Point process time–frequency analysis of dynamic respiratory patterns during meditation practice

Respiratory sinus arrhythmia (RSA) is largely mediated by the autonomic nervous system through its modulating influence on the heart beats. We propose a robust algorithm for quantifying instantaneous RSA as applied to heart beat intervals and respiratory recordings under dynamic breathing patterns. The blood volume pressure-derived heart beat series (pulse intervals, PIs) are modeled as an inverse Gaussian point process, with the instantaneous mean PI modeled as a bivariate regression incorporating both past PIs and respiration values observed at the beats. A point process maximum likelihood algorithm is used to estimate the model parameters, and instantaneous RSA is estimated via a frequency domain transfer function evaluated at instantaneous respiratory frequency where high coherence between respiration and PIs is observed. The model is statistically validated using Kolmogorov–Smirnov goodness-of-fit analysis, as well as independence tests. The algorithm is applied to subjects engaged in meditative practice, with distinctive dynamics in the respiration patterns elicited as a result. The presented analysis confirms the ability of the algorithm to track important changes in cardiorespiratory interactions elicited during meditation, otherwise not evidenced in control resting states, reporting statistically significant increase in RSA gain as measured by our paradigm.National Institutes of Health (U.S.) (Grant R01-HL084502)National Institutes of Health (U.S.) (Grant R01-DA015644)National Institutes of Health (U.S.) (Grant DP1-OD003646)National Institutes of Health (U.S.) (Grant K01-AT00694-01

Verbal, Facial and Autonomic Responses to Empathy-Eliciting Film Clips by Disruptive Male Adolescents with High Versus Low Callous-Unemotional Traits

This study examined empathy-related responding in male adolescents with disruptive behavior disorder (DBD), high or low on callous-unemotional (CU) traits. Facial electromyographic (EMG) and heart rate (HR) responses were monitored during exposure to empathy-inducing film clips portraying sadness, anger or happiness. Self-reports were assessed afterward. In agreement with expectations, DBD adolescents with high CU traits showed significantly lower levels of empathic sadness than healthy controls across all response systems. Between DBD subgroups significant differences emerged at the level of autonomic (not verbal or facial) reactions to sadness, with high CU respondents showing less HR change from baseline than low CU respondents. The study also examined basal patterns of autonomic function. Resting HR was not different between groups, but resting respiratory sinus arrhythmia (RSA) was significantly lower in DBD adolescents with high CU traits compared to controls. Results support the notion that CU traits designate a distinct subgroup of DBD individuals

MEASUREMENT AND ANALYSIS-METHODS OF HEART-RATE AND RESPIRATION FOR USE IN APPLIED ENVIRONMENTS

Cardiovascular measures are used in applied settings to assess mental load. It is neither desirable nor possible to adapt the working situation to the needs of the experimenter, as can be done in the laboratory; the purpose of this paper is to discuss how invested effort, mental efficiency, and changes in cardiovascular state can be measured in applied settings, including non-stationary ones. This paper discusses the theoretical background of fluctuations in heart rate and respiration and the application of existing methods in laboratory and normal working situations. Data acquisition and analysis methods are then presented, particularly the problems of artifact detection and correction and variability indices in spectral bands in relation to the reliability of these measures. In the last section, the interpretation of data acquired in applied environments and the specific problems inherent in such situations are discusse

Workplace for analysis of task performance

In current research on mental workload and task performance a large gap exists between laboratory based studies and research projects in real life working practice. Tasks conducted within a laboratory environment often lack a strong resemblance with real life working situations. This paper presents an experimental approach to minimizing this gap by designing a very flexible experimentation system with adequate hardware and software components. The first goal of the system is to design a laboratory based environment in which a broad range of computer supported daily life work can be simulated, including co-operative working situations. Moreover, several behavioral and physiological measurement and analysis techniques are supported, such as video based behavioral analysis, task related event registration, cardiovascular state analysis, determining mental workload indices as well as EEG background and ERP analysis. An important requirement for relating the different measured variables to task performance is synchronization of data sources and task parameters at varying time scales. The highest time accuracy should be at least 10 milliseconds. The present system fulfils this requirement by using software system components and libraries that allow real time experiment control and measurement. Additionally, the new system should work within a Microsoft Windows based environment, providing the possibility to use standard office software that is well known to subjects having to work in the new environment. The option to use such standard software, in combination with new (simulation) techniques for presenting more realistic tasks, results in a powerful laboratory environment in which task elements in semi-realistic tasks can be manipulated experimentally. The way to do this is by defining adequate scenarios that can be simulated. At present, is that both a simple, less realistic task has been realized (Synwork) with a high time accuracy (1 ms), as well as a more realistic simulation of an ambulance dispatcher task with lower time accuracy (10-100 ms). Both types of task can be seen as examples of the range of tasks to be implemented in the near future