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Locomotion in virtual environments predicts cardiovascular responsiveness to subsequent stressful challenges.

ABSTRACT: Individuals differ in their physiological responsiveness to stressful challenges, and stress potentiates the development of many diseases. Heart rate variability (HRV), a measure of cardiac vagal break, is emerging as a strong index of physiological stress vulnerability. Thus, it is important to develop tools that identify predictive markers of individual differences in HRV responsiveness without exposing subjects to high stress. Here, using machine learning approaches, we show the strong predictive power of high-dimensional locomotor responses during novelty exploration to predict HRV responsiveness during stress exposure. Locomotor responses are collected in two ecologically valid virtual reality scenarios inspired by the animal literature and stress is elicited and measured in a third threatening virtual scenario. Our model's predictions generalize to other stressful challenges and outperforms other stress prediction instruments, such as anxiety questionnaires. Our study paves the way for the development of behavioral digital phenotyping tools for early detection of stress-vulnerable individuals.

SUBMITTER: Rodrigues J

PROVIDER: S-EPMC7677550 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Locomotion in virtual environments predicts cardiovascular responsiveness to subsequent stressful challenges.

Rodrigues João J Studer Erik E Streuber Stephan S Meyer Nathalie N Sandi Carmen C

Nature communications 20201119 1

Individuals differ in their physiological responsiveness to stressful challenges, and stress potentiates the development of many diseases. Heart rate variability (HRV), a measure of cardiac vagal break, is emerging as a strong index of physiological stress vulnerability. Thus, it is important to develop tools that identify predictive markers of individual differences in HRV responsiveness without exposing subjects to high stress. Here, using machine learning approaches, we show the strong predic ...[more]

PMID: 33214564

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Project description:BACKGROUND:It is still unknown that whether co-existing intracranial stenosis and extracranial carotid vulnerable plaques have higher predictive value for subsequent vascular events. This study aimed to determine the relationship between co-existing extracranial carotid vulnerable plaques and intracranial stenosis and subsequent vascular events utilizing cardiovascular magnetic resonance (CMR) vessel wall imaging. METHODS:Patients who had recent cerebrovascular symptoms in anterior circulation (<?2?weeks) were consecutively enrolled and underwent multi-contrast CMR vessel wall imaging for extracranial carotid arteries and 3D time-of flight CMR angiography for intracranial arteries at baseline. After baseline examination, all patients were followed-up for at least 1?year to determined recurrence of vascular events. The co-existing cerebrovascular atherosclerosis was defined as presence of both intracranial artery stenosis and at least one the following measures of extracranial artery atherosclerosis: plaque, calcification, lipid-rich necrotic core (LRNC), or intraplaque hemorrhage. Univariate and multivariate Cox regressions were used to calculate the hazard ratio (HR) and corresponding 95% confidence interval (CI) of co-existing plaques in predicting subsequent vascular events. RESULTS:In total, 150 patients (mean age: 61.8?±?11.9?years; 109 males) were recruited. During the median follow-up time of 12.1?months, 41 (27.3%) patients experienced vascular events. Co-existing intracranial artery stenosis and extracranial carotid plaque (HR, 3.57; 95% CI, 1.63-7.82; P?=?0.001) and co-existing intracranial artery stenosis and extracranial carotid LRNC (HR, 4.47; 95% CI, 2.15-9.27; P?<?0.001) were significantly associated with subsequent vascular events, respectively. After adjusted for confounding factors and carotid stenosis, these associations remained statistically significant (HR, 5.12; 95% CI, 1.36-19.24; P?=?0.016 and HR, 8.12; 95% CI, 2.41-27.31; P?=?0.001, respectively). CONCLUSIONS:The co-existing cerebrovascular atherosclerotic diseases, particularly co-existing carotid lipid-rich necrotic core and intracranial stenosis, are independent predictors for subsequent vascular events.

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Locomotion in virtual environments predicts cardiovascular responsiveness to subsequent stressful challenges.

Publications

Locomotion in virtual environments predicts cardiovascular responsiveness to subsequent stressful challenges.

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