NMDA receptors regulate the firing rate set point of hippocampal circuits without altering single-cell dynamics
Bibliographic record
Abstract
Understanding how neuronal circuits stabilize their activity is a fundamental yet poorly understood aspect of neuroscience. Here, we show that hippocampal network properties, such as firing rate distribution and dimensionality, are actively regulated, despite perturbations and single-cell drift. Continuous inhibition of N-methyl-D-aspartate receptors (NMDARs) ex vivo lowers the excitation/inhibition ratio and network firing rates while preserving resilience to perturbations. This establishes a new network firing rate set point via NMDAR-eEF2K signaling pathway. NMDARs' capacity to modulate and stabilize network firing is mediated by excitatory synapses and the intrinsic excitability of parvalbumin-positive neurons, respectively. In behaving mice, continuous NMDAR blockade in CA1 reduces network firing without altering single-neuron drift or triggering a compensatory response. These findings expand NMDAR function beyond their canonical role in synaptic plasticity and raise the possibility that some NMDAR-dependent behavioral effects are mediated by their unique regulation of population activity set points.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".