Altered hippocampal GABA and glutamate levels and uncoupling from functional connectivity in multiple sclerosis
Bibliographic record
Abstract
There is growing evidence for dysfunctional glutamatergic excitation and/or gamma-aminobutyric acid (GABA)ergic inhibition in patients with multiple sclerosis (MS). Cognitive impairment may occur during the early stages of MS and hippocampal abnormalities have been suggested as biomarkers. However, researchers have not clearly determined whether changes in hippocampal GABA and glutamate (Glu) levels are associated with cognitive impairment and aberrant neural activity in patients with MS. We used magnetic resonance spectroscopy to measure GABA+ and Glu levels in the left hippocampal region of 29 patients with relapsing-remitting MS and 29 healthy controls (HCs). Resting-state functional connectivity (FC) with the hippocampus was also examined. Compared to HCs, patients exhibited significantly lower GABA+ and Glu levels, which were associated with verbal and visuospatial memory deficits, respectively. Patients also showed decreased FC strengths between the hippocampus and several cortical regions, which are located within the default mode network. Moreover, hippocampal GABA+ levels and Glu/GABA+ ratios correlated with the FC strengths in HCs but not in patients with MS. This study describes a novel method for investigating the complex relationships among excitatory/inhibitory neurotransmitters, brain connectivity and cognition in health and disease. Strategies that modulate Glu and GABA neurotransmission may represent new therapeutic treatments for patients with MS.
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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 | 0.000 |
| 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".