Upregulation of CREB-Mediated Transcription Enhances Both Short- and Long-Term Memory
Bibliographic record
Abstract
Unraveling the mechanisms by which the molecular manipulation of genes of interest enhances cognitive function is important to establish genetic therapies for cognitive disorders. Although CREB is thought to positively regulate formation of long-term memory (LTM), gain-of-function effects of CREB remain poorly understood, especially at the behavioral level. To address this, we generated four lines of transgenic mice expressing dominant active CREB mutants (CREB-Y134F or CREB-DIEDML) in the forebrain that exhibited moderate upregulation of CREB activity. These transgenic lines improved not only LTM but also long-lasting long-term potentiation in the CA1 area in the hippocampus. However, we also observed enhanced short-term memory (STM) in contextual fear-conditioning and social recognition tasks. Enhanced LTM and STM could be dissociated behaviorally in these four lines of transgenic mice, suggesting that the underlying mechanism for enhanced STM and LTM are distinct. LTM enhancement seems to be attributable to the improvement of memory consolidation by the upregulation of CREB transcriptional activity, whereas higher basal levels of BDNF, a CREB target gene, predicted enhanced shorter-term memory. The importance of BDNF in STM was verified by microinfusing BDNF or BDNF inhibitors into the hippocampus of wild-type or transgenic mice. Additionally, increasing BDNF further enhanced LTM in one of the lines of transgenic mice that displayed a normal BDNF level but enhanced LTM, suggesting that upregulation of BDNF and CREB activity cooperatively enhances LTM formation. Our findings suggest that CREB positively regulates memory consolidation and affects memory performance by regulating BDNF expression.
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.
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".