MétaCan
Menu
Back to cohort
Record W4385879793 · doi:10.1016/j.celrep.2023.112999

Adaptive expression of engrams by retroactive interference

2023· article· en· W4385879793 on OpenAlexafffund
Livia Autore, James D. O’Leary, Clara Ortega‐de San Luis, Tomás J. Ryan

Bibliographic record

VenueCell Reports · 2023
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsTrinity CollegeCanadian Institute for Advanced Research
FundersH2020 European Research CouncilIrish Research CouncilScience Foundation IrelandEuropean Research CouncilCanadian Institute for Advanced Research
KeywordsEngramForgettingRecallOptogeneticsNeurosciencePsychologyExpression (computer science)Computer scienceCognitive psychology

Abstract

fetched live from OpenAlex

Long-term memories are stored as configurations of neuronal ensembles, termed engrams. Although investigation of engram cell properties and functionality in memory recall has been extensive, less is known about how engram cells are affected by forgetting. We describe a form of interference-based forgetting using an object memory behavioral paradigm. By using activity-dependent cell labeling, we show that although retroactive interference results in decreased engram cell reactivation during recall trials, optogenetic stimulation of the labeled engram cells is sufficient to induce memory retrieval. Forgotten engrams may be reinstated via the presentation of similar or related environmental information. Furthermore, we demonstrate that engram activity is necessary for interference to occur. Taken together, these findings indicate that retroactive interference modules engram expression in a manner that is both reversible and updatable. Inference may constitute a form of adaptive forgetting where, in everyday life, new perceptual and environmental inputs modulate the natural forgetting process.

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)0.000
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 score0.008
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.087
GPT teacher head0.293
Teacher spread0.206 · 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

Citations34
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueCell ReportsSame topicMemory and Neural MechanismsFrench-language works237,207