Cortical morphology predicts placebo response in multiple sclerosis
Bibliographic record
Abstract
ABSTRACT Although significant insights have been gained into the neural mechanisms of acute placebo responses, less is known about the mechanisms of longer-term placebo responses, such as those seen in clinical trials, or the interactions between these mechanisms and brain disease. We examined neuropathological and morphological brain correlates of placebo responses in a randomized clinical trial of a controversial endovascular treatment (“liberation therapy”) for multiple sclerosis. Patients were randomized to receive either balloon or sham extracranial venoplasty and followed for 48 weeks. The trial did not support therapeutic efficacy of venoplasty, but a subset of both venoplasty- and sham-treated patients reported an improvement in health-related quality of life that peaked at 12 weeks following treatment, suggesting a placebo response. Placebo responders had higher lesion activity than placebo non-responders. Although placebo responders did not differ from non-responders in terms of total normalized brain volume, regional grey or white matter volume or cortical thickness, graph theoretical analysis of cortical thickness covariance showed that placebo non-responders had a more homogenous cortical thickness topology with a more small-world-like architecture. In placebo non-responders, lesion load inversely predicted cortical thickness in primary somatosensory and motor areas, association areas, precuneus and insula, primarily in the right hemisphere. In placebo responders, lesion load was unrelated to cortical thickness. The neuropathological process in MS may result in a cortical configuration that is less suited to functional integration and less capable of generating a sustained placebo response.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".