Five-Year Longitudinal Study of Neck Vessel Cross-Sectional Area in Multiple Sclerosis

BACKGROUND AND PURPOSE

Alterations of neck vessel cross-sectional area in multiple sclerosis have been reported. Our aim was to investigate the evolution of the neck vessel cross-sectional area in patients with MS and healthy controls during 5 years.

MATERIALS AND METHODS

Sixty-nine patients with MS (44 relapsing-remitting MS, 25 progressive MS) and 22 age- and sex-matched healthy controls were examined twice, 5 years apart, on a 3T MR imaging scanner using 2D neck MR angiography. Cross-sectional areas were computed for the common carotid/internal carotid arteries, vertebral arteries, and internal jugular veins for all slices between the C3 and C7 cervical levels. Longitudinal cross-sectional area differences at each cervical level and the whole-vessel course were tested within study groups and between patients with MS with and without cardiovascular disease using mixed-model analysis and the related-samples Wilcoxon singed rank test. The Benjamini-Hochberg procedure was performed to correct for multiple comparisons.

RESULTS

No significant cross-sectional area differences were seen between patients with MS and healthy controls at baseline or at follow-up. During the follow-up, significant cross-sectional area decrease was found in patients with MS for the common carotid artery-ICAs (C4: P = .048; C7: P = .005; whole vessel: P = .012), for vertebral arteries (C3: P = .028; C4: P = .028; C7: P = .028; whole vessel: P = .012), and for the internal jugular veins (C3: P = .014; C4: P = .008; C5: P = .010; C6: P = .010; C7: P = .008; whole vessel: P = .002). Patients with MS without cardiovascular disease had significantly greater change than patients with MS with cardiovascular disease for internal jugular veins at all levels.

CONCLUSIONS

For 5 years, patients with MS showed significant cross-sectional area decrease of all major neck vessels, regardless of the disease course and cardiovascular status.

Mortality prediction in septic shock patients: Towards new personalized models in critical care

We studied the problem of mortality prediction in 23 septic shock patients selected from the public database MIMIC-II. For each patient we derived hemodynamic variables, laboratory results and clinical information of the first 48 hours after shock onset and we performed univariate and multivariate analyses to predict mortality in the following 7 days. The results show interesting features that individually identify significant differences between survivors and non survivors and features which gain importance only when considered together with the others in a multivariate regression model, such as the respiratory rate (RR). This preliminary study on a small septic shock population represents a novel contribution towards new personalized models for an integration of multi-scale and multi-level patient information to improve critical care management of shock patients.

Non-Linear Dynamics in the Beat-to-Beat Variability of Sympathetic Activity in Decerebrate Cats

Non-linear interactions between low-frequency rhythms (0.1 Hz) of beat-to-beat variability series of sympathetic discharge and respiratory rhythm (0.3 Hz) are observed in decerebrate artificially ventilated cats. Simple graphical tools as Poincare and recurrence maps are used to detect, in a qualitative way, phase-locking phenomena. Non-parametric bispectral analysis is also carried out to quantify the degree of second-order coupling between oscillations at different frequencies.

Mapping temporo-parietal and temporo-occipital cortico-cortical connections of the human middle longitudinal fascicle in subject-specific, probabilistic, and stereotaxic Talairach spaces

Originally, the middle longitudinal fascicle (MdLF) was defined as a long association fiber tract connecting the superior temporal gyrus and temporal pole with the angular gyrus. More recently its description has been expanded to include all long postrolandic cortico-cortical association connections of the superior temporal gyrus and dorsal temporal pole with the parietal and occipital lobes. Despite its location and size, which makes MdLF one of the most prominent cerebral association fiber tracts, its discovery in humans is recent. Given the absence of a gold standard in humans for this fiber tract, its precise and complete connectivity remains to be determined with certainty. In this study using high angular resolution diffusion MRI (HARDI), we delineated for the first time, six major fiber connections of the human MdLF, four of which are temporo-parietal and two temporo-occipital, by examining morphology, topography, cortical connections, biophysical measures, volume and length in seventy brains. Considering the cortical affiliations of the different connections of MdLF we suggested that this fiber tract may be related to language, attention and integrative higher level visual and auditory processing associated functions. Furthermore, given the extensive connectivity provided to superior temporal gyrus and temporal pole with the parietal and occipital lobes, MdLF may be involved in several neurological and psychiatric conditions such as primary progressive aphasia and other aphasic syndromes, some forms of behavioral variant of frontotemporal dementia, atypical forms of Alzheimer's disease, corticobasal degeneration, schizophrenia as well as attention-deficit/hyperactivity Disorder and neglect disorders.

