Deep brain stimulation (DBS) of the subthalamic nucleus is a useful treatment for Parkinson's disease (PD), but its therapeutic mechanism is unknown. Effective DBS requires high frequency stimulation, well above the average firing rate of basal ganglia output neurons. Periodicity of DBS is also essential;random stimulation patterns at the same mean frequency are ineffective. Three mechanisms for its effect on basal ganglia output neurons have been proposed. DBS may correct a pathological change in: (1) firing rate of basal ganglia output cells and their targets in the thalamus, (2) bursting or oscillations of those cells, or (3) the degree to which the firing of the cells are correlated. Neither the rate nor the bursting model for the action of DBS adequately explains either the frequency or periodicity requirements. We have shown that a periodically-driven oscillator model of basal ganglia output cells exhibits a sequence of synchronizing entrainment and then failure of entrainment and desynchrony as the frequency of an excitatory stimulus is increased. In this model, the range of stimulus frequency, intensity and periodicity required for chaotic desynchronization matches that of the therapeutic effectiveness of DBS. This application will test our desynchronization hypothesis by measuring the degree of correlation among pairs of simultaneously recorded neurons in slices of the substantia nigra pars reticulata (SNR) during application of DBS-like natural and artificial synaptic conductances.
Aim 1 will test the fundamental mechanisms at work in the model using purely excitatory input.
Aim 2 will add an inhibitory component to the synaptic input, and test our method for designing the optimal stimulus.
Aim 3 will determine the influence of inhibitory coupling between output neurons on normal firing patterns and during DBS.
Aim 4 will determine whether the cellular dynamics or synaptic connections underlying DBS are altered after chronic dopamine depletion. Our model offers a mechanistic explanation of DBS and its properties, and a mathematical model that can be used to predict the effects of future DBS-like stimulation therapies. At this point, the model has not been validated, and this proposal will provide a test of the proposed mechanism. If it survives experimental test, our idea may be useful for explaining DBS and for designing future stimulation therapies.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
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Northwestern University at Chicago
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