Department of Biobehavioral Health, Penn State University, United States of America.
Department of Psychology, Old Dominion University, United States of America.
Int J Psychophysiol. 2022 Nov;181:73-84. doi: 10.1016/j.ijpsycho.2022.08.003. Epub 2022 Aug 25.
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.
神经内脏整合模型提出了静息状态下迷走神经介导的心率变异性（vmHRV）与认知控制之间的联系。这种联系的实证支持是混合的，可能是由于平均反应时间（RT）等粗糙的性能指标。为了澄清这个问题，我们测试了静息 vmHRV 与认知控制的精细估计之间的关系，这些精细估计是由 RT 的超伽马模型揭示的，在更大程度上是由漂移扩散模型（DDM，一种二择一性能的计算模型）揭示的。参与者（N=174）在进行 ECG 采集之前完成了五分钟的静息基线，随后进行了 Simon 空间冲突任务。通过计算相邻心搏间期的均方根差来衡量静息 vmHRV。静息 vmHRV 与 Simon 平均 RT 和准确率无关，但与反映 RT 较慢的超伽马参数（tau）呈负相关；然而，在对协变量进行调整后，这一发现减弱了。高静息 vmHRV 与较慢的漂移率和较长的非决策时间有关，DDM 参数分别反映了目标导向认知和感觉运动过程。DDM 效应在对协变量进行调整后仍然存在，并且与不一致试验（即认知控制要求较高时）特异性相关。这些发现表明，vmHRV 与漂移率之间存在认知控制的联系，并且可能与非决策时间之间存在与运动抑制有关的联系。如果依赖于传统的性能指标，这些认知相关性将被忽略。研究结果从促进高 vmHRV 个体有效表现的抑制过程的角度进行了讨论。
