The objective of this project is to test the joint hypotheses that sampling the functional MRI (fMRI) signals up to an order of magnitude more rapidly can help extract information related to neuronal signaling; and that the hemodynamic signals that form the basis of fMRI, rather than being sluggish as is commonly believed, respond rapidly and precisely to neuronal activity. Rapid sampling is commonly advocated to enable physiological noise removal-because these systemic noise sources can then be adequately sampled and so are not aliased in the raw fMRI signal-however our goal is to demonstrate that the fMRI signal at short time scales also contains fluctuations that are directly driven by neuronal activation. While the blood-oxygen-level-dependent (BOLD) response is well known to peak 6 s following the onset of neuronal activity, the initial vascular response begins in less tha 1 s. Here we challenge the notion that the BOLD response is slow. We will capitalize on our recent development of Simultaneous Multi-Slice (SMS) imaging for fMRI, which provides temporal sampling that is 12 faster than that of conventional techniques. With the SMS method, the fMRI measurement possesses the temporal resolution to detect brain activation over the entire brain with sub-second precision. Previous work has demonstrated that fMRI time series data acquired with high sampling rates can be used to parcellate global brain networks into smaller nodes, and therefore increase detection power in resting- state functional connectivity studies. Here we propose to extend this key benefit to other common fMRI experimental paradigms. Our preliminary data suggests that, by acquiring fMRI data on a finer time scale using a conventional task-driven block-design paradigm, dramatic increases in detection sensitivity up to factors of 2-3 are achievable. In these cases, faster sampling yields increased sensitivity. This boost will enable new classes of experiments, as well as single-subject analyses and potentially individualized diagnosis. Recent invasive animal neurovascular coupling studies and human fMRI studies have shown that the early stages of the BOLD response are precisely controlled by local vascular responses, and the BOLD response spreads spatially with time. High spatio-temporal resolution fMRI acquisitions can therefore enable higher accuracy by sampling the early phases of the BOLD response. In these cases, faster sampling yields increased specificity. Finally, we will test whether rapid fMRI can help (i) extrac information from continuous, temporally- encoded stimulus designs and (ii) resolve neuronal activations occurring closely in time. For the latter, we will implement a novel calibration procedure designed to remove regional variations in vascular delay from the measured delays in the BOLD response to accurately estimate the neuronal activation onset. Here, faster sampling yields additional information about neuronal function and activation latencies of the brain.
Our aim i s to demonstrate the benefits of rapid fMRI in these domains and to develop acquisition and analysis frameworks for the inevitable widespread use of this transformative new approach to fMRI.

Public Health Relevance

Functional MRI is the most widely used method for imaging the human brain, and this technique is based on measuring increases in oxygenated blood flow to regions of the brain that are active. It is widely believed that the control of blood flow in th brain is imprecise, and that fresh, oxygenated blood only arrives at active brain areas many seconds after increases in neuronal activity, however recent measurements have determined that the blood is routed in a highly controlled way immediately following neuronal activity. This project aims to use new technological advances that speed up functional MRI considerably, and with this we will test the hypothesis that blood flow is regulated in a precise manner and therefore functional MRI reflects electrical brain activity much better than is commonly believed.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB019437-04
Application #
9428443
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Liu, Guoying
Project Start
2015-04-01
Project End
2019-02-28
Budget Start
2018-03-01
Budget End
2019-02-28
Support Year
4
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
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