Brain metabolism during task-evoked and spontaneous activity in aging and Alzheimer's disease

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PROJECT ABSTRACT This proposal aims to collect data using PET and MRI in humans to measure metabolic correlates of task-evoked neural activity. Our approach is unique in simultaneously measuring the metabolic rates of oxygen (CMRO2) and glucose (CMRGlc), thereby permitting the calculation of aerobic glycolysis (AG), which reflects the rate of excess glycolysis beyond that required for oxidative metabolism. Prior work has shown that the BOLD signal, driven by a change in cerebral blood flow (CBF) that exceeds changes in CMRO2, decreases in particular “task-negative” regions of the brain during task-performance, making up the now so-called default mode network (DMN). It is, however, presently unknown whether AG also decreases or increases in these same regions during a task. Moreover, since Alzheimer’s disease (AD) pathology specifically affects the DMN, it is possible that task-evoked changes in AG are also affected by AD. Here we will collect task-evoked metabolic and BOLD fMRI data in both young and older adults, including adults with and without pathologic evidence of AD. Our primary approach is to determine how task-evoked glycolysis relates to the BOLD fMRI signal deactivations and activations, and to determine whether aging or AD affect these relationships. In Aim 1, we will determine the metabolic correlates of BOLD deactivations during task performance in young adults. We will perform FDG-PET to quantitate regional CMRGlc, as well as MRI measurements of CBF and CMRO2, thus permitting calculation of AG. We will make these measurements alongside BOLD fMRI during rest and during two different tasks. We will then determine whether AG increases or decreases in the default mode network. In Aim 2, we will determine whether task- evoked changes in brain metabolism differ among young adults, older adults, and older adults with AD. We will perform the same studies as in Aim 1, but in older healthy adults (i.e., cognitively unimpaired, amyloid-biomarker negative, without other evidence of neurological disease) and in asymptomatic older adults with pathologic evidence of AD (i.e., amyloid-biomarker positive). We will also choose one of the tasks to further perform in a group of adults with mild AD dementia. From these data, we will determine how healthy aging and AD influence task-evoked brain activity and metabolism. We expect these data to be highly informative, including in the interpretation of numerous other ongoing studies utilizing functional neuroimaging to study how aging and AD influence brain physiology.