An Investigation of Neural Responses to the Anticipation and Experience of Pain in Humans, Revealed by Functional Magnetic Resonance Imaging of the Brainstem and Spinal Cord
Bibliographic record
Abstract
Pain is a complex, highly subjective phenomenon in humans and the brainstem and spinal cord serve fundamental roles in the processing and modulation of ascending nociceptive signals. Emotional-cognitive factors such as anticipation have been shown to alter the pain experience and research has indicated there may be a dysfunction in pain processing in individuals with fibromyalgia (FM). Further research is needed in order to fully understand the underlying mechanisms involved in FM and how anticipation influences pain at the spinal level in both healthy and diseased states. The first aim of this thesis is to investigate neural responses in regions associated with the descending modulation of pain during anticipation in individuals with FM, compared to healthy controls (HC). FMRI data analyzed from two previous studies revealed no significant differences in neural responses during the anticipation of pain in FM and HC groups, suggesting that heightened pain in FM is not related to altered emotional-cognitive influences. This work indicated that the current understanding of pain is incomplete and led to forming the hypotheses for the following study in which we investigated the neural correlates of pain anticipation in healthy humans. The second aim of this thesis is to characterize functional connectivity associated with the anticipation of pain in healthy individuals. This was accomplished through a comparison of fMRI responses to noxious and innocuous thermal stimuli in time periods before and during stimulation. The results indicated similar functional connectivity during the anticipation of painful and nonpainful stimuli as well as new aspects of connectivity in pain networks during stimulation. Together, the work of the current thesis has revealed new aspects of neural activity and functional connectivity associated with the anticipation of pain in both healthy and diseased states using fMRI of the brainstem and spinal cord.
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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 | 0.000 |
| 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) | 0.001 | 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".