Biomedical Engineering - Theses

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    Tracking neural dynamics
    BALSON, RICHARD ( 2014)
    Epilepsy affects around 1% of the world's population, of which roughly a third are refractory to treatment. A major impediment to the development of effective treatments for these patients is the lack of understanding of the mechanisms underlying the disorder. In this thesis, a model-based approach is developed to provide some insight into these mechanisms. Initially, it is demonstrated that parameters linked to physiology from nonlinear models of the brain can be estimated accurately under various conditions. An animal model of epilepsy is used to illustrate that this computational model of the brain can be used to demonstrate variability in seizure mechanisms between animals, and over time. In particular, it is demonstrated that seizures group across days in the animal model, and that for each group, different physiological mechanisms are involved. This provides evidence that in the animal model studied seizures evolve, and that this evolution is linked to seizure grouping. With the knowledge that seizures are subject-specific and evolve over time, it may be possible to develop techniques that use control system theory to continuously alter therapy based on estimated physiological parameters inferred from recorded EEG, to provide treatments that are more efficacious. odel of epilepsy is used to illustrate that this computational model of the brain can be used to demonstrate variability in seizure mechanisms between animals, and over time. In particular, it is demonstrated that seizures group across days in the animal model, and that for each group, different physiological mechanisms are involved. This provides evidence that in the animal model studied seizures evolve, and that this evolution is linked to seizure grouping. With the knowledge that seizures are subject-specific and evolve over time, it may be possible to develop techniques that use control system theory to continuously alter therapy based on estimated physiological parameters inferred from recorded EEG, to provide treatments that are more efficacious.