Induction of long‐term depression is associated with decreased dendritic length and spine density in layers III and V of sensorimotor neocortex
Bibliographic record
Abstract
Long-term potentiation (LTP) and long-term depression (LTD) are currently the most widely investigated models of the synaptic mechanisms underlying learning and memory. Previous research has shown that induction of LTP increases measures of pyramidal cell dendritic morphology in the hippocampus and layers III and V of the neocortex. However, to date there are no reports on the direct effects of LTD induction on dendritic morphology. Here, we investigated the effects of LTD induction on sensorimotor pyramidal cell dendritic morphology. Rats carried a stimulating electrode in the corpus callosum (midline) and a recording electrode in the right sensorimotor cortex. Each rat received low-frequency stimulation composed of 900 pulses at 1 Hz or handling daily for a total 15 days. Evoked potentials (EPs) of the transcallosal pathway were recorded in the right hemisphere before and after the 15 days of stimulation or handling. The rats were then perfused with saline and the brains were immediately processed for Golgi-Cox staining. Our results show that LTD induction is related to decreases in dendritic length and spine density both in layers III and V as well as a decrease in dendritic branch complexity in layer V of the sensorimotor cortex. Thus, neuronal alterations following modifications in neocortical synaptic efficacy may provide a general mechanism for the physical instantiation of learning and memory.
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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".