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EEG: Reinforcement Learning in Parkinson's
This dataset comprises electroencephalography (EEG) recordings from 28 Parkinson's disease patients and 28 matched healthy controls performing a reinforcement learning task with volitional and instructed choice conditions. Parkinson's patients were tested twice within one week under both ON and OFF medication states, while controls participated in a single session. The study investigates neural correlates of reinforcement learning and decision-making in Parkinson's disease, with concurrent accelerometer recordings from the most tremor-affected hand.
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Coming soon. Per-file data-quality summaries are precomputed by the NEMAR processing pipeline. The static aggregate is on the way — tracked at nemar-cli#511.