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Record W1987466351 · doi:10.1177/1754073912457208

Current Emotion Research in Behavioral Neuroscience: The Role(s) of the Amygdala

2012· article· en· W1987466351 on OpenAlexaff
Jorge L. Armony

Bibliographic record

VenueEmotion Review · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsMcGill UniversityInternational Laboratory for Brain, Music and Sound ResearchDouglas Mental Health University Institute
Fundersnot available
KeywordsAmygdalaPsychologyAngerAffective neuroscienceCognitive psychologyAffective scienceNeuroscienceEmotion classificationSocial psychologyCognition

Abstract

fetched live from OpenAlex

Substantial advances in our understanding of the neural bases of emotional processing have been made over the past decades. Overall, studies in humans and other animals highlight the key role of the amygdala in the detection and evaluation of stimuli with affective value. Nonetheless, contradictory findings have been reported, especially in terms of the exact role of this structure in the processing of different emotions, giving rise to different neural models of emotion. For instance, although the amygdala has traditionally been considered as exclusively involved in fear (and possibly anger), more recent work suggests that it may be important for processing other types of emotions, and even nonemotional information. A review of the main findings in this field is presented here, together with some of the hypotheses that have been put forward to interpret this literature and explain its inconsistencies.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.460
GPT teacher head0.522
Teacher spread0.062 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations43
Published2012
Admission routes1
Has abstractyes

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