Preliminary profiling of blood transcriptome in a rat model of hemorrhagic shock

Hemorrhagic shock is a leading cause of morbidity and mortality worldwide. Significant blood loss may lead to decreased blood pressure and inadequate tissue perfusion with resultant organ failure and death, even after replacement of lost blood volume. One reason for this high acuity is that the fundamental mechanisms of shock are poorly understood. Proteomic and metabolomic approaches have been used to investigate the molecular events occurring in hemorrhagic shock but, to our knowledge, a systematic analysis of the transcriptomic profile is missing. Therefore, a pilot analysis using paired-end RNA sequencing was used to identify changes that occur in the blood transcriptome of rats subjected to hemorrhagic shock after blood reinfusion. Hemorrhagic shock was induced using a Wigger's shock model. The transcriptome of whole blood from shocked animals shows modulation of genes related to inflammation and immune response (Tlr13, Il1b, Ccl6, Lgals3), antioxidant functions (Mt2A, Mt1), tissue injury and repair pathways (Gpnmb, Trim72) and lipid mediators (Alox5ap, Ltb4r, Ptger2) compared with control animals. These findings are congruent with results obtained in hemorrhagic shock analysis by other authors using metabolomics and proteomics. The analysis of blood transcriptome may be a valuable tool to understand the biological changes occurring in hemorrhagic shock and a promising approach for the identification of novel biomarkers and therapeutic targets. Impact statement This study provides the first pilot analysis of the changes occurring in transcriptome expression of whole blood in hemorrhagic shock (HS) rats. We showed that the analysis of blood transcriptome is a useful approach to investigate pathways and functional alterations in this disease condition. This pilot study encourages the possible application of transcriptome analysis in the clinical setting, for the molecular profiling of whole blood in HS patients.

Individual Thresholding of Voxel-based Functional Connectivity Maps. Estimation of Random Errors by Means of Surrogate Time Series

INTRODUCTION

This article is part of the Focus Theme of Methods of Information in Medicine on "Biosignal Interpretation: Advanced Methods for Neural Signals and Images".

BACKGROUND

Voxel-based functional connectivity analysis is a common method for resting state fMRI data. However, correlations between the seed and other brain voxels are corrupted by random estimate errors yielding false connections within the functional connectivity map (FCmap). These errors must be taken into account for a correct interpretation of single-subject results.

OBJECTIVES

We estimated the statistical range of random errors and propose two methods for an individual setting of correlation threshold for FCmaps.

METHODS

We assessed the amount of random errors by means of surrogate time series and described its distribution within the brain. On the basis of these results, the FCmaps of the posterior cingulate cortex (PCC) from 15 healthy subjects were thresholded with two innovative methods: the first one consisted in the computation of a unique (global) threshold value to be applied to all brain voxels, while the second method is to set a different (local) threshold of each voxel of the FCmap.

RESULTS

The distribution of random errors within the brain was observed to be homogeneous and, after thresholding with both methods, the default mode network areas were well identifiable. The two methods yielded similar results, however the application of a global threshold to all brain voxels requires a reduced computational load. The inter-subject variability of the global threshold was observed to be very low and not correlated with age. Global threshold values are also almost independent from the number of surrogates used for their computation, so the analyses can be optimized using a reduced number of surrogate time series.

CONCLUSIONS

We demonstrated the efficacy of FCmaps thresholding based on random error estimation. This method can be used for a reliable single-subject analysis and could also be applied in clinical setting, to compute individual measures of disease progression or quantitative response to pharmacological or rehabilitation treatments.

Cardiac output is not a significant source of low frequency mean arterial pressure variability

Spontaneous mean arterial pressure (MAP) variability may be mainly due to fluctuations in cardiac output (CO) and total peripheral resistance (TPR). While high frequency (HF ∼ 0.25 Hz) oscillations in MAP are ultimately driven by respiration, the source of low frequency (LF ∼ 0.1 Hz) fluctuations has not been fully elucidated. It is known that CO buffers these oscillations, but there is no evidence on its potential role in also generating them. The main goal was to determine whether CO is a source of LF variability in MAP. Six dogs were chronically instrumented to obtain beat-to-beat measurements of CO and MAP while the dogs were fully awake and at rest. A causal dynamic model was identified to relate the fluctuations in CO to MAP. The model was then used to predict the MAP fluctuations from the CO fluctuations. The CO fluctuations were able to predict about 70% of the MAP oscillations in the HF band but showed no predictive value in the LF band. Hence, respiration induces CO fluctuations in the HF band that, in turn, cause MAP oscillations, while TPR fluctuations appear to be the dominant mediator of LF fluctuations of MAP. CO is not a significant source of these oscillations, and it may only be responsible for dampening them, likely through the baroreflex.

