ETD

• multiscale
• neuroscience
• Parkinson's disease
• simulation

This thesis presents a multiscale computational model of Parkinson’s disease that links cellular dopaminergic mechanisms to large-scale brain dynamics. A custom cortical neural mass model was integrated with a spiking network of the basal ganglia to simulate how dopamine depletion alters neural excitability and synaptic transmission. The framework enables simulations spanning from single-neuron membrane potentials to EEG signals, reproducing spectral and spatial features observed in healthy and Parkinsonian conditions. The model captures hallmark beta-band hyperactivity under dopamine loss and reveals altered cortico-basal ganglia connectivity consistent with experimental data. Overall, this work demonstrates the power of multiscale modeling to connect microscopic mechanisms with macroscale EEG dynamics, offering new insights into the emergence and propagation of pathological oscillations in Parkinson’s disease.