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The Neurovisceral Integration Model posits a link between resting vagally mediated heart rate variability (vmHRV) and cognitive control. Empirical support for this link is mixed, potentially due to coarse performance metrics such as mean response time (RT). To clarify this issue, we tested the relationships between resting vmHRV and refined estimates of cognitive control- as revealed by the ex-Gaussian model of RT and, to a greater extent, the drift diffusion model (DDM, a computational model of two-choice performance). Participants (N = 174) completed a five-minute resting baseline while ECG was collected followed by a Simon spatial conflict task. The root mean square of successive differences in interbeat intervals was calculated to index resting vmHRV. Resting vmHRV was unrelated to Simon mean RT and accuracy rates, but was inversely related to the ex-Gaussian parameter reflecting slow RTs (tau); however, this finding was attenuated after adjustment for covariates. High resting vmHRV was related to faster drift rates and slower non-decision times, DDM parameters reflecting goal-directed cognition and sensorimotor processes, respectively. The DDM effects survived covariate adjustment and were specific to incongruent trials (i.e., when cognitive control demands were high). Findings suggest a link between vmHRV and cognitive control vis-a-vis drift rate, and potentially, a link between vmHRV and motoric inhibition vis-a-vis non-decision time. These cognitive correlates would have been missed with reliance on traditional performance. Findings are discussed with respect to the inhibitory processes that promote effective performance in high vmHRV individuals., (Copyright © 2022. Published by Elsevier B.V.)

Research on the autonomic specificity of emotion has spanned decades, yet the findings of this research are still highly debated. Although many studies have explored the autonomic specificity of emotions, few have concurrently explored the influence by which the induction methods themselves have had in directing autonomic change. The current study was conducted to assess whether the methods for emotion elicitation could be meaningfully captured by multivariate pattern classification techniques that have been previously used to explore autonomic specificity of emotion. This aim was achieved by using three separate emotion-elicitation methods to elicit five separate emotions. A sample of 64 college-aged students watched film clips, read imagery scripts, and recalled personal memories for five emotion states. Using multivariate pattern classification analysis, the evidence from the current study lends further support for autonomic specificity of emotion, but also highlights the role that the specific induction technique contributes to autonomic changes that accompany emotions in the laboratory., (Published by Elsevier B.V.)