Electroencephalographic Effects of Galantamine in Major Depressive Disorder
Bibliographic record
Abstract
Nicotinic acetylcholine receptor stimulation is a potential target for controlling symptoms in several psychiatric disorders. Galantamine is a cholinesterase inhibitor that can modulate the nicotinic receptor sites. In this study, we examined the effect of galantamine on the quantitative EEG in patients with major depression. Twenty patients were included in a randomized, double-blinded, placebo-controlled trial. Patients received galantamine (8 mg/day for 4 weeks then 16 mg/day for another 4 weeks) or placebo for eight weeks. Quantitative EEG using the international 10 to 20 configuration, 9 minutes of resting, eyes closed, and eyes open was done before and after the study period. Nineteen patients completed the study and their data were included in the final analysis. The results showed that galantamine compared with placebo reduced absolute band power that was statistically significant (using multivariate analysis of variance) for beta wave [F(1,17) = 2.48, P = 0.03]; the between-subject effect was significant on the left and right posterior, and left central regions. The multivariate analysis of variance model for alpha was not significant [F(1,17) = 1.07, P = 0.43]. We suggest that the reduction in absolute power after galantamine administration could be a sign of brain activation as a result of modulation of neurotransmitter release. We recommend the initiation of a larger study to confirm our findings and help in understanding the neuropathology of major depression.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".