Enhancing communication and collaboration with youth-oriented psychopharmacology resources
Bibliographic record
Abstract
This open-label pilot study explored the effects of a course of accelerated high-frequency repetitive transcranial magnetic stimulation (HF-rTMS) on two neurocognitive domains (decision-making and impulse control) in patients with major depressive disorder (MDD).Participants with MDD and a treatment resistant major depressive episode (n=24) underwent twice-daily HF-rTMS targeted at the left dorsolateral prefrontal cortex (lDLPFC) over two weeks. Psychopathology was assessed by clinician-administered and self-reported measures of depression and anxiety; decision-making was assessed by the Iowa Gambling Task, the Balloon Analog Risk Task and the Game of Dice Task; impulse control was assessed by the Stroop Color-Word Task, the Continuous Performance Task and the Stop-Signal Task.Depression and anxiety scores significantly improved from pre-post HF-rTMS treatment. However, none of the decision-making or impulse control variables of interest changed significantly from pre-post HF-rTMS. Moreover, there was no correlation between changes in psychopathological symptoms and in neurocognition.This is a moderately sized open label trial, and the confounds of ongoing psychotropics and illness chronicity can not be excluded in this treatment resistant sample.There is dissociation between acute symptomatic benefit after a course of accelerated HF-rTMS applied to the lDLPFC in treatment resistant MDD and performance on tests of decision making and impulse control. Though rTMS appears cognitively safe, additional research is warranted to understand this potential dissociation and its putative clinical implications.
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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".