A nonstationarity test for the spectral analysis of physiological time series with an application to respiratory sinus arrhythmia

Publication guidelines for human heart rate and heart rate variability studies in psychophysiology-Part 1: Physiological underpinnings and foundations of measurement

This Committee Report provides methodological, interpretive, and reporting guidance for researchers who use measures of heart rate (HR) and heart rate variability (HRV) in psychophysiological research. We provide brief summaries of best practices in measuring HR and HRV via electrocardiographic and photoplethysmographic signals in laboratory, field (ambulatory), and brain-imaging contexts to address research questions incorporating measures of HR and HRV. The Report emphasizes evidence for the strengths and weaknesses of different recording and derivation methods for measures of HR and HRV. Along with this guidance, the Report reviews what is known about the origin of the heartbeat and its neural control, including factors that produce and influence HRV metrics. The Report concludes with checklists to guide authors in study design and analysis considerations, as well as guidance on the reporting of key methodological details and characteristics of the samples under study. It is expected that rigorous and transparent recording and reporting of HR and HRV measures will strengthen inferences across the many applications of these metrics in psychophysiology. The prior Committee Reports on HR and HRV are several decades old. Since their appearance, technologies for human cardiac and vascular monitoring in laboratory and daily life (i.e., ambulatory) contexts have greatly expanded. This Committee Report was prepared for the Society for Psychophysiological Research to provide updated methodological and interpretive guidance, as well as to summarize best practices for reporting HR and HRV studies in humans.

Increased cardiac vagal tone in childhood-only, adolescent-only, and persistently antisocial teenagers: the mediating role of low heart rate

BACKGROUND

Cardiac vagal tone is an indicator of parasympathetic nervous system functioning, and there is increasing interest in its relation to antisocial behavior. It is unclear however whether antisocial individuals are characterized by increased or decreased vagal tone, and whether increased vagal tone is the source of the low heart rate frequently reported in antisocial populations.

METHODS

Participants consisted of four groups of community-dwelling adolescent boys aged 15.7 years: (1) controls, (2) childhood-only antisocial, (3) adolescent-only antisocial, and (4) persistently antisocial. Heart rate and vagal tone were assessed in three different conditions: rest, cognitive stressor, and social stressor.

RESULTS

All three antisocial groups had both lower resting heart rates and increased vagal tone compared to the low antisocial controls across all three conditions. Low heart rate partially mediated the relationship between vagal tone and antisocial behavior.

CONCLUSIONS

Results indicate that increased vagal tone and reduced heart rate are relatively broad risk factors for different developmental forms of antisocial behavior. Findings are the first to implicate vagal tone as an explanatory factor in understanding heart rate - antisocial behavior relationships. Future experimental work using non-invasive vagus nerve stimulation or heart rate variability biofeedback is needed to more systematically evaluate this conclusion.

Understanding Heart Rate Reactions to Post-Traumatic Stress Disorder (PTSD) Among Veterans: A Naturalistic Study

OBJECTIVE

We collected naturalistic heart rate data from veterans diagnosed with post-traumatic stress disorder (PTSD) to investigate the effects of various factors on heart rate.

BACKGROUND

PTSD is prevalent among combat veterans in the United States. While a positive correlation between PTSD and heart rate has been documented, specific heart rate profiles during the onset of PTSD symptoms remain unknown.

METHOD

Veterans were recruited during five cycling events in 2017 and 2018 to record resting and activity-related heart rate data using a wrist-worn device. The device also logged self-reported PTSD hyperarousal events. Regression analyses were performed on demographic and behavioral covariates including gender, exercise, antidepressants, smoking habits, sleep habits, average heart rate during reported hyperarousal events, age, glucocorticoids consumption, and alcohol consumption. Heart rate patterns during self-reported PTSD hyperarousal events were analyzed using Auto Regressive Integrated Moving Average (ARIMA). Heart rate data were also compared to an open-access non-PTSD representative case.

RESULTS

Of 99 veterans with PTSD, 91 participants reported at least one hyperarousal event, with a total of 1023 events; demographic information was complete for 38 participants who formed the subset for regression analyses. The results show that factors including smoking, sleeping, gender, and medication significantly affect resting heart rate. Moreover, unique heart rate patterns associated with PTSD symptoms in terms of stationarity, autocorrelation, and fluctuation characteristics were identified.

CONCLUSION

Our findings show distinguishable heart rate patterns and characteristics during PTSD hyperarousal events.

