Glucocorticoid receptors in the prefrontal cortex regulate dopamine efflux to stress via descending glutamatergic feedback to the ventral tegmental area
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Enhanced dopamine (DA) efflux in the medial prefrontal cortex (mPFC) is a well-documented response to acute stress. We have previously shown that glucocorticoid receptors in the mPFC regulate stress-evoked DA efflux but the underlying mechanism is unknown. DA neurons in the ventral tegmental area (VTA) receive excitatory input from and send reciprocal projections to the mPFC. We hypothesize that blockade of prefrontal glucocorticoid receptors can reduce activity of descending glutamatergic input to the VTA, thereby attenuating stress-evoked DA efflux in the mPFC. Using in vivo microdialysis, we demonstrate that acute tail-pinch stress leads to a significant increase in glutamate efflux in the VTA. Blockade of prefrontal glucocorticoid receptors with the selective antagonist CORT 108297 attenuates stress-evoked glutamate efflux in the VTA together with DA efflux in the mPFC. Furthermore, blockade of ionotrophic glutamate receptors in the VTA attenuates stress-evoked DA efflux in the mPFC. We also examine the possible role of glucocorticoid-induced synthesis and release of endocannabinoids acting presynaptically via cannabinoid CB1 receptors to inhibit GABA release onto prefrontal pyramidal cells, thus enhancing descending glutamatergic input to the VTA leading to an increase in mPFC DA efflux during stress. However, administration of the cannabinoid CB1 receptor antagonist into the mPFC does not attenuate stress-evoked DA efflux in the mPFC. Taken together, our data indicate that glucocorticoids act locally within the mPFC to modulate mesocortical DA efflux by potentiation of glutamatergic drive onto DA neurons in the VTA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 | 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 it