Parkinson's disease is a neurological disorder characterized by the gradual degeneration of dopamine-producing cells in the brain. Although patients are treated with dopaminergic medication, this increases the risk of impulse control disorders, such as uncontrolled gambling, shopping, or eating. Using the unique and extensive dataset from the "Parkinson Op Maat" study at Radboudumc, the brain systems involved in these disorders were modeled. The analysis shows that the prefrontal cortex is more active in people with both Parkinson's disease and impulse control problems during medication use, and that this is linked to a higher expected value for rewards. Furthermore, by combining machine learning and generative modeling, it is possible to predict which patients are more likely to recover from impulse control disorders, based on brain activity related to reinforcement learning. These findings provide insights into the different responses patients have to dopaminergic medication, a crucial step in preventing medication-associated impulse control disorders in the future.
Jorryt Gerlof Tichelaar holds a Bachelor's and Master's in Molecular Life Sciences from Radboud University. He completed a PhD with Roshan Cools (Motivational & Cognitive Control) and Rick Helmich (department of Neurology), investigating the molecular, neural, and cognitive mechanisms of impulse control disorders in Parkinson’s disease. His research used computational psychiatry to assess individual differences in reinforcement learning. He now works at TenneT as data-analyst.