scholarly journals Multiscale Entropy of Cardiac and Postural Control Reflects a Flexible Adaptation to a Cognitive Task

Entropy ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. 1024 ◽  
Author(s):  
Estelle Blons ◽  
Laurent Arsac ◽  
Pierre Gilfriche ◽  
Veronique Deschodt-Arsac
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Postural Sway ◽  
Cognitive Task ◽  
Temporal Structure ◽  
Well Being ◽  
Multiscale Entropy ◽  
Cognitive Tasks ◽  
High Entropy ◽  
Stable Conditions

In humans, physiological systems involved in maintaining stable conditions for health and well-being are complex, encompassing multiple interactions within and between system components. This complexity is mirrored in the temporal structure of the variability of output signals. Entropy has been recognized as a good marker of systems complexity, notably when calculated from heart rate and postural dynamics. A degraded entropy is generally associated with frailty, aging, impairments or diseases. In contrast, high entropy has been associated with the elevated capacity to adjust to an ever-changing environment, but the link is unknown between entropy and the capacity to cope with cognitive tasks in a healthy young to middle-aged population. Here, we addressed classic markers (time and frequency domains) and refined composite multiscale entropy (MSE) markers (after pre-processing) of heart rate and postural sway time series in 34 participants during quiet versus cognitive task conditions. Recordings lasted 10 min for heart rate and 51.2 s for upright standing, providing time series lengths of 500–600 and 2048 samples, respectively. The main finding was that entropy increased during cognitive tasks. This highlights the possible links between our entropy measures and the systems complexity that probably facilitates a control remodeling and a flexible adaptability in our healthy participants. We conclude that entropy is a reliable marker of neurophysiological complexity and adaptability in autonomic and somatic systems.

The Effects of a Caffeine Placebo and Experimenter Expectation on Blood Pressure, Heart Rate, Well-Being, and Cognitive Performance

2001 ◽  
Vol 6 (1) ◽  
pp. 15-25 ◽  
Author(s):  
Harald Walach ◽  
Stefan Schmidt ◽  
Yvonne-Michelle Bihr ◽  
Susanne Wiesch
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Cognitive Task ◽  
Well Being ◽  
Control Group ◽  
Double Blind ◽  
Main Effect ◽  
The Difference ◽  
Being There ◽  
To Receive

We studied the effect of experimenter expectations and different instructions in a balanced placebo design. 157 subjects were randomized into a 2 × 4 factorial design. Two experimenters were led to expect placebos either to produce physiological effects or not (pro- vs. antiplacebo). All subjects except a control group received a caffeine placebo. They were either made to expect coffee, no coffee, or were in a double-blind condition. Dependent measures were blood pressure, heart rate, well-being, and a cognitive task. There was one main effect on the instruction factor (p = 0.03) with the group “told no caffeine” reporting significantly better well-being. There was one main effect on the experimenter factor with subjects instructed by experimenter “proplacebo” having higher systolic blood pressure (p = 0.008). There was one interaction with subjects instructed by experimenter “proplacebo” to receive coffee doing worse in the cognitive task than the rest. Subjects instructed by experimenter “antiplacebo” were significantly less likely to believe the experimental instruction, and that mostly if they had been instructed to receive coffee. Contrary to the literature we could not show an effect of instruction, but there was an effect of experimenters. It is likely, however, that these experimenter effects were not due to experimental manipulations, but to the difference in personalities.

scholarly journals Alterations in heart-brain interactions under mild stress during a cognitive task are reflected in entropy of heart rate dynamics

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Estelle Blons ◽  
Laurent M. Arsac ◽  
Pierre Gilfriche ◽  
Heather McLeod ◽  
Veronique Lespinet-Najib ◽  
...  
Keyword(s):  
Heart Rate ◽  
Cognitive Task ◽  
Modern Society ◽  
Cognitive Tasks ◽  
Mild Stress ◽  
Central Question ◽  
Integration Model ◽  
Heart Rate Dynamics ◽  
Healthy Participants

