Integrating Peripheral and Neural Measures of Emotion Regulation in Suicidal Behavior

Project Summary/Abstract Suicide is a leading cause of death in the United States. Recent neuroimaging studies have identified alterations in neural networks involved in emotion regulation in suicidal populations, and such research may be important to informing clinical interventions. Still, it remains unclear how these alterations uniquely contribute to suicidal behavior. Integrating peripheral autonomic measures of emotion with neuroimaging (fMRI) may help further delineate mechanisms of emotion dysregulation that increase risk for suicide. Autonomic cardiac reactivity plays a critical role in the formation and subjective experience of emotion. Altered autonomic responses to risky decisions are implicated in maladaptive emotional responding and behavior, and evidence suggests that deficits in perception of autonomic cues contribute to acquired capability for suicide. However, peripheral measures of emotion are rarely studied in conjunction with fMRI in suicidal populations. The current study aims to integrate fMRI with heart rate variability (HRV), a peripheral index of parasympathetically-mediated vagal control of the cardiac rhythm that facilitates adaptive emotional responding. Specifically, we aim to 1) examine alterations in autonomic reactivity to emotion in suicide attempters, 2) investigate how synchrony between HRV and fMRI connectivity is related to emotion regulation, and 3) compare HRV—fMRI synchrony and emotion regulation in suicide attempters relative to depressed non-attempters and controls. We hypothesize that asynchrony in the dynamic coordination of autonomic and neural responding underlies emotion regulation deficits in suicide attempters. We expect that suicide attempters will demonstrate blunted HRV, less synchrony between HRV and functional connectivity, and less effective emotion regulation, relative to depressed non-attempters and controls. To accomplish these aims, we will simultaneously acquire electrocardiogram (ECG) data and fMRI in the context of an emotion regulation task. ECG will be used to derive a time series of HRV. Cross-correlational analyses will be used to assess synchrony between HRV and functional neural connectivity of ventromedial prefrontal cortex and limbic networks (regions involved in emotion regulation), and how these systems interact to impact emotional functioning. Key innovations include: 1) integration of fMRI with autonomic indices of emotion to 2) examine alterations in temporal dynamics of emotional responding across multiple physiological systems in 3) suicide attempters. Our long-term goal is to better understand body-brain emotion states that contribute to suicidal behavior, in service of ultimately informing prevention and intervention efforts for suicide.