Optimal Control of Nonlinear Networks Dynamics with Applications to Brain Stimulation in Alzheimer's Disease
Date
2017-12-20
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Abstract
Brain stimulation can modulate the activity of neural circuits impaired by Alzheimer’s disease (AD), having promising clinical benefit. However, all individuals with the same condition currently receive identical brain stimulation, with limited theoretical basis for this generic approach. In this study, we introduce a control theory framework for obtaining exogenous signals that revert pathological electroencephalographic activity in AD at a minimal energetic cost, while reflecting patients’ biological variability. By considering nonlinearities in our model, we identified regions for which control inputs fail to correct abnormal activity. We also found that limbic system and basal ganglia structures constitute the top target locations for stimulation in AD. Patients with highly integrated anatomical networks are the most suitable candidates for the propagation of stimuli and consequent success on the control task. Other diseases associated with alterations in brain dynamics and the self-control mechanisms of the brain can be addressed through our framework.
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Keywords
optimal control, network theory, Alzheimer's disease, brain stimulation, nonlinear dynamics
Citation
Sánchez Rodríguez, L. M. (2017). Optimal control of nonlinear networks dynamics with applications to brain stimulation in Alzheimer's disease (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.