Baseline dependency of nicotine’s sensory gating actions: similarities and differences in low, medium and high P50 suppressors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Reduced suppression of the P50 auditory event-related potential in schizophrenia patients relative to normal controls is indicative of a sensory gating deficit and is one of the most robust findings reported for functional brain abnormalities in this disorder. However, there is considerable gating variability in patients and controls and there is little understanding as to how inter-individual differences moderate gating responses to drugs and nicotinic agonists in particular, which have shown potential to reverse gating deficits. In this study the effects of acutely administered nicotine (gum, 6 mg) on sensory gating in a paired (S₁-S₂) auditory stimulus paradigm were investigated in 57 healthy, non-smoking volunteers stratified as low (n = 19), medium (n = 19) and high (n = 19) P50 suppressors on the basis of three separate baseline derived gating indices, P50 ratios, P50 difference scores, and gating difference waveforms. Relative to placebo, nicotine consistently improved gating in low suppressors as stratified with all three gating indices, exerted no effects in medium suppressors and reduced gating in high suppressors. Analysis of individual stimulus (S₂, S₂) amplitudes showed distinctly different mechanisms of action underlying nicotine effects in individuals with low and high baseline suppression. The results parallel similar findings of baseline-dependency in the gating effects of several antipsychotic drugs in healthy volunteers and support the use of group segmentation as a translational model in novel cognitive drug development for schizophrenia.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it