Functional Connectivity and Structural Signatures of the Visual Cortical System in Fibromyalgia: A Magnetic Resonance Imaging Study
Bibliographic record
Abstract
OBJECTIVE: Abnormal functional connectivity (FC) and structure in the brain are found in patients with fibromyalgia (FM). This study investigated FC and structural alterations of the visual cortical system, the emerging contributor to pain processing, in patients with FM. METHODS: Thirty pain-free participants and 26 patients with FM were enrolled. Clinical characteristics were evaluated using standardized scales. Structural and resting-state functional magnetic resonance imaging were conducted. Seed-based FC analyses, voxel-based morphometry, and surface-based morphometry were performed. The FC and cortical structure of the visual system were compared between the 2 groups. The correlation between functional and structural changes in the visual cortical system with clinical presentation in the FM group was analyzed. RESULTS: The patients with FM showed increased FCs within visual networks, of which the FC between the visual medial network and the right lingual gyrus (LG) was positively correlated with the Fibromyalgia Impact Questionnaire (FIQ) score. However, the FM group showed decreased FCs from the visual occipital network (VON) to several regions, of which the FCs from the VON to the bilateral frontal orbital cortices were negatively correlated with the FIQ and Pittsburgh Sleep Quality Index scores. Cortical thickness of the lateral occipital cortex, LG, and pericalcarine in FM tended to increase. CONCLUSION: Altered FCs and structure in the visual cortical system might be involved in the pathomechanisms and clinical presentation in FM. These findings could potentially support further studies that seek to find diagnostic methods and mechanism-based therapies in patients with FM.
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 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) | 0.001 | 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".