Engram neurons: Encoding, consolidation, retrieval, and forgetting of memory
Bibliographic record
Abstract
Tremendous strides have been made in our understanding of the neurobiological substrates of memory - the so-called memory "engram". Here, we integrate recent progress in the engram field to illustrate how engram neurons transform across the "lifespan" of a memory - from initial memory encoding, to consolidation and retrieval, and ultimately to forgetting. To do so, we first describe how cell-intrinsic properties shape the initial emergence of the engram at memory encoding. Second, we highlight how these encoding neurons preferentially participate in synaptic- and systems-level consolidation of memory. Third, we describe how these changes during encoding and consolidation guide neural reactivation during retrieval, and facilitate memory recall. Fourth, we describe neurobiological mechanisms of forgetting, and how these mechanisms can counteract engram properties established during memory encoding, consolidation, and retrieval. Motivated by recent experimental results across these four sections, we conclude by proposing some conceptual extensions to the traditional view of the engram, including broadening the view of cell-type participation within engrams and across memory stages. In collection, our review synthesizes general principles of the engram across memory stages, and describes future avenues to further understand the dynamic engram.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Neuroscience review synthesizing engram mechanisms across memory encoding, consolidation, retrieval, and forgetting; the object is memory biology.
This review synthesizes neurobiological knowledge about memory engrams rather than studying research itself.
Neuroscience review of memory engram mechanisms; object is brain function, not research practice.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".