Modifying resting-state EEG microstates with pulsed near-infrared transcranial photobiomodulation: a randomized sham-controlled crossover study
Bibliographic record
Abstract
Abstract Objective: Transcranial Photobiomodulation (tPBM) is a novel noninvasive brain stimulation technique that applies near-infrared (NIR) light and influences cortical oscillation. However, the mechanism and extent of its effects are yet to be understood. In this study, we investigated the effect of active vs. sham tPBM on the temporal dynamics of large-scale brain networks using resting-state EEG microstate. Methods: Twenty healthy volunteers received 20 minutes of active or sham tPBM using 810 nm light-emitting diodes (LEDs), pulsed at 40 Hz with 50% duty cycle, delivered transcranially to the default mode network. 10-minute eyes-closed EEG recordings were collected before and after each stimulation session. The artifact-free resting-state data were used for microstate analysis, focusing on the mean duration, frequency of occurrence, and ratio of time coverage. We used the two-step k-mean clustering method to identify microstates that best describe the dataset across all subjects and conditions. Results: Our analysis identified four microstate classes (A-D) which explained 76% of the global variance. The active tPBM, showed modification of the temporal parameters of class A, with a posterior orientation of the mapped field, before and after stimulation. We found a significant increase in the duration (t=3.3, p=0.004), frequency of occurrence (t=2.7, p=0.013), and ratio of time coverage (t=3.3, p=0.001). The sham tPBM did not show any feature modification in the four microstate classes. Conclusion: For the first time, we revealed the influence of tPBM on the temporal dynamics of large-scale brain networks represented by modifications in the EEG microstates. The changes in this study were significant and occurred immediately after 20 minutes of active tPBM stimulation. Our findings provide more credibility to tPBM as an effective brain stimulation technique and warrant further research. Microstate measures can potentially be added to EEG, fMRI, and clinical assessments as tools to improve personalized treatments with tPBM. Keywords: photobiomodulation, EEG, microstate, brain networks
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".