APPLICATION

These findings show promise for future work to detect the onset of PTSD symptoms.

Convolutional neural networks predict the onset of paroxysmal atrial fibrillation: Theory and applications

In this study, we aimed to detect paroxysmal atrial fibrillation episodes before they occur so that patients can take precautions before putting their and others' lives in potentially life-threatening danger. We used the atrial fibrillation prediction database, open data from PhysioNet, and assembled our process based on convolutional neural networks. Conventional heart rate variability features are calculated from time-domain measures, frequency-domain measures using power spectral density estimations, time-frequency-domain measures using wavelet transform, and nonlinear Poincaré plot measures. In addition, we also applied an alternative heart rate normalization, which gave promising results only in a few studies, before calculating these heart rate variability features. We used these features directly and their normalized versions using min-max normalization and z-score normalization methods. Thus, heart rate variability features extracted from six different combinations of these normalizations, in addition to no normalization cases, were applied to the convolutional neural network classifier. We tuned the classifiers' hyperparameters using 90% of feature sets and tested the classifiers' performances using 10% of feature sets. The proposed approach resulted in 87.76% accuracy, 91.30% precision, 80.04% recall, and 87.50% f1-score in heart rate variability with z-score feature normalization. When the heart rate normalization was also utilized, the suggested method gave 100% accuracy, 100% precision, 100% recall, and 100% f1-score in heart rate variability with z-score feature normalization. The proposed method with heart rate normalization and z-score normalization methods resulted in better classification performance than similar studies in the literature. By comparing the existing studies, we conclude that our approach provides a much better tool to determine a near-future paroxysmal atrial fibrillation episode. However, although the achieved benchmarks are impressive, we note that the approach needs to be supported by other studies and on other datasets before clinical trials.

The neuronal associations of respiratory-volume variability in the resting state

The desire to enhance the sensitivity and specificity of resting-state (rs-fMRI) measures has prompted substantial recent research into removing noise components. Chief among contributions to noise in rs-fMRI are physiological processes, and the neuronal implications of respiratory-volume variability (RVT), a main rs-fMRI-relevant physiological process, is incompletely understood. The potential implications of RVT in modulating and being modulated by autonomic nervous regulation, has yet to be fully understood by the rs-fMRI community. In this work, we use high-density electroencephalography (EEG) along with simultaneously acquired RVT recordings to help address this question. We hypothesize that (1) there is a significant relationship between EEG and RVT in multiple EEG bands, and (2) that this relationship varies by brain region. Our results confirm our first hypothesis, although all brain regions are shown to be equally implicated in RVT-related EEG-signal fluctuations. The lag between RVT and EEG is consistent with previously reported values. However, an interesting finding is related to the polarity of the correlation between RVT and EEG. Our results reveal potentially two main regimes of EEG-RVT association, one in which EEG leads RVT with a positive association between the two, and one in which RVT leads EEG but with a negative association between the two. We propose that these two patterns can be interpreted differently in terms of the involvement of higher cognition. These results further suggest that treating RVT simply as noise is likely a questionable practice, and that more work is needed to avoid discarding cognitively relevant information when performing physiological correction rs-fMRI.

The relationship between resting heart rate and aggression in males is racially variant

Although resting heart rate is thought to be a generalizable risk factor for aggression, very little research has examined whether this relationship varies by race. We addressed this limitation using longitudinal data from the Pittsburgh Youth Study. Current data are from 197 men who participated in a teenage biosocial study (mean age = 15.7 years) and adult follow-up study (mean age = 32.1 years). Teenage resting heart rate interacted with race to predict teenage and adult aggression. The relationship between heart rate and aggression was significant in White, but not in Black males. To our knowledge, this is the first study to find that the relationship between resting heart rate and aggression is racially variant, suggesting that resting heart rate may not be a generalizable biomarker for conduct problems. At an intervention-level, findings could contribute to the development of more accurate risk assessment tools that take into account racial variance in risk factors.

