Exploring ultraweak photon emissions as optical markers of brain activity
Bibliographic record
Abstract
Brains are highly metabolic organs that emit ultraweak photon emissions (UPEs), which predict oxidative stress, aging, and neurodegeneration. UPEs are triggered by neurotransmitters and biophysical stimuli, but they are also generated by cells at rest and can be passively recorded using modern photodetectors in dark environments. UPEs play a role in cell-to-cell communication, and neural cells might even have waveguiding properties that support optical channels. However, it remains uncertain whether passive light emissions can be used to infer brain states as electric and magnetic fields do for encephalography. We present evidence that brain UPEs differ from background light in spectral and entropic properties, respond dynamically to tasks and stimulation, and correlate moderately with brain rhythms. We discuss these findings in the context of other neuroimaging methods, the potential of new measurement parameters, the limitations of light-based readouts, and the possibility of developing a platform to readout functional brain states: photoencephalography.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".