Resting state EEG Abnormalities and their Relationship with TMS‐EEG induced Cortical Excitability in Alzheimer's Dementia
Bibliographic record
Abstract
Abstract Background Previous literature has identified slowing of resting state electroencephalography (EEG) rhythm and abnormal cortical excitation in Alzheimer’s Dementia (AD). However, the relationship between these two divergent functional abnormalities and cognitive symptoms of AD are not well understood. Method Resting state EEG signal was recorded in participants with AD and HCs for 5 minutes with eyes closed. Relative resting state EEG power was measured for the five frequency bands. Participants underwent a single pulse transcranial magnetic stimulation (TMS) combined with EEG. Cortical evoked activity (CEA) was assessed using TMS‐evoked potential (TEP) rectified area under the curve (AUC) from 25 to 80 ms post‐TMS stimulus, and the TEPs peak amplitudes were calculated by taking the maximal peak in the following time windows: 25 – 35 ms (P30), 40 – 50 ms (N45), and 55 – 65 ms (P60). Result Compared to 32 HC (18 females; mean ± SD age: 69.3 ± 7.9 years), 52 participants with AD (32 females; 74.2 ± 8.5 years) had higher relative theta power than HCs (t(66.6) = 5.34, p<0.001). AD participants also had a significantly lower alpha power (t(76) = ‐3.03, p=0.003) and beta power (t(76) = ‐2.51, p=0.014) than HCs. Controlling for sex, age and years of education, AD participants showed a positive association between theta power and CEA (rpartial=0.573, p=0.008); and an inverse association between alpha power and CEA (rpartial=‐0.471, p=0.036). Theta power in AD participants showed a positive association with P60 (rpartial=‐0.637, p=0.003) and an inverse association with N45 (rpartial=‐0.512, p=0.025), while alpha power was inversely associated with P60 (rpartial=‐0.531, p=0.016). Conclusion This study showed a positive association between resting state EEG slowing and increased cortical excitability in AD, indicating a possible shared mechanistic pathway between these abnormalities.
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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 | 0.001 | 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".