Neural Correlates of Deficits in Pain-Related Affective Meaning Construction in Patients With Chronic Pain Disorder
Bibliographic record
Abstract
OBJECTIVE: Psychological and neural mechanisms of the affective dimension of pain are known to be disturbed in patients with chronic pain disorder. The aim of this functional magnetic resonance imaging study was to assess the neurofunctional and behavioral measures underlying the ability to construct pain-related affective meaning in a painful situation by comparing 21 clinically and psychometrically well-characterized patients with persistent non-nociceptive somatoform pain with 19 healthy controls. METHODS: The functional magnetic resonance imaging task involved viewing pictures depicting human hands and feet in different painful and nonpainful situations. Participants were asked to estimate the perceived pain intensity. These data were correlated with behavioral measures of depression, alexithymia, and general cognitive and emotional empathy. RESULTS: In a hypothesis-driven region-of-interest analysis, the healthy control group exhibited greater activation of the left perigenual anterior cingulate cortex than patients with pain (Montreal Neurological Institute coordinates (x y z)=-8 38 0; cluster extent=54 voxels; T=4.28; p=.006 corrected for multiple comparisons at cluster level). No group differences in the activation of the anterior insular cortex were found. Scores on self-assessment instruments (Beck Depression Inventory I, Interpersonal Reactivity Index, and 20-item Toronto Alexithymia Scale) did not influence neuroimaging results. CONCLUSIONS: Our results suggest that patients with chronic medically unexplained pain have an altered neural pain perception process owing to decreased activation of empathetic-affective networks, which we interpret as a deficit in pain-related affective meaning construction. These findings may lead to a more specific and detailed neurobiological understanding of the clinical impression of disturbed affect in patients with chronic pain disorder.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".