AbstractMany people experience mild stress in modern society which raises the need for an improved understanding of psychophysiological responses to stressors. Heart rate variability (HRV) may be associated with a flexible network of intricate neural structures which are dynamically organized to cope with diverse challenges. HRV was obtained in thirty-three healthy participants performing a cognitive task both with and without added stressors. Markers of neural autonomic control and neurovisceral complexity (entropy) were computed from HRV time series. Based on individual anxiety responses to the experimental stressors, two subgroups were identified: anxiety responders and non-responders. While both vagal and entropy markers rose during the cognitive task alone in both subgroups, only entropy decreased when stressors were added and exclusively in anxiety responders. We conclude that entropy may be a promising marker of cognitive tasks and acute mild stress. It brings out a new central question: why is entropy the only marker affected by mild stress? Based on the neurovisceral integration model, we hypothesized that neurophysiological complexity may be altered by mild stress, which is reflected in entropy of the cardiac output signal. The putative role of the amygdala during mild stress, in modulating the complexity of a coordinated neural network linking brain to heart, is discussed.

scholarly journals Entropy and Multifractal-Multiscale Indices of Heart Rate Time Series to Evaluate Intricate Cognitive-Autonomic Interactions

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 663
Author(s):  
Pierre Bouny ◽  
Laurent M. Arsac ◽  
Emma Touré Touré Cuq ◽  
Veronique Deschodt-Arsac
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Spatial Scales ◽  
Selective Inhibition ◽  
Emergent Behavior ◽  
Multiscale Entropy ◽  
Fluctuation Analysis ◽  
Cognitive Interference ◽  
Sensorimotor Network ◽  
Multifractal Behavior

Recent research has clarified the existence of a networked system involving a cortical and subcortical circuitry regulating both cognition and cardiac autonomic control, which is dynamically organized as a function of cognitive demand. The main interactions span multiple temporal and spatial scales and are extensively governed by nonlinear processes. Hence, entropy and (multi)fractality in heart period time series are suitable to capture emergent behavior of the cognitive-autonomic network coordination. This study investigated how entropy and multifractal-multiscale analyses could depict specific cognitive-autonomic architectures reflected in the heart rate dynamics when students performed selective inhibition tasks. The participants () completed cognitive interference (Stroop color and word task), action cancellation (stop-signal) and action restraint (go/no-go) tasks, compared to watching a neutral movie as baseline. Entropy and fractal markers (respectively, the refined composite multiscale entropy and multifractal-multiscale detrended fluctuation analysis) outperformed other time-domain and frequency-domain markers of the heart rate variability in distinguishing cognitive tasks. Crucially, the entropy increased selectively during cognitive interference and the multifractality increased during action cancellation. An interpretative hypothesis is that cognitive interference elicited a greater richness in interactive processes that form the central autonomic network while action cancellation, which is achieved via biasing a sensorimotor network, could lead to a scale-specific heightening of multifractal behavior.

scholarly journals Overload of anxiety on postural control impairments in chronic stroke survivors: The role of external focus and cognitive task on the automaticity of postural control

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0252131
Author(s):  
Zahra Ghorbanpour ◽  
Ghorban Taghizadeh ◽  
Seyed Ali Hosseini ◽  
Ebrahim Pishyareh ◽  
Farhad Tabatabai Ghomsheh ◽  
...  
Keyword(s):  
Postural Control ◽  
Healthy Subjects ◽  
Postural Sway ◽  
Cognitive Task ◽  
Neuromuscular Control ◽  
Chronic Stroke ◽  
Postural Instability ◽  
Cognitive Tasks ◽  
Stroke Survivors ◽  
External Focus

Background Despite the high prevalence of anxiety among chronic stroke survivors and evidence of its negative effects on postural control in healthy subjects, it is unclear whether anxiety also affects postural control in these patients. Recent evidence of improved postural control of healthy subjects by distracting the attention using an external focus (EF) or cognitive task, raises the question of whether similar benefits would be observed in stroke survivors. Thus, the current study aimed to investigate the effects of anxiety and distracting the attention on postural control of chronic stroke survivors in terms of both postural sway measures and neuromuscular regulation. Methods Postural sway measures and ankle muscle activity of chronic stroke survivors with the high and low level of anxiety (HA-stroke (n = 17), and LA-stroke (n = 17), respectively) and age-, sex-, height-, and weight-matched healthy subjects (n = 17) were assessed while standing on rigid and foam surfaces under following conditions: baseline, internal focus (IF), EF, simple and hard cognitive tasks (SC and HC, respectively). Results Stroke survivors, particularly HA-stroke participants, showed greater postural sway measures (i.e. postural instability) and enhanced co-contraction of ankle muscles (i.e. stiffening of the neuromuscular system) compared with healthy subjects. As opposed to baseline and IF conditions, postural instability and neuromuscular stiffening significantly reduced in EF condition and decreased more in cognitive task conditions, particularly HC condition. Conclusions The results suggest that anxiety enhances stroke-induced postural instability promoting improper neuromuscular control of posture with stiffening strategy, which can be alleviated by EF and cognitive tasks.

