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      Muscle synergy patterns as physiological markers of motor cortical damage.

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          Abstract

          The experimental findings herein reported are aimed at gaining a perspective on the complex neural events that follow lesions of the motor cortical areas. Cortical damage, whether by trauma or stroke, interferes with the flow of descending signals to the modular interneuronal structures of the spinal cord. These spinal modules subserve normal motor behaviors by activating groups of muscles as individual units (muscle synergies). Damage to the motor cortical areas disrupts the orchestration of the modules, resulting in abnormal movements. To gain insights into this complex process, we recorded myoelectric signals from multiple upper-limb muscles in subjects with cortical lesions. We used a factorization algorithm to identify the muscle synergies. Our factorization analysis revealed, in a quantitative way, three distinct patterns of muscle coordination-including preservation, merging, and fractionation of muscle synergies-that reflect the multiple neural responses that occur after cortical damage. These patterns varied as a function of both the severity of functional impairment and the temporal distance from stroke onset. We think these muscle-synergy patterns can be used as physiological markers of the status of any patient with stroke or trauma, thereby guiding the development of different rehabilitation approaches, as well as future physiological experiments for a further understanding of postinjury mechanisms of motor control and recovery.

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          Author and article information

          Journal
          Proc Natl Acad Sci U S A
          Proceedings of the National Academy of Sciences of the United States of America
          Proceedings of the National Academy of Sciences
          1091-6490
          0027-8424
          Sep 04 2012
          : 109
          : 36
          Affiliations
          [1 ] McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
          Article
          1212056109
          10.1073/pnas.1212056109
          3437897
          22908288
          978c036e-849e-43cd-9efa-7d413a3c62ea
          History

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