Comparative Efficacy of Dual- vs. Single-Node tACS in Amnestic Mild Cognitive Impairment: Behavioral and EEG Evidence
Bibliographic record
Abstract
The efficacy of current transcranial stimulation in cognitive disorders is limited by single-node intervention. Recent evidence indicates that amnestic mild cognitive impairment (aMCI) is associated with dysconnectivity in the frontoparietal network (FPN) and abnormal theta oscillations. Modulating the FPN with theta-frequency stimulation therefore represents a promising intervention for aMCI. We developed a noninvasive transcranial alternating current stimulation (tACS) protocol to modulate long-range theta interactions within the FPN in aMCI patients. Thirty patients with aMCI were randomly assigned to receive 10 sessions (2 mA, 6 Hz, 25 min per session) of either dual-node tACS applied over the right FPN (i.e., the dorsolateral prefrontal cortex, DLPFC, and the posterior parietal cortex, PPC) or single-node tACS over the right DLPFC alone. Participants also undergone EEG recordings during resting state, a 2-back working memory, and an associative memory task before and after intervention. Compared with single-node stimulation, dual-node stimulation produced more significant improvements in global cognition, as measured by Montreal Cognitive Assessment. Dual-node stimulation also enhanced resting-state theta power in dorsolateral and midline prefrontal cortices. Furthermore, dual-node stimulation was superior to single-site stimulation in improving memory performance and network dynamics. Specifically, it enhanced theta-gamma phase-amplitude coupling in right DLPFC during the working memory task and increased right frontal-to-parietal theta-phase synchronization during the associative memory task. This study provides preliminary evidence that dual-node tACS targeted over the FPN may offer behavioral and neurophysiological benefits over single-node stimulation in aMCI. Trial registration: Chinese Clinical Trial Registry, ChiCTR2200058652; Registration Date: 2022-03-13.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".