Human middle longitudinal fascicle: variations in patterns of anatomical connections

Based on high-resolution diffusion tensor magnetic resonance imaging (DTI) tractographic analyses in 39 healthy adult subjects, we derived patterns of connections and measures of volume and biophysical parameters, such as fractional anisotropy (FA) for the human middle longitudinal fascicle (MdLF). Compared to previous studies, we found that the cortical connections of the MdLF in humans appear to go beyond the superior temporal (STG) and angular (AG) gyri, extending to the temporal pole (TP), superior parietal lobule (SPL), supramarginal gyrus, precuneus and the occipital lobe (including the cuneus and lateral occipital areas). Importantly, the MdLF showed a striking lateralized pattern with predominant connections between the TP, STG and AG on the left and TP, STG and SPL on the right hemisphere. In light of the results of the present study, and of the known functional role of the cortical areas interconnected by the MdLF, we suggested that this fiber pathway might be related to language, high order auditory association, visuospatial and attention functions.

Interferences between baroreflex and respiration. Evaluation by symbolic analysis and conditional entropy

BACKGROUND

The baroreflex is one of the most important short-term cardiovascular autonomic control mechanisms. Its interactions with other reflexes, mainly cardiopulmonary reflexes, are of paramount importance in controlling heart rate.

OBJECTIVES

This study assesses the coupling between baroreflex and respiration during a progressive bicycle mild dynamical exercise.

METHODS

The coupling was assessed by symbolic analysis and conditional entropy.

RESULTS

Findings suggested the close relationship between the baroreflex sequences and the phase of respiratory signal and, thus, the interference between baroreflex and cardiopulmonary reflexes.

CONCLUSIONS

Indexes describing baroreflex based on spontaneous variability are strongly affected by cardiopulmonary influences.

ML segmentation strategies for object interference compensation in FDG-PET lesion quantification

BACKGROUND

Quantification of lesion activity by FDG uptake in oncological PET is severely limited by partial volume effects. A maximum likelihood (ML) expectation maximization (EM) algorithm considering regional basis functions (AWOSEM-region) had been previously developed. Regional basis functions are iteratively segmented and quantified, thus identifying the volume and the activity of the lesion.

OBJECTIVES

Improvement of AWOSEM-region when analyzing proximal interfering hot objects is addressed by proper segmentation initialization steps and models of spill-out and partial volume effects. Conditions relevant to lung PET-CT studies are considered: 1) lesion close to hot organ (e.g. chest wall, heart and mediastinum), 2) two close lesions.

METHODS

CT image was considered for pre-segmenting hot anatomical structures, never for lesion identification, solely defined by iterations on PET data. Further resolution recovery beyond the smooth standard clinical image was necessary to start lesion segmentation. A watershed algorithm was used to separate two close lesions. A subtraction of the spill-out from a nearby hot organ was introduced to enhance a lesion for the initial segmentation and start the further quantification steps. Biograph scanner blurring was modeled from phantom data in order to implement the procedure for 3D clinical lung studies.

RESULTS

In simulations, the procedure was able to separate structures as close as one pixel-size (2.25 mm). Robustness against the input segmentation errors defining the addressed objects was tested showing that convergence was not sensitive to initial volume overestimates up to 130%. Poor robustness was found against underestimates. A clinical study of a small lung lesion close to chest wall displayed a good recovery of both lesion activity and volume.

CONCLUSIONS

With proper initialization and models of spill-out from hot organs, AWOSEM-region can be successfully applied to lung oncological studies.

DTI parameter optimisation for acquisition at 1.5T: SNR analysis and clinical application

BACKGROUND

Magnetic Resonance (MR) diffusion tensor imaging (DTI) is able to quantify in vivo tissue microstructure properties and to detect disease related pathology of the central nervous system. Nevertheless, DTI is limited by low spatial resolution associated with its low signal-to-noise-ratio (SNR).

AIM

The aim is to select a DTI sequence for brain clinical studies, optimizing SNR and resolution.

