Significance of Non-phase Locked Oscillatory Brain Activity in Response to Noxious Stimuli
Bibliographic record
Abstract
BACKGROUND: Although current pain-evoked electroencephalographic (EEG) studies provide valuable information regarding human brain regions involved in pain, they have mostly considered neuronal responses which oscillate in phase following a painful event. In many instances, cortical neurons respond by generating bursts of activity that are slightly out of phase from trial-to-trial. These types of activity bursts are known as induced brain responses. The significance of induced brain responses to pain is still unknown. METHODS: In this study, 23 healthy subjects were given both non-painful and painful transcutaneous electrical stimulations in separate testing blocks (stimulation strength was kept constant within blocks). Subjective intensity was rated using a numerical rating scale, while cerebral activity tied to each stimulation was measured using EEG recordings. Induced brain responses were identified using a time frequency wavelet transform applied to average-removed single trials. RESULTS: Results showed a pain-specific burst of induced theta activity occurring between 180 and 500 ms post-shock onset. Source current density estimations located this activity within the dorsolateral prefrontal cortex (DLPFC, bilaterally), however, only right DLPFC activity predicted a decrease in subjective pain as testing progressed. CONCLUSION: This finding suggests that non-phase locked neuronal responses in the right DLPFC contribute to the endogenous attenuation of pain through time. PERSPECTIVE: This article presents neuroimaging findings demonstrating that, in response to pain, non-phase locked bursts of theta activity located in the right dorsolateral prefrontal cortex are associated with a progressive decrease in subjective pain intensity, which has potentially important implications regarding how humans endogenously control their experiences of pain.
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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 | 0.000 | 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) | 0.002 | 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".