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Simultaneous brain-spinal cord functional MRI with a force-matching task

Poster No:

2347 

Submission Type:

Abstract Submission 

Authors:

Sandrine Bédard1,2, Valeria Oliva1, Christine Law1, Dario Pfyffer1, Merve Kaptan1, Brett Chy1, Susanna Aufrichtig1, Nazrawit Berhe1, John Ratliff3, Serena Hu4, Zachary Smith5, Andrew Smith6, Scott Delp7, Akshay Chaudhari8, Trevor Hastie9, Gary Glover8, Sean Mackey1, Kenneth Weber1

Institutions:

1Systems Neuroscience and Pain Lab, Division of Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, 2NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montréal, QC, Canada, 3Department of Neurosurgery, Stanford University School of Medicine, Stanford, Palo Alto, CA, 4Department of Orthopaedic Surgery, Stanford University School of Medicine, Stanford, Palo Alto, CA, 5Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 6Department of Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora, CO, 7Department of Bioengineering and Mechanical Engineering, Stanford University, Palo Alto, CA, 8Department of Radiology, Stanford University School of Medicine, Palo Alto, CA, 9Department of Statistics, Stanford University, Palo Alto, CA

First Author:

Sandrine Bédard  
Systems Neuroscience and Pain Lab, Division of Pain Medicine, Stanford University School of Medicine|NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal
Palo Alto, CA|Montréal, QC, Canada

Co-Author(s):

Valeria Oliva, PhD  
Systems Neuroscience and Pain Lab, Division of Pain Medicine, Stanford University School of Medicine
Palo Alto, CA
Christine Law, PhD  
Systems Neuroscience and Pain Lab, Division of Pain Medicine, Stanford University School of Medicine
Palo Alto, CA
Dario Pfyffer, PhD  
Systems Neuroscience and Pain Lab, Division of Pain Medicine, Stanford University School of Medicine
Palo Alto, CA
Merve Kaptan, PhD  
Systems Neuroscience and Pain Lab, Division of Pain Medicine, Stanford University School of Medicine
Palo Alto, CA
Brett Chy  
Systems Neuroscience and Pain Lab, Division of Pain Medicine, Stanford University School of Medicine
Palo Alto, CA
Susanna Aufrichtig  
Systems Neuroscience and Pain Lab, Division of Pain Medicine, Stanford University School of Medicine
Palo Alto, CA
Nazrawit Berhe  
Systems Neuroscience and Pain Lab, Division of Pain Medicine, Stanford University School of Medicine
Palo Alto, CA
John Ratliff  
Department of Neurosurgery, Stanford University School of Medicine, Stanford
Palo Alto, CA
Serena Hu  
Department of Orthopaedic Surgery, Stanford University School of Medicine, Stanford
Palo Alto, CA
Zachary Smith  
Department of Neurosurgery, University of Oklahoma Health Sciences Center
Oklahoma City, OK
Andrew Smith  
Department of Physical Medicine and Rehabilitation, University of Colorado School of Medicine
Aurora, CO
Scott Delp  
Department of Bioengineering and Mechanical Engineering, Stanford University
Palo Alto, CA
Akshay Chaudhari  
Department of Radiology, Stanford University School of Medicine
Palo Alto, CA
Trevor Hastie  
Department of Statistics, Stanford University
Palo Alto, CA
Gary Glover, PhD  
Department of Radiology, Stanford University School of Medicine
Palo Alto, CA
Sean Mackey, MD, PhD  
Systems Neuroscience and Pain Lab, Division of Pain Medicine, Stanford University School of Medicine
Palo Alto, CA
Kenneth Weber, DC, PhD  
Systems Neuroscience and Pain Lab, Division of Pain Medicine, Stanford University School of Medicine
Palo Alto, CA

Introduction:

Spinal conditions affect nearly one billion individuals worldwide and rank among the primary causes of pain and physical disability1. Spinal cord and nerve root injury are characterized by hand weakness and impaired coordination2. Functional MRI (fMRI) can map motor-related brain activity and potentially characterize mechanisms underlying hand weakness and diminished coordination. Although some studies have investigated motor control mechanisms in the brain3 research exploring these processes in the spinal cord has been limited4,5, primarily due to technical challenges. In this study, we use simultaneous brain-spinal cord fMRI to capture descending motor signals, their interactions in the spinal cord, and the motor output during a force-matching task in healthy volunteers.