scholarly journals State Change Probability: A Measure of the Complexity of Cardiac RR Interval Time Series Using Physiological State Change with Statistical Hypothesis Testing

2019 ◽  
Author(s):  
Hsuan-Hao Chao ◽  
Han-Ping Huang ◽  
Sung-Yang Wei ◽  
Chang Francis Hsu ◽  
Long Hsu ◽  
...  
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
White Noise ◽  
Hypothesis Test ◽  
Statistical Tests ◽  
Physiological State ◽  
Statistical Hypothesis ◽  
Multiscale Entropy ◽  
State Change ◽  
State Changes

AbstractThe complexity of biological signals has been proposed to reflect the adaptability of a given biological system to different environments. Two measures of complexity—multiscale entropy (MSE) and entropy of entropy (EoE)—have been proposed, to evaluate the complexity of heart rate signals from different perspectives. The MSE evaluates the information content of a long time series across multiple temporal scales, while the EoE characterizes variation in amount of information, which is interpreted as the “state changing,” of segments in a time series. However, both are problematic when analyzing white noise and are sensitive to data size. Therefore, based on the concept of “state changing,” we propose state change probability (SCP) as a measure of complexity. SCP utilizes a statistical hypothesis test to determine the physiological state changes between two consecutive segments in heart rate signals. The SCP value is defined as the ratio of the number of state changes to total number of consecutive segment pairs. Two common statistical tests, the t-test and Wilcoxon rank–sum test, were separately used in the SCP algorithm for comparison, yielding similar results. The SCP method is capable of reasonably evaluating the complexity of white noise and other signals, including 1/f noise, periodic signals, and heart rate signals, from healthy subjects, as well as subjects with congestive heart failure or atrial fibrillation. The SCP method is also insensitive to data size. A universal SCP threshold value can be applied, to differentiate between healthy and pathological subjects for data sizes ranging from 100 to 10,000 points. The SCP algorithm is slightly better than the EoE method when differentiating between subjects, and is superior to the MSE method.

scholarly journals Multiscale Distribution Entropy Analysis of Short-Term Heart Rate Variability

Entropy ◽  
2018 ◽  
Vol 20 (12) ◽  
pp. 952 ◽  
Author(s):  
Dae-Young Lee ◽  
Young-Seok Choi
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Coarse Grained ◽  
Multiscale Entropy ◽  
Short Term ◽  
Ecg Signals ◽  
Improved Stability ◽  
Moving Averaging ◽  
Electrocardiogram Ecg

Electrocardiogram (ECG) signal has been commonly used to analyze the complexity of heart rate variability (HRV). For this, various entropy methods have been considerably of interest. The multiscale entropy (MSE) method, which makes use of the sample entropy (SampEn) calculation of coarse-grained time series, has attracted attention for analysis of HRV. However, the SampEn computation may fail to be defined when the length of a time series is not enough long. Recently, distribution entropy (DistEn) with improved stability for a short-term time series has been proposed. Here, we propose a novel multiscale DistEn (MDE) for analysis of the complexity of short-term HRV by utilizing a moving-averaging multiscale process and the DistEn computation of each moving-averaged time series. Thus, it provides an improved stability of entropy evaluation for short-term HRV extracted from ECG. To verify the performance of MDE, we employ the analysis of synthetic signals and confirm the superiority of MDE over MSE. Then, we evaluate the complexity of short-term HRV extracted from ECG signals of congestive heart failure (CHF) patients and healthy subjects. The experimental results exhibit that MDE is capable of quantifying the decreased complexity of HRV with aging and CHF disease with short-term HRV time series.

scholarly journals Interactions between simultaneous aerobic exercise and mental rotation

