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Evaluating the gray and white matter energy budgets of human brainfunction

机译:评估人脑的灰色和白色物质能量收支功能

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摘要

The insatiable appetite for energy to support human brain function is mainly supplied by glucose oxidation (CMRglc(ox)). But how much energy is consumed for signaling and nonsignaling processes in gray/white matter is highly debated. We examined this issue by combining metabolic measurements of gray/white matter and a theoretical calculation of bottom-up energy budget using biophysical properties of neuronal/glial cells in conjunction with species-exclusive electrophysiological and morphological data. We calculated a CMRglc(ox)-derived budget and confirmed it with experimental results measured by PET, autoradiography, 13C-MRS, and electrophysiology. Several conserved principles were observed regarding the energy costs for brain’s signaling and nonsignaling components in both human and rat. The awake resting cortical signaling processes and mass-dependent nonsignaling processes, respectively, demand ∼70% and ∼30% of CMRglc(ox). Inhibitory neurons and glia need 15–20% of CMRglc(ox), with the rest demanded by excitatory neurons. Nonsignaling demands dominate in white matter, in near opposite contrast to gray matter demands. Comparison between 13C-MRS data and calculationssuggests ∼1.2 Hz glutamatergic signaling rate in the awake human cortex, whichis ∼4 times lower than signaling in the rat cortex. Top-down validated bottom-upbudgets could allow computation of anatomy-based CMRglc(ox) maps andaccurate cellular level interpretation of brain metabolic imaging.
机译:维持人脑功能所需的能量无法满足的需求主要来自葡萄糖氧化(CMRglc(ox))。但是,在灰色/白色物质中进行信号传递和非信号传递过程消耗了多少能量一直存在争议。我们通过结合使用神经元/神经胶质细胞的生物物理特性以及物种专有的电生理学和形态学数据,结合了对灰/白质的代谢测量值和自下而上的能量收支的理论计算,从而研究了这个问题。我们计算了CMRglc(ox)衍生的预算,并用PET,放射自显影, 13 C-MRS和电生理学测量的实验结果证实了这一点。关于人和大鼠的大脑信号和非信号成分的能量消耗,人们观察到了一些保守的原则。清醒的静息皮质信号传导过程和质量相关的非信号传导过程分别需要CMRglc(ox)的〜70%和〜30%。抑制性神经元和神经胶质细胞需要CMRglc(ox)的15–20%,其余的则是兴奋性神经元。非信号需求在白质中占主导地位,与灰质需求几乎相反。 13 C-MRS数据和计算之间的比较提示清醒的人类皮层中约1.2 Hz的谷氨酸能信号传导速率,比大鼠皮质的信号传导低约4倍。自顶向下验证的自底向上预算可以允许计算基于解剖的CMRglc(ox)图,并且脑代谢成像的准确细胞水平解释。

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