Lumbar tactile acuity associated with S1-thalamic functional connectivity and S1 microstructure in patients with low back pain and pain-free controls
Bibliographic record
Abstract
ABSTRACT: Impairments in lumbar sensory perception, including reduced tactile acuity, occur in patients with nonspecific low back pain (LBP). Tactile acuity is linked to primary somatosensory cortex (S1) activity and structure, but neural markers of lumbar-specific tactile acuity tests remain unvalidated. This cross-sectional study investigated associations between lumbar two-point discrimination (TPD) and estimation (TPE) with functional and structural properties of S1, as well as S1-thalamic connectivity. Resting-state functional MRI and diffusion-weighted MRI assessed S1-thalamic functional connectivity (FC) and structural connectivity, as well as regional homogeneity (ReHo) and mean diffusivity (MD) of S1 grey matter in 78 LBP patients and 39 pain-free controls. Participants with LBP were subdivided into 2 groups: 1 with pain (LBP+, n = 39) and 1 without pain (LBP-, n = 39) on the day of assessment. Higher TPD (ie, worse tactile acuity) was associated with higher contralateral S1-thalamic FC (β = 19.97 mm, 95% CI = 8.47-31.46 mm) and lower contralateral S1-MD (β = -76.98 mm, 95% CI = -142.83 to -11.13 mm). Higher TPE was associated with higher S1-ReHo (β = 19.67 mm, 95% CI = 0.35-39 mm). Two-point discrimination and two-point estimation were positively correlated (r = 0.25, P < 0.001). No between-group differences were found for the MRI variables or TPE, but the LBP+ group showed higher TPD thresholds than pain-free controls (MDiff. = 6.05 mm, Padj . = 0.023). Our findings question the validity of TPE as a measure of tactile acuity. Both neural markers of TPD may not explain tactile acuity impairments in LBP but instead reflect a baseline indicator of tactile performance capability, suggesting poor validity as an LBP-specific marker of neuroplasticity.
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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) | 0.003 | 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".