Robust Estimation of Respiratory Variability Uncovers Correlates of Limbic Brain Activity and Transcutaneous Cervical Vagus Nerve Stimulation in the Context of Traumatic Stress

Objective:
Variations in respiration patterns are a characteristic response to distress due to underlying neurorespiratory couplings. Yet, no work to date has quantified respiration pattern variability (RPV) in the context of traumatic stress and studied its functional neural correlates – this analysis aims to address this gap.
Methods:
Fifty human subjects with prior traumatic experiences (24 with posttraumatic stress disorder (PTSD)) completed a ∼3-hr protocol involving personalized traumatic scripts and active/sham (double-blind) transcutaneous cervical vagus nerve stimulation (tcVNS). High-resolution positron emission tomography functional neuroimages, electrocardiogram (ECG), and respiratory effort (RSP) data were collected during the protocol. Supplementing the RSP signal with ECG-derived respiration for quality assessment and timing extraction, RPV metrics were quantified and analyzed. Specifically, correlation analyses were performed using neuroactivity in selected limbic regions, and responses to active and sham tcVNS were compared.
Results:
The single-lag unscaled autocorrelation of respiration rate correlated negatively with left amygdala activity and positively with right rostromedial prefrontal cortex (rmPFC) activity for non-PTSD; it also correlated negatively with left and right insulae activity and positively with right rmPFC activity for PTSD. The single-lag unscaled autocorrelation of expiration time was greater following active stimulation for non-PTSD.
Conclusion:
Quantifying RPV is of demonstrable importance to assessing trauma-induced changes in neural function and tcVNS effects on respiratory physiology.
Significance:
This is the first demonstration of RPV's pertinence to traumatic stress- and tcVNS-induced neurorespiratory responses. The open-source processing pipeline elucidated herein uniquely includes both RSP and ECG-derived respiration signals for quality assessment, timing estimation, and RPV extraction.