METHODS AND RESULTS

We applied 6 methods for SNR computation in 26 DTI sequences with different parameters using 4 healthy volunteers (HV). We choosed two DTI sequences for their high SNR, they differed by voxel size and b-value. Subsequently, the two selected sequences were acquired from 30 multiple sclerosis (MS) patients with different disability and lesion load and 18 age matched HV. We observed high concordance between mean diffusivity (MD) and fractional anysotropy (FA), nonetheless the DTI sequence with smaller voxel size displayed a better correlation with disease progression, despite a slightly lower SNR. The reliability of corpus callosum (CC) fiber tracking with the chosen DTI sequences was also tested.

CONCLUSIONS

The sensitivity of DTI-derived indices to MS-related tissue abnormalities indicates that the optimized sequence may be a powerful tool in studies aimed at monitoring the disease course and severity.

Atlas-based vs. individual-based deterministic tractography of corpus callosum in multiple sclerosis

Diffusion tensor (DT) magnetic resonance imaging is able to quantify tissue microstructure properties and to detect pathological changes even in the normal appearing tissues. DT sequence parameters which provide optimal SNR and minimum acquisition time, and an individual-based tractography post-processing allowed corpus callosum tractography even in multiple sclerosis (MS) patients also with no need of a-priori atlas. In this preliminary study, we were able to obtain reliable individual-based tractography in 28/30 MS patients. DT-derived indices computed in tracks obtained with individual-based tractography were able to differentiate healthy volunteers from MS patients better than the same indices computed with the atlas method. This indicates that such an optimized sequence may be a reliable tool to be used in future MS studies.

Biomedical engineering education at Politecnico di Milano: Development and recent changes

The biomedical engineering (BME) programme at the Politecnico di Milano (POLIMI) is characterized by a strong interdisciplinary background in a broad range of engineering subjects applied to biology and medicine. Accordingly, the undergraduate level (3 years) provides a general education, which includes mechanics, chemistry and materials, electronics, and information technology both in the context of general engineering and within BME foundations. In contrast, the postgraduate programme (2 years) offers a broad choice of specializations in BME fields in close connection with the BME research activities and laboratories of the campus and with active interchange with the other engineering disciplines. The history of BME development at POLIMI is briefly recalled, together with the characteristics of educational and research work, which is strongly biased by a large polytechnic university with no medical school within the same campus; points of strength and weakness due to this background are discussed. The introduction of a double cycle (undergraduate and postgraduate) according to the Bologna process (2000) and the effects on the programme structure is considered. An early phase in which professional education was emphasized at undergraduate level is recalled, which was followed by the actual revision fostering basic engineering and BME education at the first level while leaving in-depth specialization to postgraduate studies or to on-the-job training.

Influence of cochlear implant-like operating conditions on wavelet speech processing

This study assessed the influence of 'non-ideal' operating conditions typical of cochlear implants (CIs) on the behavior of the wavelet transform (WT) when used to process speech. Particular attention was given to the effect of limited stimulation rate and limited number of channels, typical of CI speech processing, on the performance of the WT. Computer simulations and psychoacoustic recognition tests of WT-processed speech were implemented. The crucial role played by the 'non-ideal' operating conditions on WT speech processing was put in evidence. Psychoacoustic recognition tests proved to be fundamental to evaluate feasibility of WT speech processing for CIs.

Model of arterial tree and peripheral control for the study of physiological and assisted circulation

Peripheral vasomotion, interstitial liquid exchange, and cardiovascular system behaviour are investigated by means of a lumped parameter model of the systemic and peripheral circulation, from the aortic valve to the venules. This modelling work aims at combining arterial tree hemodynamics description, active peripheral flow regulation, and fluid exchange. The arterial compartment is constructed with 63 RCL segments and 30 peripheral districts including myogenic control on arterioles, metabolic control on venules, and Starling filtration through capillary membrane. The arterial behaviour is characterised as to the long term stability of pressure/flow waves in the different segments. Peripheral districts show autoregulatory capabilities against pressure changes over a wide range and also self-sustained oscillations mimicking vasomotor activity. A preliminary study was carried out as to the model response to changes induced by cardiopulmonary bypass (CPB). Among the induced alterations, the system responds mainly to hemodilution, which increased peripheral fluid loss and oedema beyond the compensatory capabilities of local regulation mechanisms. This resulted in an overall increase total arterial resistance. Local transport deficits were assessed for each district according to the different metabolic demand. This study shows the requirement of a suitable description of both arteries and peripheral mechanisms in order to describe cardiovascular response non-physiological conditions, as well as assisted circulation or other pathological conditions.

