Defective place cell activity in nociceptin receptor knockout mice with elevated NMDA receptor‐dependent long‐term potentiation
Bibliographic record
Abstract
There is growing evidence that NMDA receptor-dependent long-term potentiation (LTP) in the hippocampus mediates the synaptic plasticity that underlies spatial learning and memory. LTP deficiencies correlate well with spatial memory deficits and LTP enhancements may improve spatial memory. In addition, LTP deficiencies are associated with abnormal place cells as expected from the spatial mapping hypothesis of hippocampal function. In contrast, nothing is known on how enhanced NMDA receptor-dependent LTP affects place cells. To address this question we recorded place cells from mice lacking the nociceptin receptor (NOP1/ORL1/OP4) that have enhanced hippocampal LTP. We found that the enhanced LTP was mediated by NMDA receptors, did not require L-type calcium channels, and occurred only when high frequency tetanizing stimulus trains were used. Place cells in nociceptin receptor knockout mice were abnormal in several ways: they were less stable, had noisier positional firing patterns, larger firing fields and higher discharge rates inside and outside the firing fields. Our results suggest that excessive LTP can cause subnormal hippocampal place cell function. The effects of LTP enhancement on place cell function may therefore also depend on molecular details of synaptic plasticity, including the relationship between stimulus frequency and synaptic strength, and not merely on the magnitude of synaptic strength increases. The data have important clinical implications on development of strategies to improve cognitive function.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".