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MR-Encephalography
Introduction
Functional magnetic resonance imaging (fMRI) investigates the activity of brain structures during various tasks. When neurons perform an activity, there is a local increase in oxygen consumption and blood flow, resulting in local changes in deoxyhemoglobin concentration. This so-called BOLD (blood oxygenation level dependent) effect can then be detected with MRI because deoxyhemoglobin is paramagnetic.
A typical fMRI scan consists of continuously acquiring several brain images, and identifying brain areas that show significant changes in response to a given task, such as visual stimulation. With standard EPI (echo-planar imaging) acquisition methods, a whole-brain image is obtained approximately every 2 to 3 seconds.
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Due to the limited temporal resolution of EPI, it is only possible to track relatively slow changes in hemodynamic activity. Moreover, physiological artifacts such as breathing (~0.3 Hz) and heart pulsatility (~1 Hz) appear as aliased time courses, contaminating the BOLD signal. Our group is developing MR-Encephalography (MREG), which allows 3D whole-brain imaging at a temporal resolution of 100 ms, with only a slight loss in spatial resolution. This ultra-fast fMRI technique is based on multi-channel parallel acquisitions with fast k-space trajectories and iterative image reconstruction. The following results for a visual stimulation experiment show time courses with a much higher temporal resolution and un-aliased respiratory and cardiac noise. These physiological artifacts can then be easily filtered out (black trace).
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Applications
Real-time BOLD signal tracking
With the high temporal resolution of MREG, we can track BOLD changes in real time, such as in the following retinotopy experiment, where a subject is scanned while being presented with a rotating checkerboard wedge on a computer screen. During a single rotation of the wedge lasting 30 seconds, we can clearly see the BOLD response travelling through the brain regions corresponding to the various parts of the visual field.
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Project Members
