The insatiable appetite for energy to support human brain function is mainly supplied by glucose oxidation (CMR_glc(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 CMR_glc(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 CMR_glc(ox). Inhibitory neurons and glia need 15–20% of CMR_glc(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 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_glc(ox) maps and accurate cellular level interpretation of brain metabolic imaging.

A1 Functional advantages of cell-type heterogeneity in neural circuits

Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding.

Spontaneous activity within local circuits affects the integrative properties of neurons and networks. We have previously shown that neocortical network activity exhibits a balance between excitatory and inhibitory synaptic potentials, and such activity has significant effects on synaptic transmission, action potential generation, and spike timing. However, whether such activity facilitates or reduces sensory responses has yet to be clearly determined. We examined this hypothesis in the primary visual cortex in vivo during slow oscillations in ketamine-xylazine anesthetized cats. We measured network activity (Up states) with extracellular recording, while simultaneously recording postsynaptic potentials (PSPs) and action potentials in nearby cells. Stimulating the receptive field revealed that spiking responses of both simple and complex cells were significantly enhanced (>2-fold) during network activity, as were spiking responses to intracellular injection of varying amplitude artificial conductance stimuli. Visually evoked PSPs were not significantly different in amplitude during network activity or quiescence; instead, spontaneous depolarization caused by network activity brought these evoked PSPs closer to firing threshold. Further examination revealed that visual responsiveness was gradually enhanced by progressive membrane potential depolarization. These spontaneous depolarizations enhanced responsiveness to stimuli of varying contrasts, resulting in an upward (multiplicative) scaling of the contrast response function. Our results suggest that small increases in ongoing balanced network activity that result in depolarization may provide a rapid and generalized mechanism to control the responsiveness (gain) of cortical neurons, such as occurs during shifts in spatial attention.