Origins of a repetitive and co-contractive pattern of muscle activation in Parkinson’s disease

Cutsuridis, Vassilis (2011) Origins of a repetitive and co-contractive pattern of muscle activation in Parkinson’s disease. Neural Networks, 24 (6). pp. 592-601. ISSN 0893-6080


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In studies of electromyographic (EMG) patterns during movements in Parkinson’s disease, often a
repetitive and sometimes co-contractive pattern of antagonist muscle activation is observed. It has been
suggested that the origin of such patterns of muscle activation is a central one arising from impairments
in the basal ganglia structures and/or the cortex, although afferent inputs can also modulate the voluntary
activity. A neural network model of Parkinson’s disease, bradykinesia and rigidity, is extended to
quantitatively study the conditions under which such a repetitive and co-contractive pattern of muscle
activation appears. Computer simulations show that an oscillatory disrupted globus pallidus internal
segment (GPi) response signal comprising at least two excitation–inhibition sequences as an input to
a normally functioning cortico-spinal model of movement generation results in a repetitive, but not cocontractive
agonist–antagonist pattern of muscle activation. A repetitive and co-contractive pattern of
muscle activation results when also dopamine is depleted in the cortex. Finally, additional dopamine
depletion in the spinal cord sites results in a reduction of the size, duration and rate of change of the
repetitive and co-contractive EMG bursts. These results have important consequences in the development
of Parkinson’s Disease therapies such as dopamine replacement in cortex and spinal cord, which can
alleviate some of the impairments of Parkinson’s Disease such as slowness of movement (bradykinesia)
and rigidity.

Keywords:Parkinson’s disease, Triphasic pattern of muscle activation, Co-contraction, Dopamine, Globus pallidus, Cortex, Spinal cord
Subjects:B Subjects allied to Medicine > B140 Neuroscience
G Mathematical and Computer Sciences > G730 Neural Computing
Divisions:College of Science > School of Computer Science
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ID Code:27713
Deposited On:05 Jul 2017 09:17

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