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Cortical or Subcortical Neural Networks During Dynamic Neuromuscular Core Stabilization: A fMRI Blood Oxygen-Level Dependent (BOLD) Analysis

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Background: While core stabilization techniques, abdominal drawing-in maneuver (ADIM) and dynamic neuromuscular stabilization (DNS) have recently been recognized as a powerful technique to mitigate or improve various medical conditions, the issue of whether the cortical or subcortical neural network contributes to dynamic neuromuscular core stabilization (yoga-like DNS breathing vs. ADIM) remains unknown. Objectives: To investigate the neural substrates mediating subconscious, implicit and conscious, explicit core stabilization exercises including abdominal drawing-in maneuver (ADIM) and dynamic neuromuscular stabilization (DNS) in individuals with core instability using fMRI. Design: Single case study. Settings: A major university hospital. Participant: A non-symptomatic participant with core instability. Intervention: All participants underwent conscious ADIM, conscious ADIM with hip flexion and extension (ADIM-HFE), subconscious HFE, and subconscious DNS-based HFE core stabilization exercise training. Outcome Measures: A 3T fMRI was used to determine cortical or subcortical activation during a series of implicit or explicit core stabilization tasks at an uncorrected p < 0.001. Results: During conscious ADIM, the contralateral primary motor area was activated. However, during subconscious DNS-based HFE, the subcortical thalamus and basal ganglia (BG) were activated along with the contralateral primary motor area. Conclusion: This is the first clinical evidence highlighting dissociated roles in cortical and subcortical neuromotor control mechanisms underpinning implicit and explicit core stabilization exercises.
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Document Type: Research Article

Publication date: 01 November 2016

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  • Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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