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Record W4410554328 · doi:10.1055/s-0045-1808136

Neural correlates of lumbar tactile acuity in patients with non-specific low back pain and healthy controls – an MRI study

2025· article· en· W4410554328 on OpenAlexaff
L Butry, Daniel L. Belavý, Rebekka Döding, Katja Ehrenbrusthoff, Bernadette M. Fitzgibbon, Frederic Junker, Christopher J Miller, J Van Oossterwijck, Patrick J. Owen, Tobias L. Schulte, Scott D. Tagliaferri, Martin Tegenthoff, Guy Trudel, S. Vickery, Elena Enax‐Krumova, Lara Schlaffke

Bibliographic record

Venuephysioscience · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsLumbarMedicineBack painLow back painPhysical medicine and rehabilitationNeural correlates of consciousnessPhysical therapyRadiologyPathology

Abstract

fetched live from OpenAlex

Background Tactile acuity is defined as the skin’s ability to discriminate spatial patterns of stimulation. The two-point discrimination (TPD) threshold is commonly used to assess tactile acuity in non-specific low back pain (nsLBP) [ 1 ]. Another approach, the two-point estimation (TPE) task [ 2 ], is more time-efficient and, therefore potentially suitable for clinical use. The TPD is closely linked to functional and structural reorganisation in the primary somatosensory cortices (S1) [ 3 ] [ 4 ], yet studies on neural correlates of TPE are lacking. This study aims to identify potential associations between outcomes of lumbar TPE and TPD and resting-state functional connectivity (rsFC) and structural connectivity (SC) of the S1 region. Methods Preliminary data from the ongoing cross-sectional ‘PREDICT-LBP’ (PRedictive Evidence Driven Intelligent Classification Tool for Low Back Pain) study [ 5 ] are analysed. Whole-brain resting-state functional MRI (voxel size: 3mm isotropic; TE: 30; TR: 2500; acquisition time: 8:12min) and diffusion-weighted MRI (voxel size: 2mm isotropic, TE: 90; TR: 10000; 105 directions in 3 shells, b: 1000/1800/2500) are acquired with a 3T Philips Achieva MR system, providing rsFC and SC, respectively. MRI data processing is performed according to literature standards [ 6 ] [ 7 ]. To obtain SC, the deterministic tractography algorithm ‘SD_Stream’ from MRtrix3 [ 8 ] is performed to reconstruct white matter streamlines. To parcellate the brain into subregions, we use the ‘Brainnetome’ atlas [ 9 ] for both SC and rsFC. The lumbar TPD and TPE are measured at spinal level L4 with a digital calliper according to established protocols [ 2 ] [ 10 ]. The correlation of both SC and rsFC of the S1 region and the measures of tactile acuity are investigated using FDR-corrected univariate testing. Results We have currently (August 2023 – June 2024) acquired data from 155 participants (111 with nsLBP and 44 healthy controls). Visual quality control and processing of MRI data is ongoing and preliminary results will be presented at FSPT 2024. We hypothesize similar findings in neural correlates of TPE and TPD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.006
GPT teacher head0.270
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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