Chronic stress modulation of prefrontal cortical NMDA receptor expression disrupts limbic structure-prefrontal cortex interaction
Bibliographic record
Abstract
Chronic stress causes various detrimental effects including cognitive and affective dysfunctions. Given the recent findings emphasizing the importance of information processing between the prefrontal cortex (PFC) and limbic structures on cognitive and affective functions, impairments of these functions caused by chronic stress may be associated with stress-induced adaptive and maladaptive responses in limbic structure-PFC interaction. In this study we have shown that chronic stress disrupts limbic structure-PFC interaction by modulating N-methyl-D-aspartate (NMDA) receptor expression in the PFC. We found that chronic stress decreased expression of NR1, NR2A and NR2B subunits of NMDA receptors in the PFC but not in the motor cortex. However, the reduction in NR2B subunits of NMDA receptors was larger in the dorsal part than the ventral part of PFC. In agreement with this observation, administration of the NMDA antagonist that was more selective for NMDA receptors containing NR2B subunits induced alterations of synchronous local field potentials between the PFC and limbic structures, synaptic plasticity induction in the limbic structure-PFC pathway, and spike firing of PFC neurons that were similar to those observed in the dorsal PFC of rats exposed to chronic stress. In contrast, administration of the NMDA antagonist that was not subunit-selective resulted in electrophysiological alterations resembling to those observed in the ventral PFC of rats exposed to chronic stress. These results suggest that chronic stress disrupts NMDA receptor-dependent limbic structure-PFC information processing.
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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) | 0.001 | 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".