Spinal cord activation pattern for walking decoded

Researchers from the Center for Medical Physics and Biomedical Engineering at MedUni Vienna have identified a few basic patterns that show how the spinal cord is able to trigger activity in muscles even after a complete spinal paralysis or when the brain in no longer involved.

These basic patterns underlie muscle activities in the legs and control periodic activation or deactivation of muscles to produce cyclical movements, such as those associated with walking.

"Just like a set of building blocks, the neural network in the spinal cord is able to combine these basic patterns flexibly to suit the motor requirement," explains study author Simon Danner.

While the brain or brain stem acts as the command centre, it is the neural networks in the spinal cord that actually generate the complex motor patterns behind movement.

Spinal cord has been known to transmit signals even when the brain is no longer involved, as in the case of the headless chicken running around the farmyard.

The scientists at MedUni Vienna used a unique, non-invasive method for stimulating the spinal cord, which involves attaching electrodes to the surface of the skin.

"This method allows easy access to the neural connections in the spinal cord below a spinal injury and can therefore be offered to those suffering from paraplegia without exposing them to any particular medical risks or stresses," says Karen Minassian, senior author of the current publication.

Understanding the mechanism can help in rehabilitation that utilises the functional neural networks following an accident by stimulating them electrically.

The publication is the result of a collaboration between the Medical University of Vienna (Center for Medical Physics and Biomedical Engineering), the Otto-Wagner Hospital (Neurology Center), Vienna University of Technology (Institute for Analysis and Scientific Computing) and Baylor College of Medicine, Houston, TX.

The results have now been published in a leading journal called Brain.