β-Adrenergic receptor signaling and modulation of long-term potentiation in the mammalian hippocampus
Bibliographic record
Abstract
Encoding new information in the brain requires changes in synaptic strength. Neuromodulatory transmitters can facilitate synaptic plasticity by modifying the actions and expression of specific signaling cascades, transmitter receptors and their associated signaling complexes, genes, and effector proteins. One critical neuromodulator in the mammalian brain is norepinephrine (NE), which regulates multiple brain functions such as attention, perception, arousal, sleep, learning, and memory. The mammalian hippocampus receives noradrenergic innervation and hippocampal neurons express β-adrenergic receptors, which are known to play important roles in gating the induction of long-lasting forms of synaptic potentiation. These forms of long-term potentiation (LTP) are believed to importantly contribute to long-term storage of spatial and contextual memories in the brain. In this review, we highlight the contributions of noradrenergic signaling in general and β-adrenergic receptors in particular, toward modulating hippocampal LTP. We focus on the roles of NE and β-adrenergic receptors in altering the efficacies of specific signaling molecules such as NMDA and AMPA receptors, protein phosphatases, and translation initiation factors. Also, the roles of β-adrenergic receptors in regulating synaptic "tagging" and "capture" of LTP within synaptic networks of the hippocampus are reviewed. Understanding the molecular and cellular bases of noradrenergic signaling will enrich our grasp of how the brain makes new, enduring memories, and may shed light on credible strategies for improving mental health through treatment of specific disorders linked to perturbed memory processing and dysfunctional noradrenergic synaptic transmission.
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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) | 0.000 | 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 | 0.001 |
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".