Conscious expectancy rather than associative strength elicits brain activity during single-cue fear conditioning
Bibliographic record
Abstract
The neurocognitive processes underlying Pavlovian conditioning in humans are still largely debated. The conventional view is that conditioned responses (CRs) emerge automatically as a function of the contingencies between a conditioned stimulus (CS) and an unconditioned stimulus (US). As such, the associative strength model asserts that the frequency or amplitude of CRs reflects the strength of the CS-US associations. Alternatively, the expectation model asserts that the presentation of the CS triggers conscious expectancy of the US, which is responsible for the production of CRs. The present study tested the hypothesis that there are dissociable brain networks related to the expectancy and associative strength theories using a single-cue fear conditioning paradigm with a pseudo-random intermittent reinforcement schedule during functional magnetic resonance imaging. Participants' (n = 21) trial-by-trial expectations of receiving shock displayed a significant linear effect consistent with the expectation model. We also found a positive linear relationship between the expectancy model and activity in frontoparietal brain areas including the dorsolateral prefrontal cortex (PFC) and dorsomedial PFC. While an exploratory analysis found a linear relationship consistent with the associated strength model in the insula and early visual cortex, our primary results are consistent with the view that conscious expectancy contributes to CRs.
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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".