Locus coeruleus in memory formation and Alzheimer's disease
Bibliographic record
Abstract
Catecholamine neurons of the locus coeruleus (LC) in the dorsal pontine tegmentum innervate the entire neuroaxis, with signaling actions implicated in the regulation of attention, arousal, sleep-wake cycle, learning, memory, anxiety, pain, mood, and brain metabolism. The co-release of norepinephrine (NE) and dopamine (DA) from LC terminals in the hippocampus plays a role in all stages of hippocampal-memory processing. This catecholaminergic regulation modulates the encoding, consolidation, retrieval, and reversal of hippocampus-based memory. LC neurons in awake animals have two distinct firing modes: tonic firing (explorative) and phasic firing (exploitative). These two firing modes exert different modulatory effects on post-synaptic dendritic spines. In the hippocampus, the firing modes regulate long-term potentiation (LTP) and long-term depression, which differentially regulate the mRNA expression and transcription of plasticity-related proteins (PRPs). These proteins aid in structural alterations of dendritic spines, that is, structural long-term potentiation (sLTP), via expansion and structural long-term depression (sLTD) via contraction of post-synaptic dendritic spines. Given the LC's role in all phases of memory processing, the degeneration of 50% of the LC neuron population occurring in Alzheimer's disease (AD) is a clinically relevant aspect of disease pathology. The loss of catecholaminergic regulation contributes to dysfunction in memory processes along with impaired functions associated with attention and task completion. The multifaceted role of the LC in memory and general task performance and the close correlation of LC degeneration with neurodegenerative disease progression together implicate it as a target for new clinical assessment tools.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".