6). Numerous studies explored the structural and functional consequences of this expenditure for limiting brain size (7) and scaling (8), efficient wiring patterns (9), analog (graded potential) vs. digital (spiking) signaling (10), distributed neural codes (11⇓–13), the distribution of information traffic along nerve tracts and their size distribution (14⇓–16), and computational heterogeneity and efficiency (17). Many of these ideas have been synthesized by Sterling and Laughlin (18) into a set of principles governing the design of brains. Now, in PNAS, Levy and Calvert (19) propose a functional accounting of the power budget of the mammalian brain, suggesting that communication is vastly more expensive than computation, and exploring the functional consequences for neural circuit organization. Levy and Calvert (19) build on the earlier literature by focusing primarily on the relative power committed to different modes of information … [↵][1]1Email: vijay{at}physics.upenn.edu. [1]: #xref-corresp-1-1