Cellular mechanisms of brain energy metabolism and their relevance to functional brain imaging

Abstract

Despite striking advances in functional brain imaging, the cellular and molecular mechanisms that underlie the signals detected by these techniques are still largely unknown. The basic physiological principle of functional imaging is represented by the tight coupling existing between neuronal activity and the associated local increase in both blood £ow and energy metabolism. Positron emission tomography (PET) signals detect blood £ow, oxygen consumption and glucose use associated with neuronal activity; the degree of blood oxygenation is currently thought to contribute to the signal detected with functional magnetic resonance imaging, while magnetic resonance spectroscopy (MRS) identi¢es the spatio-temporal pattern of the activity-dependent appearance of certain metabolic intermediates such as glucose or lactate. Recent studies, including those of neurotransmitter-regulated metabolic £uxes in puri¢ed preparations and analyses of the cellular localization of enzymes and transporters involved in energy metabolism, as well as in vivo microdialysis and MRS approaches have identi¢ed the neurotransmitter glutamate and astrocytes, a speci¢c type of glial cell, as pivotal elements in the coupling of synaptic activity with energy metabolism. Astrocytes are ideally positioned to sense increases in synaptic activity and to couple them with energy metabolism. Indeed they possess specialized processes that cover the surface of intraparenchymal capillaries, suggesting that astrocytes may be a likely site of prevalent glucose uptake. Other astrocyte processes are wrapped around synaptic contacts which possess receptors and reuptake sites for neurotransmitters. Glutamate stimulates glucose uptake into astrocytes. This e¡ect is mediated by speci¢c glutamate transporters present on these cells. The activity of these transporters, which is tightly coupled to the synaptic release of glutamate and operates the clearance of glutamate from the extracellular space, is driven by the electrochemical gradient of Na + . This Na + -dependent uptake of glutamate into astrocytes triggers a cascade of molecular events involving the Na + /K + -ATPase leading to the glycolytic processing of glucose and the release of lactate by astrocytes. The stoichiometry of this process is such that for one glutamate molecule taken up with three Na + ions, one glucose molecule enters an astrocyte, two ATP molecules are produced through aerobic glycolysis and two lactate molecules are released. Within the astrocyte, one ATP molecule fuels one`turn of the pump' while the other provides the energy needed to convert glutamate to glutamine by glutamine synthase. Evidence has been accumulated from structural as well as functional studies indicating that, under aerobic conditions, lactate may be the preferred energy substrate of activated neurons. Indeed, in the presence of oxygen, lactate is converted to pyruvate, which can be processed through the tricarboxylic acid cycle and the associated oxidative phosphorylation, to yield 17 ATP molecules per lactate molecule....

Aquaporin 9 in rat brain after severe traumatic brain injury

“…Magistretti et al 12 assumed a "lactate shuttle" model, where glucose was transformed by the astrocytes into lactate and diffused from astrocytes to neurons using the monocarboxylate transporters (MCTs). Tsukaguchi et al 13 found that AQP9 permeability to lactate increased four-fold when the pH decreased to 5.5.…”

Functional connectivity in fMRI: A modeling approach for estimation and for relating to local circuits

“…This view is still generally held to be true (Magistretti & Pellerin, 1999;Logothetis et al, 2001). The issue of how to translate baseline and scaling effects in fMRI is still poorly understood.…”

“…Furthermore, methods such as structural equation modeling (SEM (McIntosh & Gonzalez-Lima, 1992;McIntosh & Gonzalez-Lima, 1994) and dynamic causal modeling (DCM; do not take synaptic inhibition and energetic consequences of modulatory neurotransmitter effects into account. For example, how synaptic inhibition affects local blood flow (fMRI signal) is not well understood (Jueptner & Weiller, 1995;Magistretti & Pellerin, 1999;Logothetis et al, 2001;Caesar et al, 2003). Because of this, a positive connection weight can not necessarily be interpreted as an excitatory underlying connection.…”

A 4D approach to the analysis of functional brain images: Application to FMRI data

“…The water protons in the vessels and surrounding tissue are affected by these changes in the magnetic field and this is detected as changes in the signal intensity of T* 2 -weighted MR images [Ogawa et al, 1990[Ogawa et al, , 1992[Ogawa et al, , 1998]. However, the mechanism behind the coupling between neuronal activity and changes in HbR content is still a matter of debate [see, e.g., Jueptner and Weiller, 1995;Magistretti and Pellerin, 1999;and Villringer, 1999, for a general discussion on this topic, Buxton and Frank, 1997;Hyder et al, 1998, for biophysical models of the relationship between blood flow and HbR, Buxton et al, 1998;Hoge et al, 1999a, for models of the coupling between blood flow and BOLD signal, Woolsey et al, 1996;Malonek and Grinvald, 1996;Malonek et al, 1997;Yang et al, 1997;Vanzetta and Grinvald, 1999;Silva et al, 1999, andSilva et al, 2000, for detailed empirical characterization of this coupling].…”