Grant: CIHR Fellowship
Direct Payment
$150,000.00
Informing high-resolution functional MRI through modeling microvascular dynamics
FY 2018-19
Summary
Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for measuring dynamic neuronal activity across the whole brain with no harmful effects, making it an invaluable tool for human neuroscience. FMRI measurements are based on tracking focal changes in blood flow and oxygenation that occur during brain activity to meet energetic demand. Because fMRI is, therefore, an indirect measure of neuronal activity, the confidence with which changes in neuronal activity can be inferred is limited. The hypothesis of this study is that a more complete picture of the blood vessels in the brain, and how they react to brain activity, will help us to better interpret the fMRI signals.
New evidence from microscopy studies in rodents indicates that the control of blood flow in response to neuronal activity is far more precise than previously believed, suggesting that fMRI has the potential to be a reliable marker of neuronal activity if measured and interpreted correctly. However, it is challenging to translate these findings to humans since the organization of rodent blood vessels is markedly different from ours. This project will create a 3D reconstruction of the blood vessel network-down to the smallest capillaries-from human brain specimens, from which a model of how the vessels react to neuronal firing to control blood delivery will be generated-and from this, how the fMRI signals change in response to brain activity. To ensure accuracy, the model will be validated against high-resolution human fMRI data acquired on an ultra-high magnetic field strength MRI scanner. This bottom-up approach will provide a crucial missing link between measured fMRI signals and the detailed underlying physiology, helping to better understand fMRI signals and improve our ability to accurately measure brain function.
Department
Program
CIHR Fellowship
Recipient
Location
Massachusetts, United States of America
Type
Grant
Source
CIHR Funding Decisions Database
As published
Id
397305
Name
Berman Avery J
Region
Massachusetts
Country
United States of America
Orgtype
Research Institution
Instname2
Neurosciences, Mental Health and Addiction
Theme2
Biomedical
Prcname2
Fellowships - Post-PhD
Projecttitle
Informing high-resolution functional MRI through modeling microvascular dynamics
Programtype2
Fellowship Programs
Orgnameinp2
Direct Payment
Cihramount2
$150,000
Cihrequipment2
$0
Programname2
CIHR Fellowship
Keyworddelim
Brain Vasculature; Cerebral Cortex; Functional Mri; Hemodynamics; Humans; Mice; Mri; Neuroimaging; Neurovascular Coupling; Simulation
Abstract
Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for measuring dynamic neuronal activity across the whole brain with no harmful effects, making it an invaluable tool for human neuroscience. FMRI measurements are based on tracking focal changes in blood flow and oxygenation that occur during brain activity to meet energetic demand. Because fMRI is, therefore, an indirect measure of neuronal activity, the confidence with which changes in neuronal activity can be inferred is limited. The hypothesis of this study is that a more complete picture of the blood vessels in the brain, and how they react to brain activity, will help us to better interpret the fMRI signals.
New evidence from microscopy studies in rodents indicates that the control of blood flow in response to neuronal activity is far more precise than previously believed, suggesting that fMRI has the potential to be a reliable marker of neuronal activity if measured and interpreted correctly. However, it is challenging to translate these findings to humans since the organization of rodent blood vessels is markedly different from ours. This project will create a 3D reconstruction of the blood vessel network-down to the smallest capillaries-from human brain specimens, from which a model of how the vessels react to neuronal firing to control blood delivery will be generated-and from this, how the fMRI signals change in response to brain activity. To ensure accuracy, the model will be validated against high-resolution human fMRI data acquired on an ultra-high magnetic field strength MRI scanner. This bottom-up approach will provide a crucial missing link between measured fMRI signals and the detailed underlying physiology, helping to better understand fMRI signals and improve our ability to accurately measure brain function.
Competitiondate
201811
Approvedterm2
3 yrs 0 mth
Pinamesdelim
Berman, Avery J
Approvedterm
3 ans 0 mois
Cihrcontribution2
~ $150,000~ $0~