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Impairments to Consolidation, Reconsolidation, and Long-Term Memory Maintenance Lead to Memory Erasure

2020· review· en· W3008867147 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Neuroscience · 2020
Typereview
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsMcGill University
Fundersnot available
KeywordsMemory consolidationAmnesiaEngramRetrograde amnesiaLong-term memoryNeurosciencePsychologyMemory impairmentCognitive psychologyAnterograde amnesiaChildhood amnesiaConsolidation (business)Episodic memoryHippocampusChildhood memoryCognition

Abstract

fetched live from OpenAlex

An enduring problem in neuroscience is determining whether cases of amnesia result from eradication of the memory trace (storage impairment) or if the trace is present but inaccessible (retrieval impairment). The most direct approach to resolving this question is to quantify changes in the brain mechanisms of long-term memory (BM-LTM). This approach argues that if the amnesia is due to a retrieval failure, BM-LTM should remain at levels comparable to trained, unimpaired animals. Conversely, if memories are erased, BM-LTM should be reduced to resemble untrained levels. Here we review the use of BM-LTM in a number of studies that induced amnesia by targeting memory maintenance or reconsolidation. The literature strongly suggests that such amnesia is due to storage rather than retrieval impairments. We also describe the shortcomings of the purely behavioral protocol that purports to show recovery from amnesia as a method of understanding the nature of amnesia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.913
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.109
GPT teacher head0.389
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it