Apathy in Patients with Parkinson's Disease Correlates with Alteration of Left Fronto-Polar Electroencephalographic Connectivity
Bibliographic record
Abstract
Introduction: Quantitative electroencephalography (QEEG) brain frequency and network analyses are known to differentiate between disease stages in Parkinson’s disease (PD) and are possible biomarkers. They correlate with cognitive decline. Little is known about changes in brain networks in relation to apathy. Objective/Aims: To analyze changes in brain network connectivities related to apathy. Methods: 40 PD patients (14 PD with mild cognitive deficits and 26 PD with normal cognition) were included. All patients had extensive neuropsychological testing; apathy was evaluated using the apathy evaluation score (AES, median 24.5, range 18 - 39). Resting state EEG was recorded with 256 electrodes and analyzed using fully automated Matlab® code (TAPEEG). For estimation of the connectivities between brain regions, PLI (phase lag index) was used, enhanced by a microstates segmentation. Results: After correction for multiple comparisons, significant correlations were found for single alpha2-band connectivities with the AES (p-values < 0.05). Lower connectivities, mainly involving the left fronto-polar region, were related to higher apathy scores. Conclusions: In our sample of patients with PD, apathy correlates with a network alteration mainly involving the left fronto-polar region. This might be due to dysfunction of the cortico-basal loop, modulating motivation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".