Impact of glutamate levels on neuronal response and cognitive abilities in schizophrenia
Bibliographic record
Abstract
Schizophrenia is characterized by impaired cognitive functioning, and brain regions involved in cognitive control processes show marked glutamatergic abnormalities. However, it is presently unclear whether aberrant neuronal response is directly related to the observed deficits at the metabolite level in schizophrenia. Here, 17 medicated schizophrenia patients and 17 matched healthy participants underwent functional magnetic resonance imaging (fMRI) when performing an auditory cognitive control task, as well as proton magnetic resonance spectroscopy ((1)H-MRS) in order to assess resting-state glutamate in the anterior cingulate cortex. The combined fMRI-(1)H-MRS analysis revealed that glutamate differentially predicted cortical blood-oxygen level-dependent (BOLD) response in patients and controls. While we found a positive correlation between glutamate and BOLD response bilaterally in the inferior parietal lobes in the patients, the corresponding correlation was negative in the healthy control participants. Further, glutamate levels predicted task performance in patients, such that lower glutamate levels were related to impaired cognitive control functioning. This was not seen for the healthy controls. These findings suggest that schizophrenia patients have a glutamate-related dysregulation of the brain network supporting cognitive control functioning. This could be targeted in future research on glutamatergic treatment of cognitive symptoms in schizophrenia.
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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 | 0.000 | 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) | 0.001 | 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".