EEG biomarkers of α5-GABA positive allosteric modulators in rodents
Bibliographic record
Abstract
Abstract Reduced cortical inhibition mediated by gamma-aminobutyric acid (GABA) is reported in depression, anxiety disorders, and aging. Novel positive allosteric modulator that specifically target α5-GABA A receptor subunit (α5-PAM), ligand GL-II-73, shows anxiolytic, antidepressant, and pro-cognitive effects without the common side effects associated with non-specific modulation by benzodiazepines such as diazepam (DZP), thus suggesting novel therapeutic potential. However, it is unknown if α5-PAM has detectable signatures in clinically-relevant brain electroencephalography (EEG). We analyzed EEG in freely moving rats at baseline and following injections of α5-PAM and DZP. We showed that α5-PAM specifically decreased theta peak power whereas DZP shifted peak power from high to low theta, while increasing beta and gamma power. EEG decomposition showed that these effects were periodic and corresponded to changes in theta oscillation event duration. Our study thus shows that α5-PAM has robust and distinct EEG biomarkers in rodents, indicating that EEG could enable non-invasive monitoring of α5-PAM treatment efficacy.
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 | 0.000 |
| 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".