Perceiving Threat In the Face of Safety: Excitation and Inhibition of Conditioned Fear in Human Visual Cortex
Bibliographic record
Abstract
Previous findings have established that cortical sensory systems exhibit experience-dependent biases toward stimuli consistently associated with threat. It remains unclear whether safety cues also facilitate perceptual engagement or how competition between learned threat and safety cues is resolved within visual cortex. Here, we used classical discrimination conditioning with simple luminance modulated visual stimuli that predicted the presence or absence of an aversive sound to examine visuocortical competition between features signaling threat versus safety. We tracked steady-state visual evoked potentials to label distinct visual cortical responses in humans to conditioned and control stimuli. Trial-by-trial expectancy ratings collected online confirmed that participants discriminated between threat and safety cues. Conditioning was associated with heightened activation of the extended visual cortex in response to the threat, but not the safety, stimulus. Cortical facilitation for the threatening stimulus was selective and not decreased by simultaneously presenting safe and associatively novel cues. Our findings shed light on the sensory brain dynamics associated with experience-dependent acquisition of perceptual biases for danger and safety signals.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".