Rinsic activity and metabolismPursuing an understanding of the brain’s intrinsic activities needs not stop with the neurophysiology. Understanding the underlying cell biology is also relevant in understanding not only brain imaging signals but also what these signals are actually telling us about brain function (for those interested in an expanded view of this argument, see [5,54,103]). Functional brain imaging studies actually provide some clues as to how this inquiry might proceed. I begin from the perspective of the fMRI BOLD signal, whose cell biology helps introduce a somewhat more sophisticated view of the role of the metabolism of intrinsic activity, one that goes beyond a consideration of metabolism solely in terms of energy generation. One of the surprising observations made with PET was that blood flow increases much more than oxygen consumption during task-induced increases in brain activity [104,105]. The practical significance of this observation paved the way for fMRI [32]. However, overlooked by many in discussions of BOLD RP5264 custom synthesis signal biology have been the task-induced increases in aerobic glycolysis (i.e. glucose metabolized by the brain in excess of that needed for oxidative phosphorylation despite the presence of adequate oxygen; figure 3) that accompany changes in blood flow. These unexpected task-induced increases in aerobic glycolysis actually reflect an increase rather than a de novo appearance of aerobic glycolysis. Indeed, aerobic glycolysis is present in the normal adult human brain at rest, accounting for 12?5 of the glucose metabolized [109,110]. Hence it constitutes an important component of intrinsic activity metabolism [106]. Furthermore, aerobic glycolysis is not distributed uniformly (figure 3a). Rather, it exhibits elevated levels in the DMN and adjacent areas of the dorsolateral prefrontal cortex and low levels in the cerebellum and the medial temporal lobes [106]. Taking advantage of the non-uniform distribution of aerobic glycolysis, we compared the regional variance in the resting state fMRI BOLD signal (figure 1b) with the regional levels of aerobic glycolysis in the human brain (figure 3a) and found them to be highly correlated. Thus, aerobic glycolysis at `rest’5. Relating systems to cellsAt the cellular level, spontaneous activity is often discussed in terms of variations in neuronal excitability (e.g. [72,75,82,83]) mediated by spontaneous variations in membrane voltage known as up and down states (UDS). The question is whether a similar mechanism underlies the spontaneous fluctuations in the fMRI BOLD signal that gives us resting state maps of functional connectivity (figure 1). On the basis of this information, we originally thought it reasonable to ask whether spontaneous fluctuations in the fMRI BOLD signal were, in fact, related to UDS (see Supplementary Note 3 in [100]). We concluded at the time that it was unlikely to be the case for two reasons. First, the Sch66336 supplement frequency content of the BOLD signal demonstrates a power spectrum that exhibits power law scaling (for a review, see [101]), whereas UDS have a narrow frequency range that centres around 0.8 Hz. And, second, UDS and their associated LFPs travel across the cortex with latencies of a second or less (figure 2b, [84]), whereas fMRI BOLD resting state networks appear spatially stationary. Recent advances in our analysis of spontaneous fluctuations in the fMRI BOLD signal [85], however, suggest a rethinking of that view. We find that the restin.Rinsic activity and metabolismPursuing an understanding of the brain’s intrinsic activities needs not stop with the neurophysiology. Understanding the underlying cell biology is also relevant in understanding not only brain imaging signals but also what these signals are actually telling us about brain function (for those interested in an expanded view of this argument, see [5,54,103]). Functional brain imaging studies actually provide some clues as to how this inquiry might proceed. I begin from the perspective of the fMRI BOLD signal, whose cell biology helps introduce a somewhat more sophisticated view of the role of the metabolism of intrinsic activity, one that goes beyond a consideration of metabolism solely in terms of energy generation. One of the surprising observations made with PET was that blood flow increases much more than oxygen consumption during task-induced increases in brain activity [104,105]. The practical significance of this observation paved the way for fMRI [32]. However, overlooked by many in discussions of BOLD signal biology have been the task-induced increases in aerobic glycolysis (i.e. glucose metabolized by the brain in excess of that needed for oxidative phosphorylation despite the presence of adequate oxygen; figure 3) that accompany changes in blood flow. These unexpected task-induced increases in aerobic glycolysis actually reflect an increase rather than a de novo appearance of aerobic glycolysis. Indeed, aerobic glycolysis is present in the normal adult human brain at rest, accounting for 12?5 of the glucose metabolized [109,110]. Hence it constitutes an important component of intrinsic activity metabolism [106]. Furthermore, aerobic glycolysis is not distributed uniformly (figure 3a). Rather, it exhibits elevated levels in the DMN and adjacent areas of the dorsolateral prefrontal cortex and low levels in the cerebellum and the medial temporal lobes [106]. Taking advantage of the non-uniform distribution of aerobic glycolysis, we compared the regional variance in the resting state fMRI BOLD signal (figure 1b) with the regional levels of aerobic glycolysis in the human brain (figure 3a) and found them to be highly correlated. Thus, aerobic glycolysis at `rest’5. Relating systems to cellsAt the cellular level, spontaneous activity is often discussed in terms of variations in neuronal excitability (e.g. [72,75,82,83]) mediated by spontaneous variations in membrane voltage known as up and down states (UDS). The question is whether a similar mechanism underlies the spontaneous fluctuations in the fMRI BOLD signal that gives us resting state maps of functional connectivity (figure 1). On the basis of this information, we originally thought it reasonable to ask whether spontaneous fluctuations in the fMRI BOLD signal were, in fact, related to UDS (see Supplementary Note 3 in [100]). We concluded at the time that it was unlikely to be the case for two reasons. First, the frequency content of the BOLD signal demonstrates a power spectrum that exhibits power law scaling (for a review, see [101]), whereas UDS have a narrow frequency range that centres around 0.8 Hz. And, second, UDS and their associated LFPs travel across the cortex with latencies of a second or less (figure 2b, [84]), whereas fMRI BOLD resting state networks appear spatially stationary. Recent advances in our analysis of spontaneous fluctuations in the fMRI BOLD signal [85], however, suggest a rethinking of that view. We find that the restin.
