Fear in the mind’s eye: the neural correlates of differential fear acquisition to imagined conditioned stimuli
Bibliographic record
Abstract
Mental imagery is involved in both the expression and treatment of fear-related disorders such as anxiety and post-traumatic stress disorder. However, the neural correlates associated with the acquisition and generalization of differential fear conditioning to imagined conditioned stimuli are relatively unknown. In this study, healthy human participants (n = 27) acquired differential fear conditioning to imagined conditioned stimuli paired with a physical unconditioned stimulus (i.e. mild shock), as measured via self-reported fear, the skin conductance response and significant right anterior insula (aIn) activation. Multivoxel pattern analysis cross-classification also demonstrated that the pattern of activity in the right aIn during imagery acquisition was quantifiably similar to the pattern produced by standard visual acquisition. Additionally, mental imagery was associated with significant differential fear generalization. Fear conditioning acquired to imagined stimuli generalized to viewing those same stimuli as measured with self-reported fear and right aIn activity, and likewise fear conditioning to visual stimuli was associated with significant generalized differential self-reported fear and right aIn activity when imagining those stimuli. Together, the study provides a novel understanding of the neural mechanisms associated with the acquisition of differential fear conditioning to imagined stimuli and that of the relationship between imagery and emotion more generally.
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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 | 0.000 |
| 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".