Coordinated Networks in the Human Brainstem and Spinal Cord during the Expectation of Pain
Bibliographic record
Abstract
Introduction/Aim: Spontaneous variations in activity of brainstem (BS) and spinal cord (SC) regions may arise from a number of functions such as autonomic regulation, sensory, and motor functions. Recent evidence suggests that changes in a person’s cognitive/emotional state are linked to changes in identified BS and SC resting-state networks, indicating that these networks likely play a role in the integration of homeostatic autonomic functions. The aim of this study was to investigate how these networks change when participants are specifically expecting pain. Methods: Previously, data were obtained from the cervical SC and brainstem in 17 healthy participants during a stimulation paradigm that involved a predictable noxious heat stimulus. Blood oxygenation-level dependent (BOLD) fMRI data were obtained at 3 Tesla, with T2-weighted single-shot fast spin-echo imaging. For the current study we investigated functional connectivity in the entire 3D region with structural equation modelling (SEM) during the first two minutes of each run (baseline period, and after participants were told whether to expect a painful stimulus). Results: SEM results showed extensive connectivity within and across BS and SC regions both when participants were expecting pain, and when they were expecting no pain. Furthermore, significant differences in connectivity between regions of the BS and SC were also identified across study conditions. Discussion/Conclusions: The results indicate that connectivity across BS/SC networks is influenced by the expectation of pain in specific ways. The known functions of the regions involved support the conclusion that these networks likely serve to integrate autonomic regulation functions with pain processing.
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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 | 0.003 | 0.004 |
| 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) | 0.000 | 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".