Differential Fear Conditioning Induces Reciprocal Changes in the Sensory Responses of Lateral Amygdala Neurons to the CS<sup>+</sup> and CS<sup>−</sup>
Bibliographic record
Abstract
In classical fear conditioning, a neutral sensory stimulus (CS) acquires the ability to elicit fear responses after pairing to a noxious unconditioned stimulus (US). As amygdala lesions prevent the acquisition of fear responses and the lateral amygdaloid (LA) nucleus is the main input station of the amygdala for auditory afferents, the effect of auditory fear conditioning on the sensory responsiveness of LA neurons has been examined. Although conditioning was shown to increase CS-evoked LA responses, the specificity of the changes in responsiveness was not tested. Because conditioning might induce nonspecific increases in LA responses to auditory afferents, we re-examined this issue in conscious, head-restrained cats using a differential conditioning paradigm where only one of two tones (CS(+) but not CS(-)) was paired to the US. Differential conditioning increased unit and field responses to the CS(+), whereas responses to the CS(-) decreased. Such changes have never been observed in the amygdala except in cases where the CS(-) had been paired to the US before and fear responses not extinguished. This suggests that fear conditioning is not only accompanied by potentiation of amygdalopetal pathways conveying the CS(+) but also by the depression of sensory inputs unpaired to noxious stimuli.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".