Comparing the cardiac autonomic activity profile of daytime naps and nighttime sleep

Heart rate variability (HRV) is a reliable technique to evaluate autonomic activity and shows marked changes across a night of sleep. Previous nighttime sleep findings report changes in HRV during non-rapid eye movement sleep (NREM), which have been associated with cardiovascular health benefits. Daytime sleep, however, has been linked with both positive and negative cardiovascular outcomes. Yet, no studies have directly compared HRV profiles during an ecologically-valid daytime nap in healthy, well-rested adults to that of nighttime sleep. Using a within-subjects design, 32 people took a daytime nap and slept overnight in the lab at least one week apart; both sleep sessions had polysomnography, including electrocardiography (ECG), recorded. We measured inter-beat intervals (RR), total power (TP), low frequency power (LF; .04-.15 Hz), and high frequency power (HF; .15-.40 Hz) components of HRV during NREM and rapid eye movement (REM) sleep. Compared to the nap, we found longer RR intervals and decreased heart rate during the night for both Stage 2 and SWS and increased TP, LF and HF power during nighttime Stage 2 sleep only; however, no differences in the LFHF ratio or normalized HF power were found between the nap and the night. Also, no differences in REM sleep between the nap and night were detected. Similar relationships emerged when comparing the nap to one cycle of nighttime sleep. These findings suggest that longer daytime naps, with both SWS and REM, may provide similar cardiovascular benefits as nocturnal sleep. In light of the on-going debate surrounding the health benefits and/or risks associated with napping, these results suggest that longer daytime naps in young, healthy adults may support cardiac down-regulation similar to nighttime sleep. In addition, napping paradigms may serve as tools to explore sleep-related changes in autonomic activity in both healthy and at-risk populations.

Modeling Affect Dynamics: State of the Art and Future Challenges

The current article aims to provide an up-to-date synopsis of available techniques to study affect dynamics using intensive longitudinal data (ILD). We do so by introducing the following eight dichotomies that help elucidate what kind of data one has, what process aspects are of interest, and what research questions are being considered: (1) single- versus multiple-person data; (2) univariate versus multivariate models; (3) stationary versus nonstationary models; (4) linear versus nonlinear models; (5) discrete time versus continuous time models; (6) discrete versus continuous variables; (7) time versus frequency domain; and (8) modeling the process versus computing descriptives. In addition, we discuss what we believe to be the most urging future challenges regarding the modeling of affect dynamics.

Cardiovascular state changes in simulated work environments

The usefulness of cardiovascular measures as indicators of changes in cognitive workload has been addressed in several studies. In this paper the question is explored whether cardiovascular patterns in heart rate, blood pressure, baroreflex sensitivity and HRV that are found are consistent within and between two simulated working environments. Two studies, were performed, both with 21 participants: one in an ambulance dispatch simulation and one in a driving simulator. In the ambulance dispatcher task an initial strong increase in blood pressure is followed by a moderate on-going increase in blood pressure during the next hour of task performance. This pattern is accompanied by a strong increase in baroreflex sensitivity while heart rate decreases. In the driving simulator study, blood pressure initially increases but decreases almost to baseline level in the next hour. This pattern is accompanied by a decrease in baroreflex sensitivity, while heart rate decreases. Results of both studies are interpreted in terms of autonomic control (related to both sympathetic and para-sympathetic effects), using a simplified simulation of a baroreflex regulation model. Interpretation of the results leads to the conclusion that the cardiovascular response patterns in both tasks are a combination of an initial defensive reaction, in combination with compensatory blood pressure control. The level of compensatory blood pressure control, however, is quite different for the two tasks. This helps to understand the differences in response patterns between the two studies in this paper and may be helpful as well for understanding differences in cardiovascular response patterns in general. A substantial part of the effects observed during task performance are regulatory effects and are not always directly related to workload manipulations. Making this distinction may also contribute to the understanding of differences in cardiovascular response patterns during cognitive workload.

A real-time automated point-process method for the detection and correction of erroneous and ectopic heartbeats

The presence of recurring arrhythmic events (also known as cardiac dysrhythmia or irregular heartbeats), as well as erroneous beat detection due to low signal quality, significantly affects estimation of both time and frequency domain indices of heart rate variability (HRV). A reliable, real-time classification and correction of ECG-derived heartbeats is a necessary prerequisite for an accurate online monitoring of HRV and cardiovascular control. We have developed a novel point-process-based method for real-time R-R interval error detection and correction. Given an R-wave event, we assume that the length of the next R-R interval follows a physiologically motivated, time-varying inverse Gaussian probability distribution. We then devise an instantaneous automated detection and correction procedure for erroneous and arrhythmic beats by using the information on the probability of occurrence of the observed beat provided by the model. We test our algorithm over two datasets from the PhysioNet archive. The Fantasia normal rhythm database is artificially corrupted with known erroneous beats to test both the detection procedure and correction procedure. The benchmark MIT-BIH Arrhythmia database is further considered to test the detection procedure of real arrhythmic events and compare it with results from previously published algorithms. Our automated algorithm represents an improvement over previous procedures, with best specificity for the detection of correct beats, as well as highest sensitivity to missed and extra beats, artificially misplaced beats, and for real arrhythmic events. A near-optimal heartbeat classification and correction, together with the ability to adapt to time-varying changes of heartbeat dynamics in an online fashion, may provide a solid base for building a more reliable real-time HRV monitoring device.