Applying 2D ML iterative reconstruction methods with resolution recovery to 3D PET data: evaluation of rebinning effects

The applicability of OSEM reconstruction algorithms with space dependent resolution recovery to clinical FDG-PET studies is verified. The performance of the 2D algorithm is improved by means of a low resolution initialization and by a infra-iteration Metz filtering. Effects of different rebinning algorithms on 3D data are assessed, concluding that they do not alter the transaxial plane blurring parameters, thus permitting a straightforward application of 2D OSEM reconstruction after rebinning, with the same system matrix. Finally axial degradation was also quantified, finding that FORE is the best rebinning method to be combined with the 2D OSEM reconstruction.

Dopamine-dependent non-linear correlation between subthalamic rhythms in Parkinson's disease

The basic information architecture in the basal ganglia circuit is under debate. Whereas anatomical studies quantify extensive convergence/divergence patterns in the circuit, suggesting an information sharing scheme, neurophysiological studies report an absence of linear correlation between single neurones in normal animals, suggesting a segregated parallel processing scheme. In 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated monkeys and in parkinsonian patients single neurones become linearly correlated, thus leading to a loss of segregation between neurones. Here we propose a possible integrative solution to this debate, by extending the concept of functional segregation from the cellular level to the network level. To this end, we recorded local field potentials (LFPs) from electrodes implanted for deep brain stimulation (DBS) in the subthalamic nucleus (STN) of parkinsonian patients. By applying bispectral analysis, we found that in the absence of dopamine stimulation STN LFP rhythms became non-linearly correlated, thus leading to a loss of segregation between rhythms. Non-linear correlation was particularly consistent between the low-beta rhythm (13-20 Hz) and the high-beta rhythm (20-35 Hz). Levodopa administration significantly decreased these non-linear correlations, therefore increasing segregation between rhythms. These results suggest that the extensive convergence/divergence in the basal ganglia circuit is physiologically necessary to sustain LFP rhythms distributed in large ensembles of neurones, but is not sufficient to induce correlated firing between neurone pairs. Conversely, loss of dopamine generates pathological linear correlation between neurone pairs, alters the patterns within LFP rhythms, and induces non-linear correlation between LFP rhythms operating at different frequencies. The pathophysiology of information processing in the human basal ganglia therefore involves not only activities of individual rhythms, but also interactions between rhythms.

Preliminary study on the use of nonrigid registration for thoraco-abdominal radiosurgery

The inclusion of organ deformation and movement in radiosurgery treatment planning is of increasing importance as research and clinical applications begin to take into consideration the effects of physiological processes, like breathing, on the shape and position of lesions. In this scenario, the challenge is to localize the target in toto (not only by means of marker sampling) and to calculate the dose distribution as the sum of all the contributions from the positions assumed by the target during the respiratory cycle. The aim of this work is to investigate the use of nonrigid registration for target tracking and dynamic treatment planning, i.e., treatment planning based not on one single CT scan but on multiple CT scans representative of the respiration. Twenty patients were CT scanned at end-inhale and end-exhale. An expert radiation oncologist identified the PTV in both examinations. The two CT data sets per patient were nonrigidly registered using a free-form deformation algorithm based on B-splines. The optimized objective function consisted of a weighted sum of a similarity criterion (Mutual Information) and a regularization factor which constrains the transformation to be locally rigid. Once the transformation was obtained and the registration validated, its parameters were applied to the target only. Finally, the deformed target was compared to the PTV delineated by the radiation oncologist in the other study. The results of this procedure show an agreement between the center of mass as well as volume of the target identified automatically by deformable registration and manually by the radiation oncologist. Moreover, obtained displacements were in agreement with body structure constraints and considerations usually accepted in radiation therapy practice. No significant influence of initial target volume on displacements was found. In conclusion, the proposed method seems to offer the possibility of using nonrigid registrations in radiosurgery treatment planning, even if more cases need to be investigated in order to give a statistical consistency to parameter setup and proposed considerations.

Movement-related frequency modulation of beta oscillatory activity in the human subthalamic nucleus

Event-related changes of brain electrical rhythms are typically analysed as amplitude modulations of local field potential (LFP) oscillations, like radio amplitude modulation broadcasting. In telecommunications, frequency modulation (FM) is less susceptible to interference than amplitude modulation (AM) and is therefore preferred for high-fidelity transmissions. Here we hypothesized that LFP rhythms detected from deep brain stimulation (DBS) electrodes implanted in the subthalamic nucleus (STN) in patients with Parkinson's disease could represent movement-related activity not only in AM but also in FM. By combining adaptive autoregressive identification with spectral power decomposition, we were able to show that FM of low-beta (13-20 Hz) and high-beta (20-35 Hz) rhythms significantly contributes to the involvement of the human STN in movement preparation, execution and recovery, and that the FM patterns are regulated by the dopamine levels in the system. Movement-related FM of beta oscillatory activity in the human subthalamic nucleus therefore provides a novel informational domain for rhythm-based pathophysiological models of cortico-basal ganglia processing.

