# Improving Human fMRI through Modeling and Imaging Microvascular Dynamics > **NIH NIH R01** · MASSACHUSETTS GENERAL HOSPITAL · 2020 · $930,025 ## Abstract PROJECT SUMMARY/ABSTRACT All fMRI signals have a vascular origin, and this has been believed to be a major limitation to precise spatiotemporal localization of neuronal activation when using hemodynamic functional contrast such as BOLD. However, significant recent discoveries made using powerful ultrahigh-resolution optical imaging techniques have challenged this belief. Unfortunately these measures require invasive procedures and therefore cannot be performed in humans. Our aim is to transfer knowledge gained from these invasive studies into interpreting human fMRI data in order to help fMRI reach its full potential. In this proposal we plan to combine detailed maps of human macro- and meso-scale vasculature measured with high-resolution MRI with maps of the micro-scale vasculature measured in human brain specimens with CLARITY-assisted microimaging. We will then link this anatomical information with dynamic models built from 2-photon microscopy performed in rodents where the changes in vessel diameter, blood flow and oxygenation can be measured directly in each vessel type across all stages of the vascular hierarchy. We hypothesize that newly introduced models of hemo- and vaso-dynamics built from 2-photon microscopy, linked with a detailed micro- and macroscopically mapped human microvascular anatomy, can be exploited to improve the spatial and temporal specificity of human fMRI. To supply human vasculature reconstructions to our models, we propose a two-scale approach. We first advance 7 Tesla MR Angiography (MRA) techniques to image the pial vascular network as well as intracortical vessels and vascular layers of the cerebral cortex to achieve a mesoscopic model. To form the micron-scale model of vasculature at the capillary level, we will use the CLARITY technique to image the full vascular tree (from arterioles through capillaries to venules) in human primary visual cortex. To predict vasodynamic changes driven by neuronal activation, we will adapt a model derived from dynamic in vivo 2-photon microscopy of vessel diameters in rodents to human microvascular anatomy. To adapt this to human microvasculature requires a careful multi-stage transferal. First we will measure bulk changes in microvessel diameter, a.k.a. cerebral blood volume (CBV), across multiple levels of the vascular hierarchy and confirm that the model can predict the CBV-fMRI signal. The CBV-fMRI signal is used because it is a vasodynamic signal directly reflecting vessel diameter changes occurring alongside local neuronal activity (rather than the subsequent hemodynamic changes). After performing this validation we will build a dynamic model of the microvascular tree in human cortex based on our vascular reconstruction, and again measure CBV-fMRI changes across multiple levels of the vascular hierarchy. We will finally test the ability of this model to improve the neuronal specificity of fMRI by imaging the functional architecture in human visual cortex. This model will a... ## Key facts - **NIH application ID:** 9974595 - **Project number:** 5R01MH111419-05 - **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL - **Principal Investigator:** Jonathan R Polimeni - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $930,025 - **Award type:** 5 - **Project period:** 2016-09-15 → 2023-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9974595 ## Citation > US National Institutes of Health, RePORTER application 9974595, Improving Human fMRI through Modeling and Imaging Microvascular Dynamics (5R01MH111419-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9974595. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*