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.

中文翻译：

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脑力 [神经科学]

人脑仅占体重的 2%，却占其代谢负荷的 20% ( 1 ⇓ – 3 )，每克的成本是肌肉的 10 倍。另一方面，大脑设法在大约 20 W 的能量预算下创作诗歌、设计航天器和创作艺术，考虑到用于输入这篇文章的计算机需要 80 W 的能量，这个数字微不足道。耗电是什么，它的用途是什么，为什么它相对于其他生活成本如此昂贵，以及它如何实现相对于工程硅的能效？许多经典论文都研究过这些问题。阿特维尔和劳克林（4) 进行了详细的生物物理学估计，表明神经信号传导和神经递质释放的突触后效应结合起来占大脑三磷酸腺苷 (ATP) 消耗的 80%，这些结论也得到神经回路的整体生理学和解剖学的支持 ( 5 , 6）。许多研究探讨了这种支出在限制大脑大小 ( 7 ) 和缩放 ( 8 )、有效布线模式 ( 9 )、模拟（分级电位）与数字（尖峰）信号（10）、分布式神经代码方面的结构和功能后果( 11 ⇓ – 13)，沿神经束的信息流量分布及其大小分布 ( 14 ⇓ – 16 )，以及计算异质性和效率 ( 17 )。Sterling 和 Laughlin ( 18 ) 将这些想法中的许多合成为一组控制大脑设计的原则。现在，在 PNAS 中，Levy 和 Calvert ( 19 ) 提出了哺乳动物大脑功率预算的功能解释，表明通信比计算昂贵得多，并探索了神经回路组织的功能后果。