Altered subthalamo-pallidal synchronisation in parkinsonian dyskinesias

The aim of this work was to study the role of subthalamo-pallidal synchronisation in the pathophysiology of dyskinesias. We recorded local field potentials (LFPs) in a patient with Parkinson's disease and left surgery induced dyskinesias with double, bilateral deep brain stimulation electrode implants in the subthalamic nucleus (STN) and the globus pallidus internus (GPi). Synchronisation was studied through coherence analysis. In the nuclei contralateral to the dyskinetic side of the body there was decreased STN-GPi coherence in the high beta range (20-30 Hz) and an enhanced coherence at low frequencies (<10 Hz). Despite the possible limitations arising from single-case observations, our findings suggest that parkinsonian dyskinesias are related to altered synchronisation between different structures of the basal ganglia. Firing abnormalities within individual basal ganglia nuclei are probably not enough to account for the complex balance between hypokinetic and hyperkinetic symptoms in human parkinsonian dyskinesias and altered interactions between nuclei should also be considered.

An adaptive neuro-fuzzy method (ANFIS) for estimating single-trial movement-related potentials

This study aims to recover transient, trial-varying evoked potentials (EPs), in particular the movement-related potentials (MRPs), embedded within the background cerebral activity at very low signal-to-noise ratios (SNRs). A new adaptive neuro-fuzzy technique will attempt to estimate movement-related potentials within multi-channel EEG recordings, enabling this method to completely adapt to each input sweep without system training procedures. We assume that one of the sensors is corrupted by noise deriving from other sensors via an unknown function that will be estimated. We will approach this problem by: (1) spatially decorrelating the sensors in the preprocessing phase, (2) choosing the most informative of the filtered channels that will permit the best MRP estimation (input-selection phase) and (3) training the neuro-fuzzy model to fit the noise over the chosen sensor and therefore estimating the buried MRP. We tested this framework with simulations to validate the analytical results before applying them to the real biological data. Whenever it is applied to biological data, this method improves the SNR by more than 12 dB, even to very low SNRs. The processing method proposed here is likely to complement other estimation techniques and can be useful to process, enhance and analyse single-trial MRPs.

The subthalamic nucleus in Parkinson?s disease: power spectral density analysis of neural intraoperative signals

To test a new tool for the neurophysiological identification of the human subthalamic nucleus (STN) during stereotactic surgery for the implantation of deep-brain-stimulation (DBS) electrodes, we analysed off-line the intraoperative signals recorded from patients with Parkinson's disease. We estimated the power spectral density (PSD) along each penetration track (8 patients, 13 sides) and determined the spatial correlation of the PSD with the target location estimated from neuroimaging procedures ("anatomical target"), and with the final target location derived from standard intraoperative neurophysiological procedures for STN localization ("clinical target"). At each step we recorded the 'on-line' signal for 120 seconds; because the PSD was estimated by calculating the periodogram for 6-second epochs of neural signal, we had 20 epochs at each step. When the electrode track crossed the STN, the PSD in the 0.25-2.5 kHz band increased, peaking on average <0.5 mm cranial to the clinical target and 1.00+/-1.51 mm caudal to the anatomical target. When the track was outside the nucleus, the PSD remained unchanged. Even on recordings with low signal-to-noise ratio, off-line PSD analysis of neural signals showed a good correspondence with the target indicated by the surgical team. On-line intraoperative estimation of the PSD may be a simple, reliable, rapid and complementary approach to electrophysiological monitoring during STN surgery for Parkinson's disease.

