title: Multivariate Brain Prediction of Heart Rate and Skin Conductance Responses to Social Threat.
abstract: Psychosocial stressors induce autonomic nervous system (ANS) responses in multiple body systems that are linked to health risks. Much work has focused on the common effects of stress, but ANS responses in different body systems are dissociable and may result from distinct patterns of cortical-subcortical interactions. Here, we used machine learning to develop multivariate patterns of fMRI activity predictive of heart rate (HR) and skin conductance level (SCL) responses during social threat in humans (N = 18). Overall, brain patterns predicted both HR and SCL in cross-validated analyses successfully (rHR= 0.54, rSCL= 0.58, both p < 0.0001). These patterns partly reflected central stress mechanisms common to both responses because each pattern predicted the other signal to some degree (rHR→SCL= 0.21 and rSCL→HR= 0.22, both p < 0.01), but they were largely physiological response specific. Both patterns included positive predictive weights in dorsal anterior cingulate and cerebellum and negative weights in ventromedial PFC and local pattern similarity analyses within these regions suggested that they encode common central stress mechanisms. However, the predictive maps and searchlight analysis suggested that the patterns predictive of HR and SCL were substantially different across most of the brain, including significant differences in ventromedial PFC, insula, lateral PFC, pre-SMA, and dmPFC. Overall, the results indicate that specific patterns of cerebral activity track threat-induced autonomic responses in specific body systems. Physiological measures of threat are not interchangeable, but rather reflect specific interactions among brain systems.
  
  
  
  We show that threat-induced increases in heart rate and skin conductance share some common representations in the brain, located mainly in the vmPFC, temporal and parahippocampal cortices, thalamus, and brainstem. However, despite these similarities, the brain patterns that predict these two autonomic responses are largely distinct. This evidence for largely output-measure-specific regulation of autonomic responses argues against a common system hypothesis and provides evidence that different autonomic measures reflect distinct, measurable patterns of cortical-subcortical interactions.
authors.affiliation: Department of Psychology and Neuroscience and the Institute for Cognitive Science, University of Colorado, Boulder, Colorado 80309.|Department of Psychology, University of Southampton, Southampton, Hampshire SO17 1BJ, United Kingdom, and.
authors.forename: Hedwig
authors.identifier: 0000-0002-0521-2630
authors.initials: H
authors.lastname: Eisenbarth
authors.affiliation: Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire 03755.
authors.forename: Luke J
authors.identifier: 0000-0002-6621-8120
authors.initials: LJ
authors.lastname: Chang
authors.affiliation: Department of Psychology and Neuroscience and the Institute for Cognitive Science, University of Colorado, Boulder, Colorado 80309, tor.wager@colorado.edu.
authors.forename: Tor D
authors.identifier: 0000-0002-1936-5574
authors.initials: TD
authors.lastname: Wager
mesh_terms: D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D005239:Fear / Q000502:physiology*; D005260:Female; D005712:Galvanic Skin Response / Q000502:physiology*; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D015999:Multivariate Analysis; D009415:Nerve Net / Q000502:physiology; D012919:Social Behavior; D012938:Social Perception; D013312:Stress, Physiological / Q000502:physiology*; D055815:Young Adult
keywords: heart rate; machine learning; multivariate pattern analysis; skin conductance; social threat; stress