Combined effects of pharmacological interventions and intermittent theta-burst stimulation on motor sequence learning
Bibliographic record
Abstract
Abstract Drugs that modulate N-methyl-D-aspartate (NMDA) or γ-Aminobutyric acid type A (GABA A ) receptors can shed light on their role in synaptic plasticity mechanisms underlying the effects of non-invasive brain stimulation. However, research on the combined effects of these drugs and exogenous stimulation on motor learning is limited. This study aimed to investigate the effects of pharmacological interventions combined with intermittent theta-burst stimulation (iTBS) on human motor learning. Nine right-handed healthy subjects (mean age ± SD: 31.56 ± 12.96 years; 6 females) participated in this double-blind crossover study. All participants were assigned to four drug conditions in a randomized order: (1) D-cycloserine (partial NMDA receptor agonist), (2) D-cycloserine + dextromethorphan (NMDA receptor agonist + antagonist), (3) lorazepam (GABA A receptor agonist), and (4) placebo (identical microcrystalline cellulose capsule). After drug intake, participants practiced the 12-item keyboard sequential task as a baseline measure. Two hours after drug intake, iTBS was administered at the primary motor cortex. Following iTBS, the retention test was performed in the same manner as the baseline measure. Our findings revealed that lorazepam combined with iTBS impaired motor learning during the retention test. Future studies are still needed for a better understanding of the mechanisms through which TMS may influence human motor learning.
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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) | 0.001 | 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".