The Human Dimension: How the Prefrontal Cortex Modulates the Subcortical Fear Response
Bibliographic record
Abstract
Numerous studies suggest that the amygdala is critical for the acquisition and expression of fear. Conditioned fear in animals has been considered a good model for human anxiety disorders, but animal models of anxiety have several limitations. Conditioned fear in animals can be directed to a specific stressor and is easily extinguished. Furthermore, animals do not seem to be able to develop the capacity to worry excessively about the future. While animal models are useful and can demonstrate psychiatric illnesses, they do not completely mimic the complex cognitive processes that occur in anxious humans. Thus, we hypothesize that human anxiety disorders are caused at least in part by differential activity in the prefrontal cortex, the brain region that most separates us from our nearest genetic neighbors. The human prefrontal cortex has not only been shown to be more developed than that of other mammals, but it also has unique morphology and gene expression. Neuroimaging studies repeatedly show abnormalities in the prefrontal cortex in anxious individuals. Thus, we suggest that the very same cortical complexity that allows us to produce a vibrant culture is also the seat of anxiety disorders. Interestingly, preclinical studies have shown that the prefrontal cortex inhibits the amygdala. There appears to be a distinction between two classes of anxiety disorders. Those disorders involving intense fear and panic--panic disorder, post-traumatic stress disorder, and phobias--seem to be characterized by an underactivity of the prefrontal cortex, thus disinhibiting the amygdala. Disorders such as generalized anxiety disorder and obsessive-compulsive disorder, which involve worry and rumination, on the other hand, seem to be characterized by an overactivity of the prefrontal cortex. Studies of prefrontal cortical function in psychiatric illness should be a fruitful method for identifying effective treatment approaches.
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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) | 0.004 | 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".