Basal glutamate in the hippocampus and the dorsolateral prefrontal cortex in schizophrenia: Relationships to cognitive proficiency investigated with structural equation modelling
Bibliographic record
Abstract
OBJECTIVES: Schizophrenia is characterised by deficits across multiple cognitive domains and altered glutamate related neuroplasticity. The purpose was to investigate whether glutamate deficits are related to cognition in schizophrenia, and whether glutamate-cognition relationships are different between schizophrenia and controls. METHODS: Magnetic resonance spectroscopy (MRS) at 3 Tesla was acquired from the dorsolateral prefrontal cortex (dlPFC) and hippocampus in 44 schizophrenia participants and 39 controls during passive viewing visual task. Cognitive performance (working memory, episodic memory, and processing speed) was assessed on a separate session. Group differences in neurochemistry and mediation/moderation effects using structural equation modelling (SEM) were investigated. RESULTS: < .0032). SEM-analyses demonstrated no mediation or moderation effects, however, an opposing dlPFC glutamate-processing speed association between groups was observed. CONCLUSIONS: Hippocampal glutamate deficits in schizophrenia participants are consistent with evidence of reduced neuropil density. Moreover, SEM analyses indicated that hippocampal glutamate deficits in schizophrenia participants as measured during a passive state were not driven by poorer cognitive ability. We suggest that functional MRS may provide a better framework for investigating glutamate-cognition relationships in schizophrenia.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".