Statistical strategies to quantify respiratory sinus arrhythmia: are commonly used metrics equivalent?

Three frequently used RSA metrics are investigated to document violations of assumptions for parametric analyses, moderation by respiration, influences of nonstationarity, and sensitivity to vagal blockade. Although all metrics are highly correlated, new findings illustrate that the metrics are noticeably different on the above dimensions. Only one method conforms to the assumptions for parametric analyses, is not moderated by respiration, is not influenced by nonstationarity, and reliably generates stronger effect sizes. Moreover, this method is also the most sensitive to vagal blockade. Specific features of this method may provide insights into improving the statistical characteristics of other commonly used RSA metrics. These data provide the evidence to question, based on statistical grounds, published reports using particular metrics of RSA.

Dynamic Factor Analysis Models With Time-Varying Parameters

Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor model with vector autoregressive relations and time-varying cross-regression parameters at the factor level. Using techniques drawn from the state-space literature, the model was fitted to a set of daily affect data (over 71 days) from 10 participants who had been diagnosed with Parkinson's disease. Our empirical results lend partial support and some potential refinement to the Dynamic Model of Activation with regard to how the time dependencies between positive and negative affects change over time. A simulation study is conducted to examine the performance of the proposed techniques when (a) changes in the time-varying parameters are represented using the true model of change, (b) supposedly time-invariant parameters are represented as time-varying, and

Dynamic infant-parent affect coupling during the face-to-face/still-face

We examined dynamic infant-parent affect coupling using the Face-to-Face/Still-Face (FFSF). The sample included 20 infants whose older siblings had been diagnosed with Autism Spectrum Disorders (ASD-sibs) and 18 infants with comparison siblings (COMP-sibs). A series of mixed effects bivariate autoregressive models was used to represent the self-regulation and interactive dynamics of infants and parents during the FFSF. Significant bidirectional affective coupling was found between infants and parents, with infant-to-parent coupling being more prominent than parent-to-infant coupling. Further analysis of within-dyad dynamics revealed ongoing changes in concurrent infant-parent linkages both within and between different FFSF episodes. The importance of considering both inter- and intradyad differences is discussed.

Noninvasive Psychophysiological Ambulatory Recordings

Rapid technical developments have greatly facilitated noninvasive 24-hour recording of physiological signals at relatively low costs, including blood pressure, activity of the autonomic nervous system, respiratory behavior, and activity of the hypothalamic-pituitary-adrenocortical axis. Ambulatory noninvasive recordings can be used to study the baseline levels of these physiological variables as well as their reactivity to naturalistic stressors. Levels and reactivity can be compared across groups differing in exposure to risk factors (e.g., stress, genotypes) or used to sharpen the clinical profile of individual subjects (e.g., in panic or somatoform disorders). The focus of the current paper is on the importance of a priori choices in study design and data analysis strategies when ambulatory recording specifically targets the reciprocal relationship between physiological and psychological events. These choices are illustrated with ambulatory-assessed indices of the cardiac autonomic nervous system, blood pressure, respiration, and cortisol secretion.

Comparison of time and frequency domain measures of RSA in ambulatory recordings

The extent to which various measures of ambulatory respiratory sinus arrhythmia (RSA) capture the same information across conditions in different subjects remains unclear. In this study the root mean square of successive differences (RMSSD), peak valley RSA (pvRSA), and high frequency power (HF power) were assessed during ambulatory recording in 84 subjects, of which 64 were retested after about 3 years. We used covariance structure modeling to test the equality of the correlations among three RSA measures over two test days and three conditions (daytime sitting or walking and nighttime sleep) and in groups with low, medium, and high mean heart rate (HR), or low, medium, and high mean respiration rate (RR). Results showed that ambulatory RMSSD, pvRSA, and HF power are highly correlated and that their correlation is stable across time, ambulatory conditions, and a wide range of resting HR and RR values. RMSSD appears to be the most cost-efficient measure of RSA.

