Prefrontal consolidation supports the attainment of fear memory accuracy
Bibliographic record
Abstract
The neural mechanisms underlying the attainment of fear memory accuracy for appropriate discriminative responses to aversive and nonaversive stimuli are unclear. Considerable evidence indicates that coactivator of transcription and histone acetyltransferase cAMP response element binding protein (CREB) binding protein (CBP) is critically required for normal neural function. CBP hypofunction leads to severe psychopathological symptoms in human and cognitive abnormalities in genetic mutant mice with severity dependent on the neural locus and developmental time of the gene inactivation. Here, we showed that an acute hypofunction of CBP in the medial prefrontal cortex (mPFC) results in a disruption of fear memory accuracy in mice. In addition, interruption of CREB function in the mPFC also leads to a deficit in auditory discrimination of fearful stimuli. While mice with deficient CBP/CREB signaling in the mPFC maintain normal responses to aversive stimuli, they exhibit abnormal responses to similar but nonrelevant stimuli when compared to control animals. These data indicate that improvement of fear memory accuracy involves mPFC-dependent suppression of fear responses to nonrelevant stimuli. Evidence from a context discriminatory task and a newly developed task that depends on the ability to distinguish discrete auditory cues indicated that CBP-dependent neural signaling within the mPFC circuitry is an important component of the mechanism for disambiguating the meaning of fear signals with two opposing values: aversive and nonaversive.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".