Pursuing synaptic plasticity from cortex to LTP in the hippocampus.
Bibliographic record
Abstract
Here I describe how an interest in synaptic plasticity took me from a PhD at McGill, where I worked on activity-dependent plasticity in the responses of single units in the association cortex of anesthetized cats, to a collaboration with Terje Lømo in Per Andersen's laboratory in Oslo in 1968-9. There we followed up on Lømo's discovery of LTP, published as an abstract in 1966, to produce the first detailed description of the phenomenon. Later, in London, Tony Gardner-Medwin and I showed that LTP lasting for days could be obtained in the awake rabbit. The two papers were published together in the Journal of Physiology in 1973. I relate how difficulties in replicating our results in English rabbits, and the failure of the first attempts to obtain LTP in slices of the dentate gyrus, led to my abandoning work on LTP for a few years, returning to the fray in the late 1970s through a collaboration with Graham Goddard at Dalhousie University in Halifax, Canada.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".