Evaluating the gray and white matter energy budgets of human brain function

Abstract

The insatiable appetite for energy to support human brain function is mainly supplied by glucose oxidation (CMR). 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 CMR-derived budget and confirmed it with experimental results measured by PET, autoradiography, C-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 CMR. Inhibitory neurons and glia need 15-20% of CMR, with the rest demanded by excitatory neurons. Nonsignaling demands dominate in white matter, in near opposite contrast to gray matter demands. Comparison between C-MRS data and calculations suggests ∼1.2 Hz glutamatergic signaling rate in the awake human cortex, which is ∼4 times lower than signaling in the rat cortex. Top-down validated bottom-up budgets could allow computation of anatomy-based CMR maps and accurate cellular level interpretation of brain metabolic imaging.

Neurons rely on glucose rather than astrocytic lactate during stimulation

“…Additionally, brain metabolism can differ dramatically among circuits, cell‐types, and even individual cells according to their moment‐to‐moment energy demand. For instance, upon stimulation and firing of action potentials, neuronal metabolic burden increases several fold, mainly due to energy demands associated to synaptic transmission (Yu, Herman, Rothman, Agarwal, & Hyder, ).…”

“…For example, positron emission tomography studies in humans have shown increases of ~50% in blood flow and glucose consumption, but only of ~5% in O 2 consumption (Fox et al, 1988); calibrated functional magnetic resonance imaging estimates a similar value for the increase in both blood flow and glucose metabolism (~45%), but a slightly larger ~16% increase in O 2 consumption (Davis, Kwong, Weisskoff, & Rosen, 1998). 2 When glycolysis runs faster than oxidative metabolism, the excess pyruvate and NADH production is managed by the temporary 1 Neurons firing at 1 Hz (a modest rate) in the gray matter of the human brain are calculated to increase their metabolic burden by ~2.7-fold, in order to support processes like restoring the ionic gradients across the cell membrane, neurotransmitter release, vesicle recycling and Ca 2+ management (Yu, Herman, Rothman, Agarwal, & Hyder, 2018). 2 Other studies in the smaller brains of rats (Hyder et al, 1997) found little discrepancy between glucose and oxygen consumption with stimulation.…”

Comparative Primate Connectomics

“…Their costs however include the energy needed to build the connections during development, the energy needed to maintain their proper functioning, and the space they require. While gray matter consumes more energy than white matter [Yu et al, 2017], the metabolic demands of white matter are still significant. In gray matter, most energy is used for synaptic activity, whereas in white matter, most energy is used to operate the sodium and potassium pumps that maintain electrochemical gradients across the axon membrane [Yu et al, 2017].…”

“…While gray matter consumes more energy than white matter [Yu et al, 2017], the metabolic demands of white matter are still significant. In gray matter, most energy is used for synaptic activity, whereas in white matter, most energy is used to operate the sodium and potassium pumps that maintain electrochemical gradients across the axon membrane [Yu et al, 2017]. These costs may place limits on the number of neuronal connections that the organism can metabolically support.…”

Cable Energy Function of Cortical Axons: Equivalent Formulas

“…Accurate estimation of the metabolic cost of action potential generation and propagation is important for the calculation of energy budgets for individual neurons as well as for the whole brain (Hofman, 1983;Attwell and Laughlin, 2001;Lennie, 2003;Henry, 2005;Alle et al, 2009;Carter and Bean, 2009;Herman et al, 2009;Hasenstaub et al, 2010;Sengupta et al, 2010;Belanger et al, 2011;Harris and Attwell, 2012;Howarth et al, 2012;Yu et al, 2012;Hyder et al, 2013b;Moujahid et al, 2014;Sanganahalli et al, 2016). These estimates reveal computational rules such as optimal trade-offs between metabolic constraints and neural coding (Laughlin, 2001;Laughlin and Sejnowski, 2003;Lennie, 2003;Moujahid et al, 2011;Sengupta et al, 2013) and improve the interpretation of functional magnetic resonance imaging data (Logothetis, 2008;Hyder et al, 2013a;Hyder et al, 2013b;Shulman et al, 2014;Magistretti and Allaman, 2015;Yu et al, 2017).…”