Induction- and conditioning-protocol dependent involvement of NR2B-containing NMDA receptors in synaptic potentiation and contextual fear memory in the hippocampal CA1 region of rats
Bibliographic record
Abstract
Long-term potentiation (LTP) in the hippocampal CA1 region requires the activation of N-methyl-D-aspartate receptors (NMDARs). Studies using genetic and pharmacological approaches have reported inconsistent results of the requirement of NR2B-containing NMDARs in LTP in the CA1 region. Pharmacological studies showed that NR2B-containing NMDARs are not required for LTP, while genetic studies reported that over-expression of NR2B-NMDARs enhances LTP and hippocampus-dependent memory. Here, we provide evidence showing that the functional role of NR2B-NMDARs in hippocampal LTP and memory depends on LTP-inducing and behavior-conditioning protocols. Inhibition of NR2B-NMDARs with the NR2B selective antagonist ifenprodil or Ro25-6981 suppressed LTP induced by spike-timing protocol, with no impact on LTP induced by pairing protocol or two-train high-frequency stimulation (HFS) protocol. Inhibition of NR2B-NMDARs did not affect the late phase LTP induced by four-train HFS. Ca²(+) imaging showed that there was difference in kinetics of intracellular Ca²(+) signals induced by spiking-timing and pairing protocols. Pre-training intra-CA1 infusion of ifenprodil or Ro25-6981 impaired the contextual fear memory induced by five CS-US pairings, with no effect on the memory induced by one CS-US pairing.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".