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  • Publication
    Exploration of the Generation and Suppression of Pathological Oscillatory Neural Activity in a Model of Deep Brain Stimulation in Parkinsons disease
    This study explores possible mechanisms for the generation of pathological neural oscillatory activity associated with Parkinson’s disease in theoretical models. The suppression of the model oscillations with high frequency stimulation, analogous to the use of deep brain stimulation (DBS) in the treatment of Parkinson's disease, is also examined. The relationship between oscillation amplitude and the amplitude of the applied stimulation is explored theoretically and then compared with experimental data recorded in patients.
  • Publication
    Analysis of Oscillatory Neural Activity in Series Network Models of Parkinson’s Disease During Deep Brain Stimulation
    Parkinson’s disease is a progressive, neurodegenerative disorder, characterized by hallmark motor symptoms. It is associated with pathological, oscillatory neural activity in the basal ganglia. Deep brain stimulation (DBS) is often successfully used to treat medically refractive Parkinson’s disease. However, the selection of stimulation parameters is based on qualitative assessment of the patient, which can result in a lengthy tuning period and a suboptimal choice of parameters. This study explores fourth order, control theory-based models of oscillatory activity in the basal ganglia. Describing function analysis is applied to examine possible mechanisms for the generation of oscillations in interacting nuclei and to investigate the suppression of oscillations with high-frequency stimulation. The theoretical results for the suppression of the oscillatory activity obtained using both the fourth-order model, and a previously described second-order model, are optimized to t clinically recorded local field potential data obtained from Parkinsonian patients with implanted DBS. Close agreement between the power of oscillations recorded for a range of stimulation amplitudes is observed (R2 =0 .690.99). The results suggest that the behavior of the system and the suppression of pathological neural oscillations with DBS is well described by the macroscopic models presented. The results also demonstrate that in this instance, a second-order model is sufficient to model the clinical data, without the need for added complexity. Describing the system behaviour with computationally efficient models could aid in the identification of optimal stimulation parameters for patients in a clinical environment.
      265Scopus© Citations 17