Effectiveness of optimized transcranial direct current stimulation based on the electric field strength of computational model on cognitive function in patients with mild cognitive impairment
Bibliographic record
Abstract
Abstract The various electric field distributions induced by transcranial direct current stimulation (tDCS) in each subject were considered as one potential factor of inter-subject variability in the effects of tDCS. Numerical optimization techniques could be applied to a computer model with T1-weighted MR images of individual subjects to reduce the variability of tDCS-induced electric field (EF) distribution. None of the studies have prospectively verified the role and effectiveness of tDCS with optimal electrode position (opt-tDCS). This study was aim to examine the effectiveness of EF-based opt tDCS in patients with MCI on cognitive function and depression, so we determined that possible electrode locations in defined grid and found best electrode positions which maximize EF in target region; inferior and middle frontal gyrus in left dorsolateral prefrontal cortex (LDLPFC). 58 MCI patients participated in this study. All patients underwent MRI scanning and were assessed with the cognitive function and depression examination before the first session and after the 10th session. Cognitive function examination and depression scale include Hamilton Depression Rating Scale (HDRS), Korean version of Montreal Cognitive Assessment (MoCA-K), the Korean version of Consortium to Establish a Registry for Alzheimer’s Disease (CERAD-K) neuropsychological assessment battery. Patients received tDCS sessions with 2 mA, disc-shaped electrodes of a radius 3 cm over optimized electrode location for 30 min/day, 5 days/week for 2 weeks. This study found significant effects of opt-tDCS on changes in cognitive function of CERAD-K, the 15-item Boston Naming Test (p < 0.05), Word List Memory (p < 0.05), Word List Recognition (p < 0.05), total scores of memory domains (p < 0.05) and total CERAD-K scores excluding the MMSE-K scores (p < 0.05). There were no adverse events such as itching or burning sensation. The results suggest that opt-tDCS is safe and could improve cognitive function in MCI patients. Research Category and Technology and Methods Clinical Research: 9. Transcranial Direct Current Stimulation (tDCS) Keywords: tDCS, optimized tDCS, MCI, cognitive rehabilitation
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".