Comparing neural activity of older adults with and without Parkinson’s disease using mobile electroencephalography in different environments
Bibliographic record
Abstract
Abstract Background Parkinson’s disease is a progressive neurodegenerative disorder that is becoming more prevalent as the population ages. Mobile neuroimaging has made it possible to observe cortical activity in this population outside of standard laboratory environments. Yet, few studies have explored the portability of these devices in a true real‐world environment without a specific task imposed on participants (e.g., dual task, motor demands). Method Mobile electroencephalography (EEG) was utilized to examine and compare cortical activity during sitting in different environments across older adults with and without Parkinson’s disease. We used the Muse S Generation 2 Brain‐Sensing Headband to record brain function. The first condition involved participants sitting in a standard laboratory environment while their brain activity was recorded. In the second condition, participants sat in an indoor space that included a living green wall, natural light, and other people while their brain activity was recorded. Fast Fournier Transform (FFT) analysis was performed on the raw EEG data to obtain corresponding waves for each electrode to examine power (uV^2) at each frequency (Hz). Result Preliminary findings demonstrate significant differences in mean cortical activations across older adults with and without Parkinson’s disease. Differences in cortical activations were also observed when comparing the laboratory and real‐world environment. Conclusion These findings suggest that elicited brain activity may differ across older adults with and without Parkinson’s disease and across different environments. These findings expand current knowledge on Parkinson’s disease, brain function, and cognition using real‐world methods and technology, which may inform interventions to increase quality of life among this population. As our findings suggest that environmental factors may modulate cortical activity, we also highlight the potential and importance for real‐world methods to supplement standard research practices to increase the ecological validity of studies conducted across the scientific community.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".