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Record W2524675301 · doi:10.7554/elife.17464

Hippocampal neurogenesis enhancers promote forgetting of remote fear memory after hippocampal reactivation by retrieval

2016· article· en· W2524675301 on OpenAlexaff
Rie Ishikawa, Hotaka Fukushima, Paul W. Frankland, Satoshi Kida

Bibliographic record

VenueeLife · 2016
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsHospital for Sick Children
FundersCore Research for Evolutional Science and TechnologyJapan Society for the Promotion of ScienceSumitomo FoundationTakeda Science Foundation
KeywordsNeurogenesisForgettingHippocampal formationMemory consolidationHippocampusNeuroscienceRecallFear conditioningExtinction (optical mineralogy)PsychologyContext (archaeology)Freezing behaviorCognitive psychologyAmygdalaBiology

Abstract

fetched live from OpenAlex

Forgetting of recent fear memory is promoted by treatment with memantine (MEM), which increases hippocampal neurogenesis. The approaches for treatment of post-traumatic stress disorder (PTSD) using rodent models have focused on the extinction and reconsolidation of recent, but not remote, memories. Here we show that, following prolonged re-exposure to the conditioning context, enhancers of hippocampal neurogenesis, including MEM, promote forgetting of remote contextual fear memory. However, these interventions are ineffective following shorter re-exposures. Importantly, we find that long, but not short re-exposures activate gene expression in the hippocampus and induce hippocampus-dependent reconsolidation of remote contextual fear memory. Furthermore, remote memory retrieval becomes hippocampus-dependent after the long-time recall, suggesting that remote fear memory returns to a hippocampus dependent state after the long-time recall, thereby allowing enhanced forgetting by increased hippocampal neurogenesis. Forgetting of traumatic memory may contribute to the development of PTSD treatment.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.034
GPT teacher head0.279
Teacher spread0.245 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations111
Published2016
Admission routes1
Has abstractyes

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