bioRxivNeurosciencePreprint
Human brain cortical oxygen consumption is positively related to soma surface area density.
Manuela CarrieroiD, Alessandra Stella CaporaleiD, Davide Di CensoiD, Ian D. DriveriD, Elizabeth Jane FeariD, Hannah Louise ChandleriD, Fabrizio FasanoiD, Domenico ZacàiD, Emma BiondettiiD, Carolyn Beth McNabbiD, Michael A. GermuskaiD, Derek Kenton JonesiD, Marco PalomboiD, Richard G. WiseiD, Antonio Maria ChiarelliiD
Abstract
Evidence from in-silico, ex vivo and invasive animal studies suggested the function of neural tissue to be inextricably linked to its structural and microstructural organization. However, this link has never been assessed non-invasively in humans. Here, we established a simple quantitative framework linking cerebral oxygen metabolism to gray matter microstructural features in healthy humans using advanced non-invasive MRI methods. The cerebral metabolic rate of oxygen consumption (CMRO2) was quantified with calibrated fMRI, whereas microstructural properties were estimated from diffusion MRI data fitted to the Soma and Neurite Density Imaging (SANDI) model, yielding soma radius (R soma) and soma volume fraction (fsoma) metrics, from which we derived maps of soma surface area density (SAD) and soma numerical density (ND) under the assumption of a spherical soma. CMRO2 was positively associated with SAD (r = 0.29, p < 0.01), fsoma (r = 0.28, p < 0.05) and ND (r = 0.25, p < 0.05), and negatively associated with Rsoma (r = -0.23, p < 0.05) across cortical brain regions. These relationships are consistent with predictions from experimental and theoretical studies, providing the first quantitative evidence that cerebral metabolic demand is coupled to microstructure in humans. The positive association of energy consumption with SAD is consistent with the notion that both the number of synapses (energy-demanding structures), and the energy required to maintain a membrane potential, scale with soma surface area. Our findings establish a non-invasive MRI framework for investigating the microstructural determinants of brain energy metabolism in health and potentially in disease.
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