Glutamate and Dysconnection in the Salience Network: Neurochemical, Effective-connectivity, and Computational Evidence in Schizophrenia
Bibliographic record
Abstract
Abstract In the dysconnection hypothesis, psychosis is caused by NMDA hypofunction resulting in aberrant network connectivity. Combining a cognitive-control task, functional magnetic resonance spectroscopy, and functional magnetic resonance imaging, we tested this hypothesis in the salience network of 20 first-episode psychosis (FEP) and 20 healthy control (HC) subjects. Across groups, glutamate concentration in the dorsal anterior cingulate cortex (dACC) was associated with higher and lower inhibitory connectivity in the dACC and in the anterior insula (AI) respectively. Crucially, glutamate concentration correlated negatively with the inhibitory influence on the excitatory neuronal population in the dACC of FEP subjects. Furthermore, aberrant computational parameters of the cognitive-control task performance were associated with aberrant inhibitory connections. Finally, the strength of connections from the dACC to the AI correlated negatively with severity of social withdrawal. These findings support a link between glutamate-mediated cortical disinhibition, deficits in effective connectivity, and computational performance in psychosis.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".