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Eur J Neurosci. 2012 Jul;36(2):2213-28. doi: 10.1111/j.1460-9568.2012.08108.x.

Basal ganglia activity patterns in parkinsonism and computational modeling of their downstream effects.

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Department of Mathematics and Center for the Neural Basis of Cognition, University of Pittsburgh, 301 Thackeray Hall, Pittsburgh, PA 15260, USA.


The availability of suitable animal models and the opportunity to record electrophysiologic data in movement disorder patients undergoing neurosurgical procedures has allowed researchers to investigate parkinsonism-related changes in neuronal firing patterns in the basal ganglia and associated areas of the thalamus and cortex. These studies have shown that parkinsonism is associated with increased activity in the basal ganglia output nuclei, along with increases in burst discharges, oscillatory firing and synchronous firing patterns throughout the basal ganglia. Computational approaches have the potential to play an important role in the interpretation of these data. Such efforts can provide a formalized view of neuronal interactions in the network of connections between the basal ganglia, thalamus, and cortex, allow for the exploration of possible contributions of particular network components to parkinsonism, and potentially result in new conceptual frameworks and hypotheses that can be subjected to biological testing. It has proven very difficult, however, to integrate the wealth of the experimental findings into coherent models of the disease. In this review, we provide an overview of the abnormalities in neuronal activity that have been associated with parkinsonism. Subsequently, we discuss some particular efforts to model the pathophysiologic mechanisms that may link abnormal basal ganglia activity to the cardinal parkinsonian motor signs and may help to explain the mechanisms underlying the therapeutic efficacy of deep brain stimulation for Parkinson's disease. We emphasize the logical structure of these computational studies, making clear the assumptions from which they proceed and the consequences and predictions that follow from these assumptions.

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