Current understanding of fear learning and memory in humans and animal models and the value of a linguistic approach for analyzing fear learning and memory in humans
Bibliographic record
Abstract
Fear is an emotion that serves as a driving factor in how organisms move through the world. In this review, we discuss the current understandings of the subjective experience of fear and the related biological processes involved in fear learning and memory. We first provide an overview of fear learning and memory in humans and animal models, encompassing the neurocircuitry and molecular mechanisms, the influence of genetic and environmental factors, and how fear learning paradigms have contributed to treatments for fear-related disorders, such as posttraumatic stress disorder. Current treatments as well as novel strategies, such as targeting the perisynaptic environment and use of virtual reality, are addressed. We review research on the subjective experience of fear and the role of autobiographical memory in fear-related disorders. We also discuss the gaps in our understanding of fear learning and memory, and the degree of consensus in the field. Lastly, the development of linguistic tools for assessments and treatment of fear learning and memory disorders is discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".