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Abstract #3441

Modelling the macrovascular contribution to resting-state fMRI functional connectivity at 3 Tesla

Xiaole Zhong1,2, Jonathan R. Polimeni3,4,5, and J. Jean Chen1,2,6
1Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 2Rotman Research Institute at Baycrest, Toronto, ON, Canada, 3Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 4Department of Radiology, Harvard Medical School, Boston, MA, United States, 5Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States, 6Biomedical Engineering, University of Toronto, Toronto, ON, Canada

Synopsis

Keywords: fMRI Analysis, fMRI (resting state)

Motivation: There has been evidence that macrovasculature may bias the analysis of resting-state functional connectivity (FC) and that such a bias may be difficult to remove.

Goal(s): This study intends to demonstrate such an effect can be predicted with a biophysical model.

Approach: We used a biophysical model with experimentally acquired vascular maps to simulate macrovascular effects on functional connectivity estimates from BOLD fMRI.

Results: Our results show that it is feasible to model the macrovascular BOLD contribution to FC through simulation. While both arteries and veins contribute, our model is more accurately captures effects of veins.

Impact: This study aims to demonstrate the feasibility of simulating the BOLD signal in a voxel containing macrovasculature using a biophysical model, which will enable correction of the macrovascular bias in resting-state and other types of fMRI.

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Keywords