The many metrics of cardiac chronotropy: a pragmatic primer and a brief comparison of metrics

This paper focuses on pragmatic issues in obtaining measures of cardiac vagal control, and overviews a set of freely available software tools for obtaining several widely used metrics that putatively reflect sympathetic and/or parasympathetic contributions to cardiac chronotropy. After an overview of those metrics, and a discussion of potential confounds and extraneous influences, an empirical examination of the relationships amongst these metrics is provided. This study examined 10 metrics in 96 unselected college students under conditions of resting baseline and serial paced arithmetic. Intercorrelations between metrics were very high. Factor analyses were conducted on the metrics reflecting variability in cardiac rate, once at baseline and again during mental arithmetic. Factor structure was highly stable across tasks, and included a factor that had high loadings of all variables except Toichi's "cardiac sympathetic index" (CSI), and a second factor that was defined predominantly by the CSI. Although generally highly correlated, the various metrics responded differently under challenge.

Quantification of the dynamic behavior over time of narrow-band components present in heart rate variability by means of the instantaneous amplitude and frequency

The statistical properties of the time- and frequency-domain characteristics of heart rate variability are known to vary over time. A method is presented to compute the time-varying spectral contents of the characteristic narrow-band frequency components of heart rate variability by means of the instantaneous amplitude and frequency at an optimal time resolution. The instantaneous frequency may show oscillatory, but also irregular periods in time. An index of the instantaneous bandwidth is computed to discriminate between oscillatory and irregular periods and to correct the instantaneous amplitude and frequency for irregular periods.

Regional cerebral blood flow correlates with heart period and high-frequency heart period variability during working-memory tasks: Implications for the cortical and subcortical regulation of cardiac autonomic activity

The aim of the present study was to characterize the functional relationships between behaviorally evoked regional brain activation and cardiac autonomic activity in humans. Concurrent estimates of regional cerebral blood flow (rCBF; obtained by positron emission tomography), heart period, and high-frequency heart period variability (HF-HPV; an indicator of cardiac parasympathetic activity) were examined in 93 adults (aged 50-70 years) who performed a series of increasingly difficult working-memory tasks. Increased task difficulty resulted in decreased heart period (indicating cardioacceleration) and decreased HF-HPV (indicating decreased cardiac parasympathetic activity). Task-induced decreases in heart period and HF-HPV were associated with concurrent increases and decreases in rCBF to cortical and subcortical brain regions that are speculated to regulate cardiac autonomic activity during behavioral processes: the medial-prefrontal, insular, and anterior cingulate cortices, the amygdala-hippocampal complex, and the cerebellum. These findings replicate and extend a small number of functional neuroimaging studies that suggest an important role for both cortical and subcortical brain systems in human cardiac autonomic regulation.

The instantaneous frequency of cardiovascular time series: a comparison of methods

The instantaneous frequency (IF) of cardiovascular time series is used to describe the time-varying spectral contents of the characteristic frequency bands that are of interest for psychophysiological and cardiovascular research. Four methods to compute IF of band-limited, monocomponent, and analytical cardiovascular time series were compared by means of simulated time series contaminated with additive noise. These four methods are: the method using the inverse Fourier transform of uncorrelated time-slices of the Wigner-Ville distribution, the discrete time-frequency transform, the circular mean direction of the time-slices of the Wigner-Ville distribution, and the central finite difference of the phase. The time resolution of the estimates is optimal and is inversely related to the bandwidth of the frequency components, as given by the uncertainty principle of Gabor. At periods in time where the signal fulfills the requirements of the model signal, the four estimates of IF are numerically equal; only the circular mean direction showed a slight deviation from the other estimates. Although the estimates of IF differ at sudden phase shifts at low amplitude, i.e. at points where the signal locally does not comply with the requirements of the model signal, overall the four methods produce comparable estimates of IF of a cardiovascular time series at an optimal time resolution.

