Anodal transcranial direct current stimulation modulates GABAB-related intracortical inhibition in the M1 of healthy individuals
Bibliographic record
Abstract
It is known that transcranial direct current stimulation (tDCS) can induce polarity-specific shifts in brain excitability of the primary motor cortex (M1) with anodal tDCS enhancing and cathodal tDCS reducing cortical excitability. However, less is known about its impact on specific intracortical inhibitory mechanisms, such as γ-aminobutyric acid B (GABAB)-mediated inhibition. Consequently, the aim of the present study was to assess the impact of anodal and cathodal tDCS on M1 intracortical inhibition in healthy individuals. Long-interval intracortical inhibition (LICI) and cortical silent period (CSP) duration, both presumably mediated by GABAB receptors, were assessed using transcranial magnetic stimulation immediately before and after a 20 min session of tDCS over the left M1. Anodal tDCS significantly enhanced motor evoked potential size and reduced CSP duration, whereas it had no effect on LICI. Cathodal stimulation did not significantly modulate motor evoked potential size, CSP duration or LICI. This study provides evidence that anodal tDCS, presumably by synaptic plasticity mechanisms, has a direct effect on GABAB-meditated inhibition assessed by the CSP, but not by LICI. Our results further suggest that CSP and LICI probe distinct intracortical inhibitory mechanisms as they are differentially modulated by anodal tDCS. Finally, these data may have clinical value in patients in whom a pathological increase in CSP duration is present, such as 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.
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".