Interhemispheric Regulation of the Medial Prefrontal Cortical Glutamate Stress Response in Rats
Bibliographic record
Abstract
While stressors are known to increase medial prefrontal cortex (PFC) glutamate (GLU) levels, the mechanism(s) subserving this response remain to be elucidated. We used microdialysis and local drug applications to investigate, in male Long-Evans rats, whether the PFC GLU stress response might reflect increased interhemispheric communication by callosal projection neurons. We report here that tail-pinch stress (20 min) elicited comparable increases in GLU in the left and right PFC that were sodium and calcium dependent and insensitive to local glial cystine-GLU exchanger blockade. Unilateral ibotenate-induced PFC lesions abolished the GLU stress response in the opposite hemisphere, as did contralateral mGlu(2/3) receptor activation. Local dopamine (DA) D(1) receptor blockade in the left PFC potently enhanced the right PFC GLU stress response, whereas the same treatment applied to the right PFC had a much weaker effect on the left PFC GLU response. Finally, the PFC GLU stress response was attenuated and potentiated, respectively, following alpha(1)-adrenoreceptor blockade and GABA(B) receptor activation in the opposite hemisphere. These findings indicate that the PFC GLU stress response reflects, at least in part, activation of callosal neurons located in the opposite hemisphere and that stress-induced activation of these neurons is regulated by GLU-, DA-, norepinephrine-, and GABA-sensitive mechanisms. In the case of DA, this control is asymmetrical, with a marked regulatory bias of the left PFC DA input over the right PFC GLU stress response. Together, these findings suggest that callosal neurons and their afferentation play an important role in the hemispheric specialization of PFC-mediated responses to stressors.
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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) | 0.001 | 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 | 0.001 |
| 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".