Sergio Cerutti

Assessment of the neural control of the circulation during psychological stress

In this study, we used spectral analysis of short-term R-R and systolic arterial pressure (SAP) variabilities to estimate the changes in neural control of the circulation produced by psychological stress. The 0.1 Hz low-frequency (LF) component of R-R and SAP variabilities provided a quantitative index of the sympathetic activity controlling heart rate and vasomotion. Conversely the high-frequency (HF) respiratory component of R-R variability provided an index of vagal tone. In conscious dogs we used the seemingly stressful situation of being accompanied for the first time to the experimental laboratory as a stimulus. In human subjects we used mental arithmetic. In both cases LF of R-R and SAP variabilities increased significantly suggesting enhanced sympathetic activity both to the SA node and the vasculature. In man, the index alpha, a measure of the overall gain of baroreceptor mechanisms, was found to be reduced during mental arithmetic. Spectral analysis of cardiovascular variabilities thus suggests that in man and in conscious dogs psychological challenges induce a profound re-arrangement of neural control of the circulation, which appears to be characterised by sympathetic predominance and which can be monitored by this technique.

Autonomic Changes During Hypnosis: A Heart Rate Variability Power Spectrum Analysis as a Marker of Sympatho-Vagal Balance

Spectral analysis of beat-to-beat variability in electrocardiography is a simple, noninvasive method to analyze sympatho-vagal interaction. The electrocardiogram is analyzed by means of an automatic, autoregressive modeling algorithm that provides a quantitative estimate of R-R interval variability by the computation of power spectral density. Two major peaks are recognizable in this specter: a low-frequency peak (LF, -0.1 Hz), related to the overall autonomic activity (ortho+parasympathetic) and a high-frequency peak (HF, -0.25 Hz), representative of the vagal activity. The LF/HF ratio is an index of the sympatho-vagal interaction. This technique was applied, using a computer-assisted electrocardiograph, to 10 healthy volunteers (6 high and 4 low hypnotizable subjects as determined by the Stanford Hypnotic Susceptibility Scale, Form C) in randomized awake and neutral hypnosis conditions. Preliminary results indicated that hypnosis affects heart rate variability, shifting the balance of the sympatho-vagal interaction toward an enhanced parasympathetic activity, concomitant with a reduction of the sympathetic tone. A positive correlation between hypnotic susceptibility and autonomic responsiveness during hypnosis was also found, with high hypnotizable subjects showing a trend toward a greater increase of vagal efferent activity than did low hypnotizables.

Identification techniques applied to processing of signals from cardiovascular systems.

The analysis of variability signals bound to the pathophysiology of cardiovascular systems is a technique of growing interest for the evaluation of the influences of endogenous and exogenous control mechanisms, and constitutes fundamental information in physiological research. It is also of growing interest for clinical purposes (i.e. when monitoring the critically ill patient or in the diagnostic phase of various cardiac pathologies). The information contained in the signals constituted by the R-R duration time series, blood pressure, respiration, etc., must be appropriately treated to reveal the extremely complicated interconnections between them. Methodologies for the analysis of heart rate variability (HRV) have been introduced in the literature using either the classical analysis algorithms or advanced ones of higher order [l-61. Such algorithms appear extremely promising, as they provide physicians and researchers with quantitative means for the monitoring of biological signal variability and a unitary approach to simultaneous parameter extraction from signals of different origin. In the present paper only a few preliminary results are presented: others are covered in the literature [7-91. The application fields discussed here are the study of neural control mechanisms on HRV and blood pressure, and parameter extraction from R-R signals of arrhythmic patients (MIT-BIH data base). An important issue revealed by the research is that by introducing the proper identification and stochastic modelling methodologies (AR/ARMA models) it is possible to obtain some parameters which provide quantitative means of measuring a few typical influences elicited by the control systems on the series of signals. The complexity of the various connections may not be obviously overcome but, on the other hand, this kind of black-box modelling allows the correlation of parameters obtained from the signal processing phase with other parameters of neurophysiological interest. The parallel progress of research in physiological mechanisms of interaction and in new advanced methods of signal processing and parameter extrcction is certainly important and promising for the comprehension of numerous phenomena which are extremely difficult to treat by the traditional approaches.

Parameter extraction in EEG processing during riskful neurosurgical operations

Abstract An advanced methodology of EEG parameter extraction is presented. This has been used during riskful surgical interventions i.e. intracranial aneurysm clipping in controlled hypotension through continuous infusion of sodium nitroprusside, SNP. The signal is processed using an AR-modelling approach and the information is shown in the form of pole diagram, power density spectrum estimation, and plotting of the identification coefficients. Some advantages of the previously reported techniques are discussed in respect to the more traditional approaches (e.g. FFT algorithms). Important applications are also foreseen in the field of neurophysiological research and clinical neurology.

Spectral analysis of short-term heart rate variability in diabetic patients.

Spectral analysis of short term R-R variability estimated by autoregressive modelling is a recently developed method for the evaluation of cardiovascular autonomic function. This new test also allows to study the interaction on heart rate variability of parasympathetic and sympathetic system. The sensitivity of the method for detection of cardiovascular autonomic neuropathy has been evaluated in a group of diabetic patients in comparison with the sensitivity of a battery of the most commonly used cardiovascular autonomic tests (deep-breathing, lying-to-standing, Valsalva Manoeuvre, postural hypotension and hand grip). Spectral analysis of heart rate variability resulted in a very sensitive method for early detection of diabetic autonomic neuropathy, about one-fourth of diabetic patients with normal traditional cardiovascular autonomic tests had abnormal results at spectral analysis. Both sympathetic and vagal control of heart rate resulted alterated in diabetic autonomic neuropathy.

Power spectrum analysis of heart rate variability signal in the diagnosis of diabetic neuropathy

A clinical test based on the cross-spectral analysis of heart-rate variability (HRV obtained from ECG) and respiration is proposed for the assessment of autonomic diabetic neuropathy. The analysis was performed by means of an autoregressive model in bivariate form, and autospectra, cross spectra, and squared coherence functions were evaluated. Spectral parameters and, in particular, the power of the HRV signal which is coherent and which is not coherent with respiration are considered during different physiological conditions. In a first step, a group of 20 normal subjects underwent this test and ranges of normality were obtained for each parameter. In a second step, diabetic patients were analyzed and the obtained values of the spectral parameters were compared with the normality ranges. The proposed test recognizes patients with neuropathy and gives an earlier diagnosis of a compromission of the autonomic nervous system.<<ETX>>

Spectral Analysis of Cardiovascular Variability Signals

It is well known that the control mechanisms of heart rate and blood pressure, as well as of many other cardiovascular parameters, manifest themselves though beat-to-beat variations in the related signals1,2. The quantification of these variations, both in control conditions and after provocative tests, plays a fundamental role for a better comprehension of the pathophysiological properties of such mechanisms which act through neural, mechanical, vascular, humoral and other factors.

Single Sweep Analysis of Evoked and Event Related Potentials

Different approaches of single sweep analysis of evoked and event related potentials are presented. The autoregressive with eXogenous input (ARX) model is described with different applications in the study of dynamical changes of the brain responses and in artifact removal. A study of the modifications induced in the EEG by a sensory stimulation via ARX and AR models is also described. Finally, the wavelet transform is employed for the reconstruction of the single evoked response.