GRAHAM LAB

GRAHAM LAB

Head Motion in fMRI and Anatomical MRI

Our laboratory focuses on addressing the challenge of head motion in both functional MRI (fMRI) and anatomical MRI, which can introduce \"artifact\" signals that can potentially degrade data quality and complicate the interpretation of brain activity. This issue is particularly relevant in patient populations, where motion artifacts are more common.
Screenshot_20221223_091420
Left: baseline condition where subject attempts to lie as still as possible. Middle: subject nods their head slightly to create motion through the plane of image acquisition. Right: subject undergoes through-plane motion during fMRI where the images are adaptively compensated for motion effects during the data acquisition process.
Images of the voxel-wise temporal standard deviation of resting-state fMRI time series data for a representative subject (Faraji-Dana et al., 2016).

Motion Suppression Strategies

Robust strategies are required to suppress this problem so that clinical and research applications of fMRI can be made practical. To mitigate motion artifacts and improve data accuracy, we have explored several key approaches:
  • Characterization of Head Motion: Careful study of head motion during motor tasks, particularly in stroke patients, and the development of behavioural tasks designed to reduce head movement during fMRI. Development of fMRI
  • Simulators: The creation of realistic fMRI mock-up systems that c can be used to optimize experimental designs or train individuals to remain still prior to scanning. Optical Position
  • Tracking Systems: Use of high-resolution tracking systems to measure head motion in real-time. We have designed and constructed several such MRI-compatible tracking systems that can adaptively move the scan plane based on tracking data, significantly reducing motion artifacts and enhancing image quality.

Featured Work

These research posters, created by our graduate student, Marina Silic, provide an in-depth look at various aspects of the ongoing research. Each poster highlights key findings and methodologies, offering a comprehensive overview of the work being done in the lab.

Explore the captions for further details.

  • Slide1 (1)
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Recent Publications

Test Platform for Developing New Optical Position Tracking Technology towards Improved Head Motion Correction in Magnetic Resonance Imaging
Silic, M., Tam, F., & Graham, S. J. (2024).

Sensors, 24(12), 3737. https://doi.org/10.3390/s24123737 ‌

Resting State fMRI: Going Through the Motions
Maknojia, S., Churchill, N. W., Schweizer, T. A., & Graham, S. J. (2019).

Frontiers in Neuroscience, 13, 462471. https://doi.org/10.3389/fnins.2019.00825 ‌

Visualization of Brain Shift Corrected Functional Magnetic Resonance Imaging Data for Intraoperative Brain Mapping
Maknojia, S., Tam, F., Das, S., Schweizer, T., & Graham, S. J. (2019).

World Neurosurgery: X, 2, 100021. https://doi.org/10.1016/j.wnsx.2019.100021 ‌

Simultaneous Multislice Resting-State Functional Magnetic Resonance Imaging at 3 Tesla: Slice-Acceleration-Related Biases in Physiological Effects
Golestani A. M., Faraji-Dana, Z., Kayvanrad, M., Setsompop, K., Graham, S. J., & Chen, J. J. (2018).

Brain Connectivity, 8(2). https://doi.org/10.1089/brain.2017.0491 ‌

A robust method for suppressing motion-induced coil sensitivity variations during prospective correction of head motion in fMRI
Faraji-Dana, Z., Tam, F., Chen, J. J., & Graham, S. J. (2016).

Magnetic Resonance Imaging, 34(8), 1206–1219. https://doi.org/10.1016/j.mri.2016.06.005 ‌

Interactions between head motion and coil sensitivity in accelerated fMRI
Faraji-Dana, Z., Tam, F., Chen, J. J., & Graham, S. J. (2016).

Journal of Neuroscience Methods, 270, 46–60. https://doi.org/10.1016/j.jneumeth.2016.06.005

Suppressing Respiration Effects when Geometric Distortion Is Corrected Dynamically by Phase Labeling for Additional Coordinate Encoding (PLACE) during Functional MRI
Faraji-Dana, Z., Tam, F., Chen, J. J, & Graham, S. J. (2016).

PLoS ONE, 11(6), e0156750–e0156750. https://doi.org/10.1371/journal.pone.0156750 ‌

Real-time correction by optical tracking with integrated geometric distortion correction for reducing motion artifacts in functional MRI
Rotenberg, D. J., Chiew, M., Ranieri, S., Tam, F., Chopra, R., & Graham, S. J. (2012).

Magnetic Resonance in Medicine, 69(3), 734–748. https://doi.org/10.1002/mrm.24309 ‌

Spin-history artifact during functional MRI: Potential for adaptive correction
Yancey, S. E., Rotenberg, D. J., Tam, F., Chiew, M., Ranieri, S., Biswas, L., Anderson, S. Nicole Baker, Wright, G. A., & Graham, S. J. (2011).

Medical Physics, 38(8), 4634–4646. https://doi.org/10.1118/1.3583814 ‌

Retrospective coregistration of functional magnetic resonance imaging data using external monitoring
Tremblay, M., Tam, F., & Graham, S. J. (2004).

Magnetic Resonance in Medicine, 53(1), 141–149. https://doi.org/10.1002/mrm.20319 ‌

Quantifying Head Motion Associated with Motor Tasks Used in fMRI
Seto, E., Sela, G., McIlroy, W. E., Black, S. E., Staines, W. R., Bronskill, M. J., McIntosh, A. R., & Graham, S. J. (2001).

NeuroImage, 14(2), 284–297. https://doi.org/10.1006/nimg.2001.0829 ‌