Non-invasive model-based estimation of the sinus node dynamic properties from spontaneous cardiovascular variability series

A non-invasive model-based approach to the estimation of sinus node dynamic properties is proposed. The model exploits the spontaneous beat-to-beat variability of heart period and systolic arterial pressure and the sampled respiration, thus surrogating the information from direct measures of neural activity. The residual heart period variability not related to baroreflex, to direct effects of respiration and to low frequency influences independent of baroreflex, is interpreted as the effect of the dynamic properties of the sinus node and modelled as a regression of the RR interval over its previous value. Therefore the sinus node transfer function is modelled by means of a filter with a real pole z = mu (and a zero in the origin). It was found that: first, in young healthy subjects the nodal tissue responded as a low-pass filter with mu = 0.76 +/- 0.12 (mean +/- SD); secondly, ageing did not significantly modify either its shape or gain at 0 Hz; thirdly, in heart transplant recipients, the dynamic transduction properties were lost (all-pass filter, p = 0.06 +/- 0.16, p < 0.001); fourthly, low-dose atropine left the sinus node dynamic properties unmodified; fifthly, high-dose atropine affected the dynamic transduction properties by increasing the gain at 0 Hz and rendering steeper its roll-off (the percent increase of mu with respect to baseline was 18.3 +/- 22.3, p < 0.05).

Movement-related modulation of neural activity in human basal ganglia and its L-DOPA dependency: recordings from deep brain stimulation electrodes in patients with Parkinson's disease

Through electrodes implanted for deep brain stimulation in three patients (5 sides) with Parkinson's disease, we recorded the electrical activity from the human basal ganglia before, during and after voluntary contralateral finger movements, before and after L-DOPA. We analysed the movement-related spectral changes in the electroencephalographic signal from the subthalamic nucleus (STN) and from the internal globus pallidus (GPi). Before, during and after voluntary movements, signals arising from the human basal ganglia contained two main frequencies: a high beta (around 26 Hz), and a low beta (around 18 Hz). The high beta (around 26 Hz) power decreased in the STN and GPi, whereas the low beta (around 18 Hz) power decrease was consistently found only in the GPi. Both frequencies changed their power with a specific temporal modulation related to the different movement phases. L-DOPA specifically and selectively influenced the spectral power changes in these two signal bands.

Analysis of cardiac left-ventricular volume based on time warping averaging

The cardiac left-ventricular (LV) volume signal, obtained by acoustic quantification, is affected by noise and respiratory modulation, resulting in a large beat-to-beat variability that affects the computation of LV function indices. A new method is proposed to improve the evaluation of LV indices by applying a signal averaging technique based on dynamic time warping to consecutive LV volume waveforms. Volume signals obtained from ten normal young (NY) subjects (mean age +/- SD: 25+/-5 years) were used to evaluate the performance of this algorithm. To evaluate its clinical utility, the effects of ageing and pharmacologically induced changes on LV function were assessed by studying, respectively, ten normal (N) adult subjects (age 64+/-8 years) and ten patients with dilated cardiomyopathy during a control and low-dose dobutamine (10 microg kg(-1) min(-1)) study. Indices of LV function were highly consistent, with a variability of less than 8%, even when only 16 beats were averaged, independently of their selection inside the whole recording. When compared with beat-to-beat measures, the averaging of 16 beats significantly reduced (by more than 50%) the interbeat variability of all indexes. Expected alterations in both diastolic and systolic function were evidenced both with ageing (peak filling atrial contraction and ejection rates: from 275+/-77 mls(-1), 76+/-30 ml s(-1) 230+/-70 mls(-1), respectively, in NY, to 160+/-33 mls(-1), 125+/-39 mls(-1), 163+/-54 mls(-1) in N) and with dobutamine (peak filling and ejection rates from 160+/-72 mls(-1) and 183+/-86 mls(-1) respectively, in control, to 253+/-75 mls(-1) and 251+/-105 mls(-1) with dobutamine). Signal averaging with time warping allows fast and improved assessment of LV function.

Short and long term non-linear analysis of RR variability series

The complexity of RR variability is approached in the short and in the long term by means of black-box data analysis. Short term series of a few hundred beats are explored by means of informational entropy and predictability indexes. A correction to biases toward false determinism is performed assuming maximum uncertainty, whenever data do not furnish sufficient recurrences. Non-randomness and non-linearity are tested by means of surrogate data provided by random shuffling and phase randomization respectively. In the long term of the 24-h or of several hours, similar tests based on mutual information are applied and validated by means of surrogate series. In addition the state space reconstruction is carried out by means of state space non-linear filtering addressing directly the reconstructed trajectories. In this condition, parameters characterizing the hypothetical attractor, mainly the maximum Lyapunov exponent, can be reliably identified.

