Upregulation of cortical GABAA receptor concentration in fibromyalgia
Bibliographic record
Abstract
An imbalance between excitatory and inhibitory neurotransmission has been linked to fibromyalgia (FM). Magnetic resonance spectroscopy has shown increased levels of glutamate in the insula and posterior cingulate cortex in FM as well as reduced insular levels of gamma-aminobutyric acid (GABA). Both of these changes have been associated with increased pain sensitivity. However, it is not clear whether excitatory and/or inhibitory neurotransmission is altered across the brain. Therefore, the aim of this study was to quantify GABAA receptor concentration on the whole brain level in FM to investigate a potential dysregulation of the GABAergic system. Fifty-one postmenopausal women (26 FM, 25 matched controls) underwent assessments of pain sensitivity, attention and memory, psychological status and function, as well as positron emission tomography imaging using a tracer for GABAA receptors, [F]flumazenil. Patients showed increased pain sensitivity, impaired immediate memory, and increased cortical GABAA receptor concentration in the attention and default-mode networks. No decrease of GABAA receptor concentration was observed. Across the 2 groups, GABAA receptor concentration correlated positively with functional scores and current pain in areas overlapping with regions of increased GABAA receptor concentration. This study shows increased GABAA receptor concentration in FM, associated with pain symptoms and impaired function. The changes were widespread and not restricted to pain-processing regions. These findings suggest that the GABAergic system is altered, possibly indicating an imbalance between excitatory and inhibitory neurotransmission. Future studies should try to understand the nature of the dysregulation of the GABAergic system in FM and in other pain syndromes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".