Long-term potentiation in the hippocampus: From magnesium to memory
Bibliographic record
Abstract
Long-term potentiation (LTP) is a widely studied phenomenon since the underlying molecular mechanisms are widely believed to be critical for learning and memory and their dysregulation has been implicated in many brain disorders affecting cognitive functions. Central to the induction of LTP, in most pathways that have been studied in the mammalian CNS, is the N-methyl-D-aspartate receptor (NMDAR). Philippe Ascher discovered that the NMDAR is subject to a rapid, highly voltage-dependent block by Mg 2+ . Here I describe how my own work on NMDARs has been so profoundly influenced by this seminal discovery. This personal reflection describes how the voltage-dependent Mg 2+ block of NMDARs was a crucial component of the understanding of the molecular mechanisms responsible for the induction of LTP. It explains how this unusual molecular mechanism underlies the Hebbian nature of synaptic plasticity and the hallmark features of NMDAR-LTP (input specificity, cooperativity and associativity). Then the role of the Mg 2+ block of NMDARs is discussed in the context of memory and dementia. In particular, the idea that alterations in the voltage-dependent block of the NMDAR is a component of cognitive decline during normal ageing and neurodegenerative disorders, such as Alzheimer's disease, is discussed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".