Functional MRI (fMRI) is widely used for mapping spatial and temporal patterns of brain activity, but a major concern is the inability to quantitatively relate the blood oxygen level dependent (BOLD) fMRI signal to the underlying physiological changes. The BOLD signal results from changes in local deoxyhemoglobin content, and so depends not only on the relative changes in cerebral blood flow and oxygen metabolism, but also on the baseline metabolic state. The complexity of this signal leads to a fundamental problem in interpreting the magnitude of the BOLD response: e.g. what does it mean if the magnitude of the BOLD response in the lateral prefrontal cortex to a working memory task is altered after exercise, which is known to change both blood flow and oxygen consumption in the brain? Because of this complexity, BOLD fMRI has had limited clinical applications to date, primarily confined to mapping where neural activation occurs. While the complex sensitivity of the BOLD signal to blood flow and oxygen metabolism creates difficulty in interpretation, it also offers the possibility of calculating changes in metabolism from combined BOLD-CBF measurements. This quantitative fMRI approach offers the potential to broaden fMRI from a mapping tool into a true probe of brain function in health and disease. Exercise has been shown to be beneficial to physical health, mental health and in prevention of disease, but how exercise affects brain physiology is poorly understood. The general approach in our group is to use a novel quantitative fMRI approach (dual-echo arterial spin labeling) for simultaneous measurement of blood flow and BOLD responses, and analyze the data within a mathematical framework for how the BOLD effect depends on the underlying physiological changes, specifically oxygen metabolism. In the first specific aim, we will use this approach to examine the effects of two levels of exercise (maximal exertion and 20 minutes at 60% of VO2 max) on blood flow and oxygen metabolism. In our second aim, we will investigate whether these levels of exercise alter the responses of blood flow and oxygen metabolism to a working memory task, complex motor task and a standard visual stimulus. These studies are of interest not only as they will expand applications of quantitative fMRI but will also provide more insight into neurophysiological impact of exercise. The long-term goal is the development of tools and methods for assessing the mental effects of exercise more broadly (e.g., for treatment of depression or slowing cognitive decline). Additionally, these studies will further our understanding of how the BOLD signal measured with fMRI is related to underlying physiological changes. In this work I will receive extensive training in state of the art fMRI methods for assessing brain function, current ideas and methods of exercise physiology, and experience with integrating these components for the study of exercise effects on brain function.

Public Health Relevance

Functional MRI has had wide-ranging impact on modern brain science, however wider application to the study of mental health has been hindered by the inability to precisely quantify the underlying physiological changes. Oxygen metabolic rate may provide a much more accurate reflection of neural activity than changes in the standard fMRI signal alone since aerobic metabolism of glucose is the primary metabolic fuel for energy production in the human brain. Here, we develop techniques to non-invasively measure oxygen metabolic rate while examining the neurophysiological effects of exercise, which is of particular interest as a possible moderator of depression and for slowing cognitive decline.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Individual Predoctoral NRSA for M.D./Ph.D. Fellowships (ADAMHA) (F30)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-F01-F (20))
Program Officer
Rosemond, Erica K
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of California San Diego
Schools of Medicine
La Jolla
United States
Zip Code