Monitoring the adaptation to experimental pain using functional near infrared spectroscopy
Bibliographic record
Abstract
Background: Despite pain being one of the more thoroughly studied phenomena, it is still one of the more complex and least well understood. Studies of late, in particular imaging studies, have made an attempt to take individuals' subjective response to pain into consideration, while observing how their bodies respond physiologically. This has led to our lab's focus on the adaptation to pain. As adaptation is the reduction of the response to a given stimulus over time, monitoring the adaptation to experimental pain over time using functional near infrared spectroscopy shows the change in autonomic response with each additional exposure. Doing this, while also observing the change in perception to each additional exposure, can further progress the research of pain imaging, and more importantly, show how changes in physiological response and perceptive response correlate over time. Methods: In the investigations outlined in the aims of this thesis, experimental pain (the cold pressor test in a repeated-measures fashion) was used to conduct experiments in healthy subjects. In conjunction with this, the McGill Pain Questionnaire and State Trait Anxiety Inventory were employed during experimentation as well. In post experimentation analysis, multilevel modeling, linear regression and clustering were the main techniques used to understand how the pain response changes with each additional exposure to a stimulus. Results: These statistical techniques yielded results that suggest that with each additional exposure to noxious stimulus, the magnitude of a subjects' autonomic response continues to diminish. Through the measures of perception, the subjects did not show significant change with each additional exposure; although, there was a trend demonstrating that the subjects felt the pain with slightly less intensity with each additional exposure. Conclusions: From interpreting the results of the studies performed as a part of this thesis, it is evident that functional near infrared spectroscopy is a powerful enough imaging tool to monitor adaptation to repeated exposure of stimuli. To further understand how perception and autonomic response relate, more studies with a greater number of subjects will give greater understanding of the connection (or lack thereof) between the two.
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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 | 0.001 | 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 | 0.001 |
| 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".