Changes in resting-state functional MRI connectivity during and after transcranial direct current stimulation in healthy adults
Bibliographic record
Abstract
Introduction: Transcranial direct current stimulation (tDCS) applied over the dorsolateral prefrontal cortex (DLPFC) at rest can influence behaviors. However, its mechanisms remain poorly understood. This study examined the effect of a single session of tDCS over the bilateral DLPFC on resting-state functional connectivity using fMRI (rs-fcMRI) during and after stimulation in healthy adults. We also investigated whether baseline rs-fcMRI predicted tDCS-induced changes in rs-fcMRI. Methods: This was a randomized, sham-controlled, double-blind, crossover study. We delivered tDCS for 30 min at 1 mA with the anode and cathode over the left and right DLPFC, respectively. We used seed-based analyses to measure tDCS-induced effects on whole-brain rs-fcMRI using a 3 (before, during, after stimulation) × 2 (active, sham stimulation) ANOVA. Results: There were four significant Time × Stimulation interactions on the connectivity scores with the left DLPFC seed (under the anode electrode) and no interactions for the right DLPFC seed (under the cathode electrode). tDCS changed rs-fcMRI between the left DLPFC seed and parieto-occipital, parietal, parieto-occipitotemporal, and frontal clusters during and after stimulation, as compared to sham. Furthermore, rs-fcMRI prior to stimulation predicted some of these tDCS-induced changes in rs-fcMRI during and after stimulation. For instance, rs-fcMRI of the fronto-parietooccipital network predicted changes observed after active stimulation, rs-fcMRI of the fronto-parietal network predicted changes during active stimulation, whereas rs-fcMRI of the fronto-parieto-occipitotemporal and the frontal networks predicted changes both during and after active stimulation. Discussion: Our findings reveal that tDCS modulated rs-fcMRI both during and after stimulation mainly in regions distal, but also in those proximal to the area under the anode electrode, which were predicted by rs-fcMRI prior to tDCS. It might be worth considering rs-fcMRI to optimize response to tDCS.
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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 | 0.001 |
| 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".