Elevated corticosterone after fear learning impairs remote auditory memory retrieval and alters brain network connectivity
Bibliographic record
Abstract
Glucocorticoids are potent memory modulators that can modify behavior in an adaptive or maladaptive manner. Elevated glucocorticoid levels after learning promote memory consolidation at recent time points, but their effects on remote time points are not well established. Here we set out to assess whether corticosterone (CORT) given after learning modifies remote fear memory. To that end, mice were exposed to a mild auditory fear conditioning paradigm followed by a single 2 mg/kg CORT injection, and after 28 d, auditory memory was assessed. Neuronal activation was investigated using immunohistochemistry for the immediate early gene c - Fos , and coactivation of brain regions was determined using a correlation matrix analysis. CORT-treated mice displayed significantly less remote auditory memory retrieval. While the net activity of studied brain regions was similar compared with the control condition, CORT-induced remote memory impairment was associated with altered correlated activity between brain regions. Specifically, connectivity of the lateral amygdala with the basal amygdala and the dorsal dentate gyrus was significantly reduced in CORT-treated mice, suggesting disrupted network connectivity that may underlie diminished remote memory retrieval. Elucidating the pathways underlying these effects could help provide mechanistic insight into the effects of stress on memory and possibly provide therapeutic targets for psychopathology.
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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 | 0.000 | 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".