Eye-blink conditioning is associated with changes in synaptic ultrastructure in the rabbit interpositus nuclei
Bibliographic record
Abstract
Eye-blink conditioning involves the pairing of a conditioned stimulus (usually a tone) to an unconditioned stimulus (air puff), and it is well established that an intact cerebellum and interpositus nucleus, in particular, are required for this form of classical conditioning. Changes in synaptic number or structure have long been proposed as a mechanism that may underlie learning and memory, but localizing these changes has been difficult. Thus, the current experiment took advantage of the large amount of research conducted on the neural circuitry that supports eye-blink conditioning by examining synaptic changes in the rabbit interpositus nucleus. Synaptic quantifications included total number of synapses per neuron, numbers of excitatory versus inhibitory synapses, synaptic curvature, synaptic perforations, and the maximum length of the synapses. No overall changes in synaptic number, shape, or perforations were observed. There was, however, a significant increase in the length of excitatory synapses in the conditioned animals. This increase in synaptic length was particularly evident in the concave-shaped synapses. These results, together with previous findings, begin to describe a sequence of synaptic change in the interpositus nuclei following eye-blink conditioning that would appear to begin with structural change and end with an increase in synaptic number.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".