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Record W2763834310 · doi:10.1038/s41598-017-13203-8

Subcortical Facilitation of Behavioral Responses to Threat

2017· article· en· W2763834310 on OpenAlexaff
Mark D. Vida, Marlene Behrmann

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsBaycrest Hospital
FundersNational Science Foundation
KeywordsFacilitationNeurosciencePsychologyMedicine

Abstract

fetched live from OpenAlex

Behavioral responses to threat are critical to survival. Several cortical and subcortical brain regions respond selectively to threat. However, the relation of these neural responses and their underlying representations to behavior is unclear. We examined the contribution of lower-order subcortical representations to behavioral responses to threat in adult humans. In Experiments 1 and 2, participants viewed pairs of images presented to the same eye or to different eyes. We observed a monocular advantage, which indicates subcortical facilitation, for ancestral threats (snakes, spiders), but not for modern threats, positive images, or neutral images. In Experiment 3, we presented pairs of snakes or neutral images into the temporal or nasal hemifield. For snakes only, we observed a temporal hemifield advantage, which indicates facilitation by the retino-tectal subcortical pathway. These results advance the current understanding of processing of threat by adult humans by revealing the characteristics of behaviors driven by a lower-order neural mechanism that is specialized for the processing of ancestral threats. The results also contribute to ongoing debates concerning the biological generality of neural mechanisms for processing of complex, emotionally-relevant stimuli by providing evidence for conservation of lower-order neural mechanisms for processing of ancestral threats across both ontogeny and phylogeny.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0050.000

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 head0.204
GPT teacher head0.405
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations15
Published2017
Admission routes1
Has abstractyes

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