Sustained <i>N</i>‐methyl‐<scp>d</scp>‐aspartate receptor hypofunction remodels the dopamine system and impairs phasic signaling
Bibliographic record
Abstract
Chronic N-methyl-d-aspartate receptor (NMDAR) hypofunction has been proposed as a contributing factor to symptoms of schizophrenia. However, it is unclear how sustained NMDAR hypofunction throughout development affects other neurotransmitter systems that have been implicated in the disease. Dopamine neuron biochemistry and activity were examined to determine whether sustained NMDAR hypofunction causes a state of hyperdopaminergia. We report that a global, genetic reduction in NMDARs led to a remodeling of dopamine neurons, substantially affecting two key regulators of dopamine homeostasis, i.e., tyrosine hydroxylase and the dopamine transporter. In NR1 knockdown mice, dopamine synthesis and release were attenuated, and dopamine clearance was increased. Although these changes would have the effect of reducing dopamine transmission, we demonstrated that a state of hyperdopaminergia existed in these mice because dopamine D2 autoreceptors were desensitized. In support of this conclusion, NR1 knockdown dopamine neurons have higher tonic firing rates. Although the tonic firing rates are higher, phasic signaling is impaired, and dopamine overflow cannot be achieved with exogenous high-frequency stimulation that models phasic firing. Through the examination of several parameters of dopamine neurotransmission, we provide evidence that chronic NMDAR hypofunction leads to a state of elevated synaptic dopamine. Compensatory mechanisms to attenuate hyperdopaminergia also impact the ability to generate dopamine surges through phasic firing.
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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 | 0.000 | 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 | 0.001 |
| 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".