Sustained anxiety increases amygdala–dorsomedial prefrontal coupling: a mechanism for maintaining an anxious state in healthy adults
Bibliographic record
Abstract
BACKGROUND: Neuroimaging research has traditionally explored fear and anxiety in response to discrete threat cues (e.g., during fear conditioning). However, anxiety is a sustained aversive state that can persist in the absence of discrete threats. Little is known about mechanisms that maintain anxiety states over a prolonged period. Here, we used a robust translational paradigm (threat of shock) to induce sustained anxiety. Recent translational work has implicated an amygdala-prefrontal cortex (PFC) circuit in the maintenance of anxiety in rodents. To explore the functional homologues of this circuitry in humans, we used a novel paradigm to examine the impact of sustained anticipatory anxiety on amygdala-PFC intrinsic connectivity. METHODS: Task-independent fMRI data were collected in healthy participants during long-duration periods of shock anticipation and safety. We examined intrinsic functional connectivity. RESULTS: Our study involved 20 healthy participants. During sustained anxiety, amygdala activity was positively coupled with dorsomedial PFC (DMPFC) activity. High trait anxiety was associated with increased amygdala-DMPFC coupling. In addition, induced anxiety was associated with positive coupling between regions involved in defensive responding, and decreased coupling between regions involved in emotional control and the default mode network. LIMITATIONS: Inferences regarding anxious pathology should be made with caution because this study was conducted in healthy participants. CONCLUSION: Findings suggest that anticipatory anxiety increases intrinsic amygdala-DMPFC coupling and that the DMPFC may serve as a functional homologue for the rodent prefrontal regions by sustaining anxiety. Future research may use this defensive neural context to identify biomarkers of risk for anxious pathology and target these circuits for therapeutic intervention.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".