Brain Vital Signs Detect Information Processing Differences When Neuromodulation Is Used During Cognitive Skills Training
Bibliographic record
Abstract
Background: Neuromodulation through translingual neurostimulation (TLNS) has been shown to initiate long-lasting processes of neuronal reorganization with a variety of outcomes (i.e., neuroplasticity). Non-invasive TLNS is increasingly accessible through the Portable Neuromodulation Stimulator (PoNS®), a medical device that delivers electrical stimulation to the tongue in order to activate the trigeminal (V) and facial (VII) cranial nerves. Anecdotal reports from previous clinical studies have suggested incidental improvements in cognitive function. To objectively explore this observation, we examined TLNS-related effects on the semantic N400 brain vital sign cognitive response during cognitive skills training in healthy individuals. Methods: Thirty-seven healthy volunteers were randomized to receive simultaneous TLNS (treatment) or no TLNS (control) while undergoing cognitive skills training. Cognitive training was conducted for two 20-minute sessions (morning and afternoon/evening) over three consecutive days. Brain vital signs were evaluated at baseline, Day 1, and Day 3. Analyses focused on cognitive processing as measured by N400 changes in amplitude and latency. Results: Over the 3-day course of cognitive training, the N400 amplitude decreased significantly in the control group due to habituation (p=0.028). In contrast, there was no significant change in the TLNS treatment group. Conclusion: TLNS led to a sustained N400 response during cognitive skills training, as measured by the brain vital signs framework. The study findings suggest differential learning effects due to neuromodulation, consistent with increased attention and cognitive vigilance.
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 | 0.001 |
| 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) | 0.003 | 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".