Systems consolidation and hippocampus: two views
Bibliographic record
Abstract
Two approaches to systems-level memory consolidation are contrasted. The standard model and multiple trace theory are spelled out, their implications are outlined, and their fit to the data from a number of approaches is evaluated. We conclude that the data from neuroimaging studies strongly support multiple trace theory, that data from neuropsychological studies favor but does not conclusively support multiple trace theory, while evidence from a new approach, the study of prospective memory, also supporting multiple trace theory, offers a promising new way to distinguish between these two theories. Work with animals is largely consistent with this conclusion. We suggest that the hippocampal and neocortical systems are critical for different forms of memory, and that the shift of memory from dependence on hippocampus to dependence on neocortex during consolidation is a reflection of the fact that memory often is transformed with time, becoming more generic in nature. Insofar as detailed episodic recollections are retained, the data show that they are dependent on the hippocampal system, much as multiple trace theory postulated.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.030 |
| Scholarly communication | 0.008 | 0.020 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".