A mechanistic model of threat-driven respiration and its homeostatic recovery in anxiety and depression
Year: 2026
Type: preprint
Abstract: Anxiety and depression change how people breathe, often early in the illness, and wearable sensors now allow breathing to be monitored continuously. This work presents, to our knowledge, the first mechanistic model of how the brain’s threat response sets breathing rate and depth and how fast breathing recovers after stress. A threat signal from the amygdala, shaped by stimulus magnitude and by cognitive appraisal (coping capacity and perceived stress), drives the breathing-control center that receives lung feedback: stretch receptors slow breathing and airway receptors speed it up. A simple electrical circuit stores the threat signal and expresses recovery as one time constant. We prove the model’s key properties, test them under noise and parameter variation, and compare it with chest-belt recordings from 15 adults in the Wearable Stress and Affect Detection (WESAD) study. Breathing rate rose from 18 to 28 and 31 breaths per minute from normal to moderate to severe, an order that held in every test. Recovery took about 3, 10, and 50 seconds, paced by how long the airway-receptor signal lingers in the brainstem, and the circuit followed breathing closely (correlation 0.96–0.98). In WESAD, a spoken stress task raised anxiety and breath depth ( p < 0.001); speech set the breathing rhythm during the task, and breathing then returned to rest, as the model predicts for healthy people. A compact, provable model links clinical stress measures to the breathing signals that wearables record. It offers measurable targets for monitoring anxiety and depression: how strongly threat drives respiration and how quickly homeostatic regulation restores it. Author summary Anxiety and depression change the way people breathe: breathing becomes faster, and it takes longer to settle after a stressful moment. Wearables now record breathing continuously, but without a mechanistic account of how the brain’s response to threat shapes each breath, these recordings are hard to interpret. We built a mathematical model that runs from a threat-processing circuit in the amygdala, tuned by a person’s coping capacity and perceived stress, through the brainstem centers that set breathing, to the stretch and irritant sensors in the lungs that feed back on them. Analysis and simulation showed that as the clinical profile worsens, breathing becomes faster both at rest and under threat and recovers more slowly after stress. This recovery is paced not by the threat itself but by how long the brainstem retains signals from the airway sensors. In healthy volunteers performing a public-speaking stress test, speaking itself set the breathing rhythm and masked any stress-driven change in rate, and breathing rate was back at rest once the task ended. Our results identify two quantities that wearables could track, how strongly threat drives breathing and how quickly it recovers, and define the experiments needed to test them in patients.
Authors: Malik Faizan, P. J. White, Indrakshi Dey
Language: English
Subfield: Endocrine and Autonomic Systems
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7223250447