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. 2021 May 1:355:109108.
doi: 10.1016/j.jneumeth.2021.109108. Epub 2021 Mar 8.

Integrated 3D motion analysis with functional magnetic resonance neuroimaging to identify neural correlates of lower extremity movement

Manish Anand  1 , Jed A Diekfuss  2 , Alexis B Slutsky-Ganesh  3 , Dustin R Grooms  4 , Scott Bonnette  5 , Kim D Barber Foss  6 , Christopher A DiCesare  5 , Jennifer L Hunnicutt  7 , Gregory D Myer  8
Affiliations

Integrated 3D motion analysis with functional magnetic resonance neuroimaging to identify neural correlates of lower extremity movement

Manish Anand et al. J Neurosci Methods. .

Abstract

Background: To better understand the neural drivers of aberrant motor control, methods are needed to identify whole brain neural correlates of isolated joints during multi-joint lower-extremity coordinated movements. This investigation aimed to identify the neural correlates of knee kinematics during a unilateral leg press task.

New method: The current study utilized an MRI-compatible motion capture system in conjunction with a lower extremity unilateral leg press task during fMRI. Knee joint kinematics and brain activity were collected concurrently and averaged range of motion were modeled as covariates to determine the neural substrates of knee out-of-plane (frontal) and in-plane (sagittal) range of motion.

Results: Increased out-of-plane (frontal) range of motion was associated with altered brain activity in regions important for attention, sensorimotor control, and sensorimotor integration (z >3.1, p < .05), but no such correlates were found with in-plane (sagittal) range of motion (z >3.1, p > .05). Comparison with Existing Method(s): Previous studies have either presented overall brain activation only, or utilized biomechanical data collected outside MRI in a standard biomechanics lab for identifying single-joint neural correlates.

Conclusions: The study shows promise for the MRI-compatible system to capture lower-extremity biomechanical data collected concurrently during fMRI, and the present data identified potentially unique neural drivers of aberrant biomechanics. Future research can adopt these methods for patient populations with CNS-related movement disorders to identify single-joint kinematic neural correlates that may adjunctively supplement brain-body therapeutic approaches.

Keywords: ACL; Knee biomechanics; Motion capture; Neural correlates; fMRI.

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Conflict of interest statement

Conflict of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Figure 1.
Figure 1.
A subject in the MRI with the MPT markers performing the unilateral leg press task.
Figure 2.
Figure 2.
(a) MPT camera with its axis overlay. (b) MPT compatible marker showing the Moiré pattern and axis overlay.
Fig. 3.
Fig. 3.
Knee sagittal and frontal plane angles of a representative subject during a movement block. Calculation of range of motion (ROM) for one cycle within the block is shown with the overlaid arrows.
Figure 4.
Figure 4.
Z-score map for overall brain activation during task performance. The cluster-wise threshold was set at Z > 3.1, p < .05.
Figure 5.
Figure 5.
Brain activation during the fMRI leg task (green) and neural correlates of Frontal Plane Range of Motion (positive = red, negative = blue) shown in the axial view with Z-coordinate slices. Small yellow clusters in the Precuneus (slice: −15) and Cerebellum I-IV (slice: 60) represent spatial areas of overlap between overall activation and positive correlates of Frontal Range of Motion. L = left, R = right.
See this image and copyright information in PMC

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