Methods:

Eleven healthy volunteers (Age = 41 ± 14.8 years; 7 females, 4 males) were scanned using a 3T GE SIGNA Premier scanner with a 21-channel Head-Neck coil. We acquired simultaneous brain and spinal cord sequence6 (EPI pulse sequence, dynamic per slice shimming; TR = 2.6 s, TE = 30 ms, GRAPPA = 2), with 30 brain slices (3.43 x 3.43 x 5.00 mm3) and 15 cervical spinal cord slices (1.25 x 1.25 x 5.00 mm3) centered at the C5-C6 intervertebral disc. The imaging protocol also included axial (FOV = 22 cm, matrix size = 128 x 128, ΔTE=1ms) and sagittal (FOV = 30 cm, matrix size = 256 x 64, ΔTE =1 ms) field maps for shimming, and anatomical scans of the brain (T1w 3DFSPGR; 1.0 x 1.0 x 1.0 mm3) and spinal cord (T2w reduced-FOV 3D turbo spin-echo; 0.8 x 0.8 x 0.8 mm3).

The experimental design consisted of 30 sequences of 15 s blocks right-hand gripping using an MRI-compatible hand dynamometer with visual feedback with 15 s rest period between the task blocks. Participants matched three different force levels (10%, 20% and 30% of individual maximum voluntary contraction) during the experiment.

Brain and spinal cord analysis included physiological noise correction, white matter and cerebrospinal fluid principal component regression, motion correction, temporal filtering, spatial normalization to the MNI7 (brain) or PAM508 (spinal cord), and spatial smoothing using FSL9 and the Spinal Cord Toolbox10. Subject-level activation maps were generated using a general linear model including three regressors corresponding to the three force task levels and then entered in group level analyses.

Results:

In the brain, we identified activity in the contralateral motor and sensory cortices during the three different force levels. Additionally, BOLD signal change in the anterior cingulate cortex, the thalamus, cerebellum and occipital cortex linearly increased with force (Figure 1; mixed effects FLAME 1; Z > 2.3, cluster corrected p < 0.05).

In the spinal cord, we identified activity in the right ventral horn for each force level at the C7 spinal segment. However, no significant linear increase in BOLD signal was identified across the three force levels (Figure 2; fixed effects, uncorrected p < 0.05).
Supporting Image: ForceMatch_figure.png
Supporting Image: figure_forcepercent.png
 

Conclusions:

This study provides insights into the neural mechanisms of motor output in healthy volunteers with simultaneous brain and spinal cord fMRI and a force-matching task. The ipsilateral sensory and motor cortices show a linear increase in activity with higher force levels. In contrast, spinal cord activity, notably in the right ventral horn, did not demonstrate a similar linear relationship in this small sample. Studying motor control in the brain and spinal cord simultaneously has potential applications to spinal conditions such as spinal cord and nerve injury.

Modeling and Analysis Methods:

Activation (eg. BOLD task-fMRI)

Motor Behavior:

Motor Behavior Other 2

Novel Imaging Acquisition Methods:

BOLD fMRI 1

Keywords:

Cortex
FUNCTIONAL MRI
Motor
Open-Source Code
Spinal Cord
Sub-Cortical
Other - simultaneous brain and spinal cord fMRI;hand grip;force-matching task;motor control

1|2Indicates the priority used for review

Provide references using author date format

1. Abubakar, I. I., Tillmann, T. & Banerjee, A. Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 385, 117–171 (2015).
2. Badhiwala, J. H. et al. Degenerative cervical myelopathy — update and future directions. Nat. Rev. Neurol. 16, 108–124 (2020).
3. Cramer, S. C. et al. Motor cortex activation is related to force of squeezing. Hum. Brain Mapp. 16, 197–205 (2002).
4. Hemmerling, K. J., Hoggarth, M. A., Sandhu, M. S., Parrish, T. B. & Bright, M. G. Spatial distribution of hand-grasp motor task activity in spinal cord functional magnetic resonance imaging. Hum. Brain Mapp. (2023) doi:10.1002/hbm.26458.
5. Weber, K. A., 2nd, Chen, Y., Wang, X., Kahnt, T. & Parrish, T. B. Lateralization of cervical spinal cord activity during an isometric upper extremity motor task with functional magnetic resonance imaging. Neuroimage 125, 233–243 (2016).
6. Islam, H., Law, C. S. W., Weber, K. A., Mackey, S. C. & Glover, G. H. Dynamic per slice shimming for simultaneous brain and spinal cord fMRI. Magn. Reson. Med. 81, 825–838 (2019).
7. Fonov, V. S., Evans, A. C., McKinstry, R. C., Almli, C. R. & Collins, D. L. Unbiased nonlinear average age-appropriate brain templates from birth to adulthood. Neuroimage 47, S102 (2009).
8. De Leener, B. et al. PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space. Neuroimage 165, 170–179 (2018).
9. Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W. & Smith, S. M. FSL. Neuroimage 62, 782–790 (2012).
10. De Leener, B. et al. SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data. Neuroimage 145, 24–43 (2017).