Assessing motor cortex excitability and its relationship with brain atrophy in Ahlzeimer’s disease
Bibliographic record
Abstract
Abstract Background Cortical excitability detected using resting electroencephalography (EEG) or transcranial magnetic stimulation (TMS) combined with EEG has been proposed as a new neurophysiological marker of Alzheimer’s dementia (AD). However, the link between cortical excitability and structural changes in AD is not well understood. The objective of this study was to assess the relationship between cortical excitability and brain structure (cortical thickness) in the motor cortex of patients with AD and healthy older individuals. Methods 63 participants (38 females) with AD (Mage = 74.5, SD = 8.0) and 48 healthy individuals (27 females) (Mage = 71.1, SD = 7.8) were included. hot spot’ over the left motor cortex was defined as the location that generated maximal motor‐evoked potentials in the abductor pollicis brevis muscle. Each participant’s resting motor threshold (rMT) was determined using the ‘hotspot’ by finding the lowest stimulus strength to evoke a motor‐evoked potential with a peak‐to‐peak amplitude of ≥50 µV in at least five of ten consecutive single pulse TMS trials. T1w MRI scans were pre‐processed using the anatomical pipeline in fMRIPrep v20.2.6. This pipeline includes recon‐all from Freesurfer v6.0.1, which estimates cortical thickness based on ROIs defined in the Desikan‐Killiany atlas. Results Participants with AD had lower motor cortex thickness than healthy individuals (t(93) = ‐4.398, p = <0.001). Participants with AD had lower rMT (indicative of higher excitability) than healthy individuals (t(109) = ‐2.265, p = 0.026). Within the total sample, rMT was correlated with motor cortex thickness (r = 0.216, df = 95, p = 0.036). Conclusions Consistent with previous literature, our study supports that AD is associated with decreased cortical thickness and higher motor cortex excitability. We also found that changes in cortical thickness positively correlated with rMT, suggesting that cortical hyperexcitability is influenced by cortical neurodegeneration. Future studies may wish to examine the association between cortical excitability and functional imaging measures to understand specific mechanisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".