Evidence of a large current of transcranial alternating current stimulation directly to deep brain regions
Bibliographic record
Abstract
Deep brain regions such as hippocampus, insula, and amygdala are involved in neuropsychiatric disorders, including chronic insomnia and depression. Our recent reports showed that transcranial alternating current stimulation (tACS) with a current of 15 mA and a frequency of 77.5 Hz, delivered through a montage of the forehead and both mastoids was safe and effective in intervening chronic insomnia and depression over 8 weeks. However, there is no physical evidence to support whether a large alternating current of 15 mA in tACS can send electrical currents to deep brain tissue in awake humans. Here, we directly recorded local field potentials (LFPs) in the hippocampus, insula and amygdala at different current strengths (1 to 15 mA) in 11 adult patients with drug-resistant epilepsy implanted with stereoelectroencephalography (SEEG) electrodes who received tACS at 77.5 Hz from 1 mA to 15 mA at 77.5 Hz for five minutes at each current for a total of 40 min. For the current of 15 mA at 77.5 Hz, additional 55 min were applied to add up a total of 60 min. Linear regression analysis revealed that the average LFPs for the remaining contacts on both sides of the hippocampus, insula, and amygdala of each patient were statistically associated with the given currents in each patient (p < 0.05-0.01), except for the left insula of one subject (p = 0.053). Alternating currents greater than 7 mA were required to produce significant differences in LFPs in the three brain regions compared to LFPs at 0 mA (p < 0.05). The differences remained significant after adjusting for multiple comparisons (p < 0.05). Our study provides direct evidence that the specific tACS procedures are capable of delivering electrical currents to deep brain tissues, opening a realistic avenue for modulating or treating neuropsychiatric disorders associated with hippocampus, insula, and amygdala.
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".