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This paper aimed to (a) validate a novel technique that quantifies the length of the trajectories the cardiac system follows within a two-dimensional state-space, and (b) test its usefulness to better understand how cognitive emotion regulation (CER) style is associated with cardiac output. A positive CER style was assessed in a sample of healthy adolescents (n = 57), and mean and total distances, in addition to heart rate variability (HRV) measures and cardiac entropy (SampEn), were calculated during a conflict discussion with the adolescents' mothers. Associations between distances and HRV measures in time and frequency-domains and SampEn were examined to better understand the physiological meaning of distances; further, whether a positive CER style would predict distances, HRV, and SampEn. Correlation analysis revealed that associations of distances with time-domain HRV measures were stronger than associations with frequency-domain HRV measures, while correlations between distances and SampEn were moderate. Hierarchical multiple regression analysis revealed that a positive CER style predicted distances and SampEn, but not HRV measures. Distances are clearly time-domain measures of HRV, but only partly capture the complexity of the heart signal. The results highlight the importance of assessing heart rate dynamics beyond HRV in the study of CER.

An inverted U-shaped pattern in heart rate (HR) and a U-shaped pattern in heart rate variability (HRV) are easily recognizable when individuals experience any acute stressor. How cardiac complexity (scaling and entropy) changes under acute stress is not well known. Psychologically, emotion regulation (ER) style is likely to influence the individual's specific behavioral response when affronting stress. This study tested whether adolescents with distinct ER styles would show different patterns of linear and nonlinear cardiac changes under stressful conditions. We predicted less autonomic flexibility for adolescents with a highly negative emotional regulation (HNER) style (n = 10) than for those adolescents with a highly positive emotional regulation (HPER) style (n=10). Further, associations between linear and nonlinear measures during each condition were examined for each group. Repeated measures ANOVAs revealed that HR and HRV changed according to the predicted pattern. Higuchi's fractal dimension and Sample Entropy followed a U-shaped pattern, whereas the short-term scaling exponent followed the reverse pattern. Cardiac changes across conditions were larger in the HPER group. Significant associations between linear and nonlinear measures were found in the HPER group but not in the HNER group. Results are cautiously discussed within a multiscale framework of fluctuations of the different cardiac features.

This paper introduces a new measure to evaluate heart output from a dynamical systems approach. The measure is based on the time delay technique for two-dimensional state space reconstruction from time series of interbeat intervals. The system's trajectories within this space are depicted and the mean distance, as well as the total and maximum distances travelled by the system, are calculated in pixels. Preliminary data from adolescents with highly positive emotional regulation (HPER) style (n=10) and adolescents with highly negative (HNER) style (n=10) who underwent a protocol of stress induction show the usefulness of the new metrics to distinguish the dynamical behavior of the heart systems from these groups. Repeated measures ANOVAs revealed that changes in all three distances across conditions (baseline, anticipation of stress, exposure to stress, and recovery) were significant in the HPER group but not in the HNER group. As to the physiological meaning of the new measure a correlational analysis revealed that associations with time-domain HRV measures were stronger than associations with frequency-domain HRV measures in both groups. Because of the small sample size, bootstrap resampling was used to obtain confidence intervals. Distances calculated with the new measure are sensitive to the ER-related cardiac flexibility under acute stress conditions. However, the physiological meaning of the new indices remains unclear.

The risk of suffering anxiety disorders is associated with sustained subthreshold symptoms of anxiety. This study evaluated the stability of anxiety scores (high, moderate or low) across a six-month period in early adolescents (N = 95). The associations between sustained anxiety, vagally-mediated heart rate variability (vmHRV), sympathetic activity, and heart rate fractal dynamics in everyday life conditions were analyzed. The anxiety scores from 71.50% of participants remained at the same level. The linear correlations between anxiety and cardiac measures were weak but a group-based approach revealed that the fractal dimension (FD) from stable-low anxiety participants was higher than the FD from participants with stable-moderate anxiety scores but not higher than the FD from the stable-high anxiety group. The short-term correlations' exponent a1 from the stable-high anxiety group was higher than the a1 from the stable-moderate anxiety group but not higher than the exponent from the stable-low anxiety group. No differences were found in the vmHRV nor sympathetic activity. The lack of a direct association between the complexity of the heart rate and the level of sustained anxiety suggests a nonlinear pattern of associations that would be in accordance with the optimum variability principle.

Many physiological systems are multistable, i.e. they operate at different time scales under an allometric control process. The multistability of affective fluctuations has been clearly illustrated in a sample of adults, but little is known about their dynamics in adolescents. The main aim of this study was to determine whether affective fluctuations in adolescents show multistability and to explore their relationship with anxiety symptomatology and temperamental factors. Twenty-five early adolescents self-reported their daily mood, anxiety and worry levels twice a day over a 100-day period. The time series were analysed using the allometric aggregation method to obtain the scaling exponent h. Almost all the (Hurst) scaling exponents were 0.5 > h > 1. The worry exponents were related to temperament factors, whereas the anxiety exponents were related to social phobia symptoms. The results substantiate that affective fluctuations in adolescents are multistable, lending support to the presence of allometric control mechanisms.

This study is aimed at elucidating (a) whether heart rate (HR) complexity measures are associated with the attentional orienting function, and (b) which of these measures better predicts orienting efficiency indexes. Vagal tone, sample entropy, scaling exponents ?1 and ?2, and fractal dimension (FD) were calculated in HR time series (n=109). Vagal tone, entropy, and FD were positively associated with orienting, while this association was negative for ?2. These results show that HR scaling properties, which underlie the role of vagal tone and reflect allometric control mechanisms, are associated with orienting deficits. FD was the best predictor of attentional orienting.

Effective regulation of emotions requires the ability to voluntarily manage attention, i.e. attentional control (AC), which has been related to heart rate variability and vagal tone in laboratory based research. In this study, we calculated the correlation dimension (CD), the fractal-like properties (scaling exponents ?1 and ?2, and fractal dimension) and the sample entropy of heart rate time series obtained from ECG recordings (4 hours long each) taken from a sample of healthy students (n=47) during everyday activities. AC was assessed through a self-reported questionnaire. As expected, a linear positive correlation was found between AC scores and CD and entropy, but no associations were found between AC and ?1 and fractal dimension. The association between AC and ?2 was negative and marginally significant. No associations were found between AC and linear heart rate variability measures. These results show that nonlinear measures of long, everyday life, heart rate time series may provide useful information about the AC ability of healthy students.