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Record W4414462549 · doi:10.1371/journal.pbio.3003391

Extinction and subsequent updating of innate fear responses to a visual looming stimulus rely on hippocampus-dependent mechanisms

2025· article· en· W4414462549 on OpenAlexaff
Livia Autore, Andrea Zamora, Antoine Harel, Zijun Wang, Armn A. Tavallaei, Stephen M. Winston, Clara Ortega‐de San Luis, James D. O’Leary, Mark A. Brimble, Gisella Vetere, Tomás J. Ryan

Bibliographic record

VenuePLoS Biology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsCanadian Institute for Advanced Research
FundersResearch IrelandAir Force Office of Scientific ResearchHORIZON EUROPE European Research CouncilTrinity College DublinIrish Research Council for Science, Engineering and Technology
KeywordsLoomingStimulus (psychology)EngramFear conditioningExtinction (optical mineralogy)Innate immune system

Abstract

fetched live from OpenAlex

Animals rely on innate and learned behavior to respond to their environment, but how the brain balances hardwired responses with adaptive flexibility remains unclear. Here, we demonstrate that innate looming stimulus responses in Mus musculus can be attenuated via repeated unreinforced presentation. This attenuation is long-lasting and generalizing, but is rapidly recovered when the stimulus is paired with an electric foot-shock. Fiber photometry recordings reveal attenuation of responses to visual looming stimuli in the SC and PAG, which do not recover following recovery of behavioral responses. Analysis of c-Fos expression uncovered a ventral CA1 (vCA1) ensemble that is active during both innate and learned looming fear responses. We report that this vCA1 engram is not necessary for innate defensive behavior but is necessary for learned fear responses. These findings reveal a novel role of the hippocampus in adapting to looming stimuli, and provide a platform for understanding the interaction of memory and instinct.

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 score0.007
Threshold uncertainty score0.552

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 head0.066
GPT teacher head0.340
Teacher spread0.275 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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