Combination of Sub‐effective Doses of NMDA and D1 Dopamine Receptor Antagonists Impairs Executive Function in Rats
Bibliographic record
Abstract
Contemporary research in the pathophysiology of cognitive deficits in schizophrenia has provided a multifactorial view, in which the neurotransmitters dopamine, gamma aminobutyric acid (GABA) and glutamate are disturbed in the prefrontal cortex (PFC) of schizophrenic brains. This view is supported by the fact that current antipsychotic drugs, which are primarily dopamine receptor blockers, are not effective in treating the cognitive symptoms of schizophrenia. We hypothesized that abnormality in dopamine, GABA and glutamate neurotransmissions act synergistically to cause certain cognitive symptoms of schizophrenia. We tested the effect of blockade of all three neurotransmitter systems on executive function using an operant conditioning‐based attentional set‐shifting task to assess behavioral flexibility. In a series of dose‐response studies, we determined the effective doses of the specific antagonists for dopamine D1 receptors (SH‐23390), GABA‐A receptors (bicuculline methiodide) and NMDA receptors (MK‐801). Next, sub‐effective doses were administered subcutaneously 25 min before the set‐shifting task. Our results indicate that while the single antagonist treatments did not impair set‐shifting, combination of sub‐effective doses of SH‐23390 and MK‐801 severely affected performance. Present findings will help to elucidate mechanisms underlying cognitive deficits in schizophrenia. Acknowledgement: Supported by NSERC and the Dept. of Psychiatry, University of Western Ontario.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".