The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Cerebral energetics and the glycogen shunt: Neurochemical basis of functional imaging
Open accessAbstract
Positron-emission tomography and functional MRS imaging signals can be analyzed to derive neurophysiological values of cerebral blood flow or volume and cerebral metabolic consumption rates of glucose (CMR Glc ) or oxygen (CMR O 2 ). Under basal physiological conditions in the adult mammalian brain, glucose oxidation is nearly complete so that the oxygen-to-glucose index (OGI), given by the ratio of CMR O 2 /CMR Glc , is close to the stoichiometric value of 6. However, a survey of functional imaging data suggests that the OGI is activity dependent, moving further below the oxidative value of 6 as activity is increased. Brain lactate concentrations also increase with stimulation. These results had led to the concept that brain activation is supported by anaerobic glucose metabolism, which was inconsistent with basal glucose oxidation. These differences are resolved here by a proposed model of glucose energetics, in which a fraction of glucose is cycled through the cerebral glycogen pool, a fraction that increases with degree of brain activation. The “glycogen shunt,” although energetically less efficient than glycolysis, is followed because of its ability to supply glial energy in milliseconds for rapid neurotransmitter clearance, as a consequence of which OGI is lowered and lactate is increased. The value of OGI observed is consistent with passive lactate efflux, driven by the observed lactate concentration, for the few experiments with complete data. Although the OGI changes during activation, the energies required per neurotransmitter release (neuronal) and clearance (glial) are constant over a wide range of brain activity.
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Pellerin, L., & Magistretti, P. J. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.22.10625 · Cited by 2,927
Fox, P. T., & Raichle, M. E. (1986) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.83.4.1140 · Cited by 2,056
Nonoxidative Glucose Consumption During Focal Physiologic Neural Activity
Fox, P. T., Raichle, M. E., Mintun, M. A., & Dence, C. (1988) · Science · doi:10.1126/science.3260686 · Cited by 1,796
Determination of the rate of the glutamate/glutamine cycle in the human brain by in vivo 13 C NMR
Shen, J., Petersen, K. F., Behar, K. L., Brown, P., Nixon, T. W., Mason, G. F., Petroff, O. A. C., Shulman, G. I., Shulman, R. G., & Rothman, D. L. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.14.8235 · Cited by 462
Self-citationBarbiturate-induced glycogen accumulation in brain. An electron microscopic study.
Phelps, C. H. (1972) · Brain Research · doi:10.1016/0006-8993(72)90797-4 · Cited by 154
Cited by
Searching for a baseline: Functional imaging and the resting human brain
Gusnard, D. A., & Raichle, M. E. (2001) · Nature Reviews Neuroscience · doi:10.1038/35094500 · Cited by 3,371
Raichle, M. E., & Mintun, M. A. (2006) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.112819 · Cited by 1,630
What does fMRI tell us about neuronal activity?
Heeger, D. J., & Ress, D. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn730 · Cited by 1,085
New Insights into Neuron-Glia Communication
Fields, R. D., & Stevens-Graham, B. (2002) · Science · doi:10.1126/science.298.5593.556 · Cited by 955
Brain Glucose Metabolism: Integration of Energetics with Function
Dienel, G. A. (2019) · Physiological Reviews · doi:10.1152/physrev.00062.2017 · Cited by 865
Metadata
- Authors
- Shulman, R. G., Hyder, F., & Rothman, D. L.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2001-05-08
- Volume
- 98
- Issue
- 11
- Pages
- 6417-6422
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2105077078
- Cited by
- 298
- References
- 5
- FWCI
- 15.99
- Type
- journal article
- Language
- en
- Open access
- green
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