Graduate Student Seminar Series
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Presentation Title: Computational Modelling of Deep Brain Stimulation
Abstract: Deep brain stimulation is a common treatment for Parkinson’s disease,however the mechanisms that make DBS treatment effective are not fully known. The firing rate of activity of regions in the basal ganglia during DBS can serve as an indicator of successful treatment of PD. How DBS reduces neuronal activity to a normal level in PD is not known, however computational models have provided some insight. Other markers have also been found that may be indicative of successful DBS treatment, such as the evoked resonant neural activity observed in response to DBS treatment in some locations of the subthalamic nucleus. Computational models have also done well to reveal the possible mechanism of action of ERNA. The accessibility of neural activity throughout the basal ganglia during DBS is limited. Biophysically realistic computational models allow exploration of hypotheses of DBS mechanisms and the PD state. Computational modelling is required to explore features of DBS impact and network dynamics that are sufficient for relevant clinical markers in humans. The aim of this research is to build on the mechanistic understanding of DBS, as well as the network impact DBS has and the importance of incorporating biophysical details such as morphology and synaptic distribution. The results of this research will be used to design optimal patterns of DBS pulses that maximize clinical outcomes.
Supervisor Name: Milad Lankarany
Year of Study: 3
Program of Study: PhD
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