NR2B subunit‐dependent long‐term potentiation enhancement in the rat cortical auditory system <i>in vivo</i> following masking of patterned auditory input by white noise exposure during early postnatal life
Bibliographic record
Abstract
The composition of N-methyl-D-aspartate (NMDA) receptor subunits influences the degree of synaptic plasticity expressed during development and into adulthood. Here, we show that theta-burst stimulation of the medial geniculate nucleus reliably induced NMDA receptor-dependent long-term potentiation (LTP) of field postsynaptic potentials recorded in the primary auditory cortex (A1) of urethane-anesthetized rats. Furthermore, substantially greater levels of LTP were elicited in juvenile animals (30-37 days old; approximately 55% maximal potentiation) than in adult animals (approximately 30% potentiation). Masking patterned sound via continuous white noise exposure during early postnatal life (from postnatal day 5 to postnatal day 50-60) resulted in enhanced, juvenile-like levels of LTP (approximately 70% maximal potentiation) relative to age-matched controls reared in unaltered acoustic environments (approximately 30%). Rats reared in white noise and then placed in unaltered acoustic environments for 40-50 days showed levels of LTP comparable to those of adult controls, indicating that white noise rearing results in a form of developmental arrest that can be overcome by subsequent patterned sound exposure. We explored the mechanisms mediating white noise-induced plasticity enhancements by local NR2B subunit antagonist application in A1. NR2B subunit antagonists (Ro 25-6981 or ifenprodil) completely reversed white noise-induced LTP enhancement at concentrations that did not affect LTP in adult or age-matched controls. We conclude that white noise exposure during early postnatal life results in the maintenance of juvenile-like, higher levels of plasticity in A1, an effect that appears to be critically dependent on NR2B subunit activation.
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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) | 0.001 | 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".