Methodological considerations for the use of heart rate variability as a measure of pain reactivity in vulnerable infants

Measures of HR and HRV offer multiple indices of reactivity to painful events. These measures are particularly helpful in preterm and ill infants where distress signals are often nonspecific and ambiguous. HR is easy to acquire, and a variety of widely used techniques are available for processing it. In general, the neuroanatomic and neurophysiologic bases for pain perception are in place even in the most preterm infant and produce patterns of HR and HRV responses that are similar across multiple settings. Developmental and experiential factors related to preterm birth, however, may affect these HR responses. Furthermore, evaluation of ill infants in an NICU setting adds multiple contextual factors that potentially influence HR and HRV and alter their specificity as measures of pain. In some cases, it may appear that pain reactivity is reduced when, in fact, HR reactivity is only an expression of the biologic capacity to produce a response, not the presence of a response itself. The nature of the setting and the infant's health, developmental stage, and behavioral state all contribute to potentially altering HR responses to painful events in this setting. Thus, the methodology used and its application must be flexible. A variety of HRV analysis techniques may be needed to identify a variety of response patterns and mechanisms that influence pain reactivity. Furthermore, careful selection of HR epochs for stationarity, an understanding of the potential discordance between biologic and behavioral measures, the effects of medication, and an accounting for developmental differences that occur during a typical NICU course are all critical factors for investigators to be aware of. Understanding cardiovascular reactivity as a measure of response to painful events in vulnerable infants requires ongoing work.

An advanced detrending method with application to HRV analysis

An advanced, simple to use, detrending method to be used before heart rate variability analysis (HRV) is presented. The method is based on smoothness priors approach and operates like a time-varying finite-impulse response high-pass filter. The effect of the detrending on time- and frequency-domain analysis of HRV is studied.

The time-course of electrocardiographic interbeat interval dynamics in alcoholic subjects after short-term abstinence

Alcohol dependence has been correlated with decreases in heart rate variability. However, the time course of recovery of heart rate variability after cessation of alcohol consumption is unknown. We used electrocardiogram (ECG) data serially obtained from a population of detoxifying alcoholic subjects to determine the Hurst exponent of the ECG interbeat interval time series. Higher values of the Hurst exponent are associated with decreased heart rate variability when H< or =0.5. We tested a series of response-surface models relating the Hurst exponent (H) thus obtained to the following independent variables: the time interval T (days since last use of alcohol), A (age in years at time of admission), and gender. The best-fit model was: H(T)=(KA+H(m)T+H(f)T)/(1+T), F=5.2, P(F)</=0.01. Model parameters were: K=0.008+/-0.002 (mean+/-SEM); asymptotic H-values for males and females: H(m)=0.24+/-0.02 and H(f)=0.16+/-0.03, respectively, significantly different at P< or =0.05. Age was the strongest predictor of initial H-values in this alcoholic population sample.

Cumulative plot of heart rate variability spectrum assesses kinetics of action of cholinergic drugs in rats

A new approach to assess autonomic nervous system (ANS) activity and its response to drug action is presented. Our approach is based on the use of a cumulative plot of data obtained by power spectral analysis of heart rate variability, in defined frequency bands, during short time epochs (e.g., 2 min in rats). The substantial temporal variability in power evolving from the constant balancing nature of the ANS activity is minimized by this approach and produces a measurable index of ANS activity vs. time. The cumulative plot emphasizes the temporal response pattern of different components of the ANS and thereby facilitates the investigation of the kinetics of action of drugs affecting the ANS. We used this method to measure the activity of cholinergic drugs in freely moving Sabra rats. Bolus atropine doses between 0.5 and 2 mg/kg produced a similar magnitude of effect, reduction of the ascending slope by 0. 003 power units/h, whereas the duration of this effect was dose dependent. A lower atropine dose (0.1 mg/kg) or 0.5 mg/kg scopolamine elevated the slope (0.074 and 0.054 power units/h for 206 and 216 min, respectively). The method was used similarly to assess the interaction between cholinergic drugs. Pretreatment with pyridostigmine produced temporal blockage of the anticholinergic activity of atropine.

MESA: a new configuration for measuring electromagnetic field fluctuations

This paper describes how the multi-energy sensor array has been refitted to meet the needs of measuring geomagnetic and other types of electromagnetic phenomena in an environment. This portable laptop computer system was designed to measure the interaction of multiple frequencies with the psychological and physiological processes that underlie human exposure to electromagnetic fields across the spectra. New sensors and analytical software have been implemented in the new configuration.

