Clinical thresholds in pain-related facial activity linked to differences in cortical network activation in neonates
Bibliographic record
Abstract
ABSTRACT: In neonates, a noxious stimulus elicits pain-related facial expression changes and distinct brain activity as measured by electroencephalography, but past research has revealed an inconsistent relationship between these responses. Facial activity is the most commonly used index of neonatal pain in clinical settings, with clinical thresholds determining if analgesia should be provided; however, we do not know if these thresholds are associated with differences in how the neonatal brain processes a noxious stimulus. The objective of this study was to examine whether subclinical vs clinically significant levels of pain-related facial activity are related to differences in the pattern of nociceptive brain activity in preterm and term neonates. We recorded whole-head electroencephalography and video in 78 neonates (0-14 days postnatal age) after a clinically required heel lance. Using an optimal constellation of Neonatal Facial Coding System actions (brow bulge, eye squeeze, and nasolabial furrow), we compared the serial network engagement (microstates) between neonates with and without clinically significant pain behaviour. Results revealed a sequence of nociceptive cortical network activation that was independent of pain-related behavior; however, a separate but interleaved sequence of early activity was related to the magnitude of the immediate behavioural response. Importantly, the degree of pain-related behavior is related to how the brain processes a stimulus and not simply the degree of cortical activation. This suggests that neonates who exhibit clinically significant pain behaviours process the stimulus differently and that neonatal pain-related behaviours reflect just a portion of the overall cortical pain response.
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 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 | 0.018 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".