2021 ◽  
Author(s):  
Leonardo Jost ◽  
Andreas Weishäupl ◽  
Petra Jansen
Keyword(s):  
Heart Rate ◽  
Reaction Time ◽  
Aerobic Exercise ◽  
Mental Rotation ◽  
Cognitive Performance ◽  
Hierarchical Linear Modeling ◽  
Cognitive Task ◽  
Cognitive Effort ◽  
Mental Rotation Task ◽  
Cognitive Tasks

AbstractWhile the effects of aerobic exercise during a cognitive task on the performance of said cognitive task have been extensively studied, it has not been investigated whether cognitive performance during aerobic exercise influences the physical performance. For this, it is the main goal of the study to investigate the physical and cognitive performance during a simultaneous conduction of aerobic exercise and mental rotation. Forty-one German sport students cycled at 60% intensity while simultaneously performing a mental rotation task. In a within-subject design, both physical and cognitive performances were compared with isolated cycling and mental rotation as control conditions using both objective (heart rate and pedal cadence in the cycling task, reaction time and accuracy in the mental rotation task) and subjective (RPE) cognitive and physical measures. The results analyzed with hierarchical linear modeling revealed no effect of either simultaneous cognitive tasks on objective (heart rate) or subjective (RPE) physical effort, nor of simultaneous exercise on reaction time or accuracy in cognitive performance. However, we have found lower cadence during cognitive tasks, which was also stable in time compared to an increase in cadence during exercise control. Furthermore, our results demonstrated increased cognitive effort during exercise. Our findings suggest that increased effort, both physiological and cognitive, is required during combined physical and cognitive work in support of neurological resource conflicts caused by the differing demands of exercise and executive function.

Psychometric Properties of the Spontaneous and Deliberate Mind Wandering Scales

2019 ◽  
Vol 35 (6) ◽  
pp. 878-890 ◽  
Author(s):  
David Marcusson-Clavertz ◽  
Oscar N. E. Kjell
Keyword(s):  
Anxiety Disorder ◽  
Psychometric Properties ◽  
Generalized Anxiety Disorder ◽  
Social Desirability ◽  
Cognitive Task ◽  
Experience Sampling ◽  
Well Being ◽  
Mind Wandering ◽  
Generalized Anxiety ◽  
Psychological Variables

Abstract. Thinking about task-unrelated matters (mind wandering) is related to cognition and well-being. However, the relations between mind wandering and other psychological variables may depend on whether the former commence spontaneously or deliberately. The current two studies investigated the psychometric properties of the Spontaneous and Deliberate Mind Wandering Scales (SDMWS; Carriere, Seli, & Smilek, 2013 ). Study 1 evaluated the stability of the scales over 2 weeks ( N = 284 at Time 1), whereas Study 2 ( N = 323) evaluated their relations to Generalized anxiety disorder symptoms, Openness, Social desirability, and experience-sampling reports of intentional and unintentional mind wandering during an online cognitive task. The results indicated that the SDMWS were better fitted with a two-factor than a one-factor solution, although the fit was improved with the exclusion of one item. The scales exhibited strong measurement invariance across gender and time, and moderately high test-retest reliability. Spontaneous mind wandering predicted Generalized anxiety disorder and experience-sampling reports of unintentional mind wandering, whereas Deliberate mind wandering predicted Openness and experience-sampling reports of intentional mind wandering. Furthermore, Spontaneous mind wandering showed a negative association with social desirability of weak-to-medium strength. In sum, the scales generally showed favorable psychometric properties.

Correlation in the heart rate data

1998 ◽  
Vol 2 ◽  
pp. 141-148
Author(s):  
J. Ulbikas ◽  
A. Čenys ◽  
D. Žemaitytė ◽  
G. Varoneckas
Keyword(s):  
Nonlinear Dynamics ◽  
Experimental Data ◽  
Heart Rate ◽  
Time Series ◽  
Cardiovascular Function ◽  
Statistical Properties ◽  
Rate Data ◽  
Heart Rate Data ◽  
Dynamical Nature ◽  
Analysis Of Time Series

Variety of methods of nonlinear dynamics have been used for possibility of an analysis of time series in experimental physiology. Dynamical nature of experimental data was checked using specific methods. Statistical properties of the heart rate have been investigated. Correlation between of cardiovascular function and statistical properties of both, heart rate and stroke volume, have been analyzed. Possibility to use a data from correlations in heart rate for monitoring of cardiovascular function was discussed.

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