Influence of GABA <sub>A</sub> and GABA <sub>B</sub> receptor activation on auditory sensory gating and its association with anxiety in healthy volunteers
Bibliographic record
Abstract
Background: Dysfunctional sensory gating in anxiety disorders, indexed by the failure to inhibit the P50 event-related potential (ERP) to repeated stimuli, has been linked to deficits in the major inhibitory neurotransmitter γ-aminobutyric acid (GABA). Aims/Methods: This study, conducted in 30 healthy volunteers, examined the acute effects of GABA A (lorazepam: 1 mg) and GABA B receptor (baclofen: 10 mg) agonists on P50 measures of auditory sensory gating within a paired-stimulus (S1-S2) paradigm and assessed changes in gating in relation to self-ratings of anxiety. Results: Compared to placebo, lorazepam reduced ERP indices of sensory gating by attenuating response to S1. Although not directly impacting P50 inhibition, baclofen-induced changes in gating (relative to placebo) were negatively correlated with trait but not state anxiety. Conclusions: These preliminary findings support the involvement of GABA in sensory gating and tentatively suggest a role for GABA B receptor signaling in anxiety-associated gating dysregulation.
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 | 0.000 | 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".