Neurocircuitry and Neuroanatomy in Panic Disorder: A Systematic Review
Bibliographic record
Abstract
Background: This review updates our understanding of the neuroanatomical and neurocircuitry factors involved in panic disorder (PD). Many aspects remain undetermined. Methods: Clinical studies and a randomized controlled trial were identified via PubMed database and included in this review. Results: The search, following PRISMA guidelines, identified 13 human studies and 3 animal studies. Nine human studies compared brain activity and connectivity between regions in PD patients. Neural activity in the amygdala was highlighted in six studies. The hippocampus had higher activation in PD patients compared to those with social phobia, but generally showed less activity compared to healthy controls. The parahippocampal gyrus and thalamus exhibited greater activation in PD patients than healthy controls. Activity in the prefrontal cortices was also noted, particularly the ventromedial prefrontal cortex (vmPFC), ventrolateral prefrontal cortex (vlPFC), dorsomedial prefrontal cortex (dmPFC), and dorsolateral prefrontal cortex (dlPFC). Other regions involved included the dorsal midbrain, left brainstem (showing hyperactivation), S1, and right caudate, which showed increased activity in PD patients. The left intraparietal sulcus (IPS) exhibited hypoactivation in response to predictable cues compared to unpredictable or neutral cues within the default mode network (DMN). Three animal studies suggested that electrical and chemical activation of the dorsal periaqueductal gray (dPAG) in rats elicited fight-or-flight behaviors, providing a model for panic attacks. Conclusions: Neuroimaging studies suggest several key regions involved in PD pathophysiology, including the brainstem, amygdala, hippocampus, parahippocampal gyrus, thalamus, insula, and prefrontal and cingulate cortices. Hypersensitivity in the brainstem and amygdala plays a role in activating the fear network. Further prospective studies are needed to identify the neuroanatomical sites involved in PD and fear circuitry.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".