Heart rate variability: origins, methods, and interpretive caveats

Components of heart rate variability have attracted considerable attention in psychology and medicine and have become important dependent measures in psychophysiology and behavioral medicine. Quantification and interpretation of heart rate variability, however, remain complex issues and are fraught with pitfalls. The present report (a) examines the physiological origins and mechanisms of heart rate variability, (b) considers quantitative approaches to measurement, and (c) highlights important caveats in the interpretation of heart rate variability. Summary guidelines for research in this area are outlined, and suggestions and prospects for future developments are considered.

Ambulatory measurement of respiratory sinus arrhythmia and respiration rate

The present study describes a device (AMD43) for ambulatory measurement of respiration rate and respiratory sinus arrhythmia from the combined electrocardiogram (ECG) and thoracic impedance signals. Respiratory time intervals derived from this ambulatory device closely corresponds to those derived from simultaneous recordings with a 'classical' laboratory set-up. Good cross-instrument comparison was also found for respiratory sinus arrhythmia parameters derived with both the peak-to-trough and spectral analyses methods. It is discussed how simultaneous measurement of respiration rate, respiratory sinus arrhythmia may be used to assess cardiac vagal tone in real-life situations.

Baroreflex sensitivity during noxious stimulation in vasovagal reactors to blood donation

Baroreflex sensitivity was assessed at rest and during constrictive pain in healthy males with and without a history of vasovagal reactions to blood donation. Continuous recordings of cardiac inter-beat interval and finger arterial pressure were obtained at rest and during repeated presentations of constrictive thigh-cuff stimulation. Baroreflex sensitivity (in msec/mm Hg) was computed according to the spontaneous sequence analysis method. Results indicated that vasovagal reactors exhibited significantly lower descending baroreflex sensitivity across all periods, and significantly lower ascending baroreflex sensitivity at rest. Baseline differences in ascending baroreflex sensitivity were eliminated during thigh-cuff stimulation, as vasovagal reactors exhibited increases in ascending baroreflex sensitivity while non-reactors exhibited decreases. These findings suggest that susceptibility to vasovagal reactions may be associated with individual differences in baroreflex sensitivity.

A BASIC program for the peak-to-valley estimation of respiratory sinus arrhythmia

A computer program for the automatic scoring of respiratory sinus arrhythmia (RSA) is described. The program uses the 'peak-to-valley' quantification of RSA. Data was collected on 20 subjects to determine the inter-rater reliability and efficiency of the program. Highly reliable estimates of RSA were found. Advantages and limitations of the program are discussed.

Heart rate and sustained attention during childhood: age changes in anticipatory heart rate, primary bradycardia, and respiratory sinus arrhythmia

This study examined age changes in three aspects of heart rate responsivity elicited in an auditory oddball task; anticipatory heart rate change, primary bradycardia, and respiratory sinus arrhythmia. Three age groups (5-, 7-, and 9-year-old boys) were presented with series of target (15%) and standard (85%) tones. The results were consistent with the findings reported previously in the adult literature. Heart rate decreased in anticipation of the target tone. The morphology of anticipatory deceleration was somewhat different for the 5-year-olds compared to the older children. Stimuli presented during the early part of the cardiac cycle induced added deceleration, but this primary bradycardia did not differ between age groups. Respiratory sinus arrhythmia did not discriminate between age groups but was suppressed during the performance of the oddball task relative to base level. It was concluded that these three aspects of heart rate responsivity show developmental constancy rather than change.

Parasympathetic nervous system control of heart rate responses to stress in offspring of hypertensives

The elevated heart rate response to stress in normotensive offspring of hypertensives (PH+) has been suggested to be a function of sympathetic nervous system activity. This study examined whether parasympathetic nervous system activity may also underlie familial differences in the heart rate response. Twenty-four subjects, half of whom were PH+, were exposed to four stressor tasks administered in counterbalanced order. Stressors were chosen based on previous research that suggested vagal contributions to the heart rate response. Stressors were a cold pack to the forehead, isometric hand grip, a noxious film, and a shock-avoidance video game task. Physiological measures included heart rate (HR), respiration rate (RR), and respiratory sinus arrhythmia (RSA). RSA values were corrected for corresponding RR by analysis of covariance. Familial differences in HR were observed in response to the hand grip and video game tasks. However, in both cases analyses suggest that familial differences in reactivity were a function of primarily sympathetic as opposed to parasympathetic influences. Familial differences in RSA were not observed for rest or tasks. This study found no evidence for parasympathetic mediation of familial differences in the heart rate response to the stressors employed.

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 environments and the specific problems inherent in such situations are discussed.