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Record W2058797163 · doi:10.1155/2011/813749

Interplay of Amygdala and Cingulate Plasticity in Emotional Fear

2011· review· en· W2058797163 on OpenAlexafffund
Hiroki Toyoda, Xiang‐Yao Li, Long‐Jun Wu, Ming Zhao, Giannina Descalzi, Tao Chen, Kohei Koga, Min Zhuo

Bibliographic record

VenueNeural Plasticity · 2011
Typereview
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsAmygdalaNeuroscienceFear processing in the brainFear conditioningHippocampusPsychologySynaptic plasticityLong-term potentiationAnterior cingulate cortexPrefrontal cortexNeuroplasticityMedicineCognition

Abstract

fetched live from OpenAlex

The amygdala is known to be a critical brain region for emotional fear. It is believed that synaptic plasticity within the amygdala is the cellular basis of fear memory. Recent studies demonstrate that cortical areas such as the prefrontal cortex (PFC) and anterior cingulate cortex (ACC) may also contribute to the formation of fear memory, including trace fear memory and remote fear memory. At synaptic level, fear conditioning also triggers plastic changes within the cortical areas immediately after the condition. These results raise the possibility that certain forms of synaptic plasticity may occur within the cortex while synaptic potentiation takes place within synapses in the hippocampus and amygdala. This hypothesis is supported by electrophysiological evidence obtained from freely moving animals that neurons in the hippocampus/amygdala fire synchronous activities with cortical neurons during the learning. To study fear-related synaptic plasticity in the cortex and its functional connectivity with neurons in the amygdala and hippocampus will help us understand brain mechanisms of fear and improve clinical treatment of emotional disorders in patients.

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)0.000
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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.131
GPT teacher head0.352
Teacher spread0.220 · 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

Citations84
Published2011
Admission routes2
Has abstractyes

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