Abstract
Background: The regulation of muscle force is a vital aspect of sensorimotor control, requiring intricate neural processes. While neural activity associated with upper extremity force control has been documented, extrapolation to lower extremity force control is limited. Knowledge of how the brain regulates force control for knee extension and flexion may provide insights as to how pathology or intervention impacts central control of movement. Objectives: To develop and implement a neuroimaging-compatible force control paradigm for knee extension and flexion. Methods: A magnetic resonance imaging (MRI) safe load cell was used in a customized apparatus to quantify force (N) during neuroimaging (Philips Achieva 3T). Visual biofeedback and a target sinusoidal wave that fluctuated between 0 and 5 N was provided via an MRI-safe virtual reality display. Fifteen right leg dominant female participants (age = 20.3 ± 1.2 years, height = 1.6 ± 0.10 m, weight = 64.8 ± 6.4 kg) completed a knee extension and flexion force matching paradigm during neuroimaging. The force-matching error was calculated based on the difference between the visual target and actual performance. Brain activation patterns were calculated and associated with force-matching error and the difference between quadriceps and hamstring force-matching tasks were evaluated with a mixed-effects model (z > 3.1, p < 0.05, cluster corrected). Results: Knee extension and flexion force-matching tasks increased BOLD signal among cerebellar, sensorimotor, and visual-processing regions. Increased knee extension force-matching error was associated with greater right frontal cortex and left parietal cortex activity and reduced left lingual gyrus activity. Increased knee flexion force-matching error was associated with reduced left frontal and right parietal region activity. Knee flexion force control increased bilateral premotor, secondary somatosensory, and right anterior temporal activity relative to knee extension. The force-matching error was not statistically different between tasks. Conclusion: Lower extremity force control results in unique activation strategies depending on if engaging knee extension or flexion, with knee flexion requiring increased neural activity (BOLD signal) for the same level of force and no difference in relative error. These fMRI compatible force control paradigms allow precise behavioral quantification of motor performance concurrent with brain activity for lower extremity sensorimotor function and may serve as a method for future research to investigate how pathologies affect lower extremity neuromuscular function.