The history of <scp>long‐term</scp> potentiation as a memory mechanism: Controversies, confirmation, and some lessons to remember
Bibliographic record
Abstract
The discovery of long-term potentiation (LTP) provided the first, direct evidence for long-lasting synaptic plasticity in the living brain. Consequently, LTP was proposed to serve as a mechanism for information storage among neurons, thus providing the basis for the behavioral and psychological phenomena of learning and long-term memory formation. However, for several decades, the LTP-memory hypothesis remained highly controversial, with inconsistent and contradictory evidence providing a barrier to its general acceptance. This review summarizes the history of these early debates, challenges, and experimental strategies (successful and unsuccessful) to establish a link between LTP and memory. Together, the empirical evidence, gathered over a period of about four decades, strongly suggests that LTP serves as one of the mechanisms affording learning and memory storage in neuronal circuits. Notably, this body of work also offers some important lessons that apply to the broader fields of behavioral and cognitive neuroscience. As such, the history of LTP as a learning mechanism provides valuable insights to neuroscientists exploring the relations between brain and psychological states.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.003 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.009 |
| 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".