Accelerated Deep Transcranial Magnetic Stimulation for Stimulant Use Disorder
Bibliographic record
Abstract
Transcranial direct current stimulation (tDCS), when targeted at the left dorsolateral prefrontal cortex (DLPFC) has been shown to be an effective treatment for depression.However, the underlying mechanism of this effect remains largely unknown.Given that depression can significantly impact how patients process reward-and error-related information, our study aimed to investigate whether tDCS, applied to a non-depressed sample, would modulate the amplitudes of event-related potentials (ERPs) during two cognitive tasks: the gambling doors task and the Go/No-Go task.These tasks provide information on how the participant reacts to reward-and error-related information.In gambling doors task, stimulation had discernible effects on the N1-P2 complex, but it did not significantly influence the reward positivity (RewP) response.Interestingly, the late positive polarity (LPP) showed a modest elevation in the stimulation group.In Go/No-Go task, participants in the stimulation group exhibited shortened reaction times compared to the control group.However, there was no significant difference in the number of errors committed between the two groups.Notably, the amplitude of error-related negativity (ERN) remained consistent across both groups, while the later-emerging error positivity (Pe) was more pronounced in the stimulation group.The results indicate that anodal tDCS targeted at the left DLPFC might alter conscious processing, rather than automatic processing, of error-and reward-related information.
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".