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Uncertainty quantification in a computationally optimised volume conductor model for deep brain stimulation  (  Dissertationsschrift  ) 
This thesis examines the influence of uncertainty in the parameters of a volume conductor model of the human brain on the voltage response and neural activation in the proximity of the stimulated brain area. The quantification of uncertainty in the human brain model was obtained by approximating the probabilistic voltage response and volume of tissue activated by a polynomial expansion, using the polynomial chaos technique. The required number of evaluations of the deterministic model was further reduced by the application of sparse grids with nested nodes.
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