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Record W295262342 · doi:10.3758/bf03330630

Amygdala lesions impair context aversions but not the ability of contexts to serve as occasion setters

2000· article· en· W295262342 on OpenAlexaff
Darlene M. Skinner, Hance Clarke, Derek van der Kooy

Bibliographic record

VenuePsychobiology · 2000
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAmygdalaPsychologyContext (archaeology)Basolateral amygdalaNeuroscienceSaccharinClassical conditioningConditioningEndocrinologyMedicineBiology

Abstract

fetched live from OpenAlex

Rats with large amygdala lesions (Experiment 1) were compared with sham controls on a conditional discrimination task that allowed assessment of occasion-setting learning. A saccharin solution was paired with lithium chloride in one context, but with saline in a second context. All the groups learned to suppress fluid consumption in the first, relative to the second, context. Sham lesioned rats, but not amygdala-lesioned rats, also showed a large aversion to the first context on a choice test. Shamlesioned Pavlovian control groups, given direct pairings of Context 1 with lithium chloride and of Context 2 with saline, showed large aversions to Context 1, whereas similarly trained amygdala-lesioned rats did not avoid the context associated with lithium chloride. Rats with discrete lesions of either the central nucleus or the basolateral nucleus (Experiment 2) of the amygdala were not impaired on the conditional discrimination task but did show deficits on the place choice test. The data from amygdala-lesioned rats in the present study support previous behavioral data in suggesting that the aversive properties of contextual cues, as acquired through Pavlovian conditioning, are neither necessary nor sufficient for occasion-setting learning.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.014
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.073
GPT teacher head0.338
Teacher spread0.265 · 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; both teacher heads agree on what is shown here.

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

Citations6
Published2000
Admission routes1
Has abstractyes

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