Altered EEG alpha and theta oscillations characterize apathy in Parkinson's disease during incentivized movement
Bibliographic record
Abstract
Apathy is a common non-motor symptom of Parkinson's disease (PD) that is difficult to quantify and poorly understood. Some studies have used incentivized motor tasks to assess apathy, as the condition is often associated with a reduction in motivated behavior. Normally event-related desynchronization, a reduction of power in specific frequency bands, is observed in the motor cortex during the peri-movement period. Also, alpha (8-12 Hz) and theta (4-7 Hz) oscillations are sensitive to rewards that are closely related to motivational states however these oscillations have not been widely investigated in relation to apathy in PD. Using EEG recordings, we investigated the neural oscillatory characteristics of apathy in PD during an incentivized motor task with interleaved rest periods. Apathetic and non-apathetic PD subjects on dopaminergic medication and healthy control subjects were instructed to squeeze a hand grip device for a monetary reward proportional to the subject's grip force and the monetary value attributed to that trial. Apathetic PD subjects exhibited higher alpha and theta powers in the pre-trial baseline rest period compared to non-apathetic PD subjects and healthy subjects. Further, we found that both resting power and relative power in alpha and theta bands during incentivized movement predicted PD subjects' apathy scores. Our results suggest that apathetic PD patients may need to overcome greater baseline alpha and theta oscillatory activity in order to facilitate incentivized movement. Clinically, resting alpha and theta power as well as alpha and theta event-related desynchronization during movement may serve as potential neural markers for apathy severity in PD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".