RR-arterial pressure variability relationships

Methodological aspects of a causal black-box model of heart period/arterial pressure interaction, arterial pressure closed-loop regulation and respiration effects on both heart period and arterial pressure are revisited in the "time" (more exactly heart beat count) domain. Parameters are estimated from experimental data (model identification) by means of multiple linear regressions of actual samples over the past ones. The elements composing either heart period or systolic arterial pressure variability are visualised as beat-by-beat series. Indexes describing the signal interactions, the loop properties and the spectral components of the variability series are consequently summarised. In 17 normal young volunteers, the analysis was carried out during active standing, rest, mild clinostatic pedalling exercise at 10%, 20%, and 30% of the maximum effort, and recovery. A negative effect of heart period changes on systolic arterial pressure of - 13.3 mm Hg/s was found at rest. This effect, though augmented by exercise, appeared insignificant in explaining arterial pressure variability. Arterial baroreflex was assessed by alphaart index which had a value of 5.18 mm Hg/ms at rest, 3.78 mm Hg/ms during active standing, and decreased progressively with exercise down to 0.55 mmHg/ms. The pressure regulation loop displayed a tendency to amplify disturbances at low frequency (around 0.1 Hz) 5.94 times at rest, augmented to 8.88 times during standing, 7.55 at 30% exercise. The first parameter of the pressure auto-regression was slightly higher than 1 at rest and even more augmented during standing, thus, indicating a tendency of arterial pressure perturbations to persist from one beat to the next. These mechanisms appear important in the genesis of low-frequency pressure waves. Nonetheless, the trace of different sources was evident in the regression residuals. Noticeably, during exercise it explained 10.16% of total heart period variability compared to 12.49% related to the low-frequency oscillations of closed-loops. The origin of high-frequency waves synchronous with respiration appeared miscellaneous as well. Arterial pressure appeared negligibly affected by heart period changes. Conversely, a limited effect of arterial pressure waves was found on heart period superimposed to a large effect of cardiopulmonary reflexes directly modulating the sinus node. In conclusion, both high-frequency and low-frequency waves are composite phenomena and a multi-channel analysis comparing heart period and arterial pressure variability yields a variety of figures assessing cardiovascular regulation and cardiorespiratory coupling.

Assessment of inertial and gravitational inputs to the vestibular system

A new device for the assessment of instantaneous angular and linear accelerations of the head is presented, which is based on four linear tri-axial accelerometers suitably attached to the head by an helmet. A procedure for reproducible helmet placement and calibration is given. A method is also illustrated to work out the different linear accelerations sensed by the vestibular organs in the left and right labyrinths and the components of the angular acceleration sensed by their semicircular canals. The computation is based on few individual parameters describing the helmet position with respect to external landmarks and on the average internal position and orientation of the vestibula. The purpose is to study the components of internal inertial forces, which represent the primary inputs to the vestibular system devoted to equilibrium and oculomotor control. The system is designed to be of easy application during rehabilitation exercises and in clinical environment during diagnostic and therapeutic manoeuvres. The prototype is tested with simple free movements such as "yes", "no", and gait.

Prediction of short cardiovascular variability signals based on conditional distribution

A new approach measuring the predictability of a process is proposed. The predictor is defined as the median of the distribution conditioned by a sequence of L - 1 previous samples (i.e., a pattern). A function referred to as the corrected mean squared predictor error is defined to prevent the perfect adequacy to the data (i.e., the decrease to zero of the prediction error), thus avoiding to divide the whole set of data in learning and test sets. This function exhibits a minimum and this minimum is taken as a measure of predictability of the series. The use of the minimization procedure avoids to fix a priori the pattern length L. This approach permits one a reliable measure of predictability on short data sequences (around 300 samples). Moreover, this method, in connection with a surrogate data approach, is useful to detect nonlinear dynamics. The analysis indicates that, in simulated and real data, predictability and nonlinearity measures provide different information. The application of this approach to the analysis of cardiovascular variability series of the heart period (RR interval) and systolic arterial pressure (SAP) shows: 1) SAP series is more predictable than RR interval series; 2) predictability of the RR interval series is larger during tilt, during controlled respiration at 10 breaths/min (bpm) and after high-dose administration of atropine; 3) SAP series is dominated by linear correlation; 4) RR interval series exhibits nonlinear dynamics during controlled respiration at 10 bpm and after low-dose administration of atropine, while it is linear during sympathetic activation produced by tilt and after peripheral parasympathetic blockade caused by high-dose administration of atropine.

Assessing baroreflex gain from spontaneous variability in conscious dogs: role of causality and respiration

A double exogenous autoregressive (XXAR) causal parametric model was used to estimate the baroreflex gain (alpha(XXAR)) from spontaneous R-R interval and systolic arterial pressure (SAP) variabilities in conscious dogs. This model takes into account 1) effects of current and past SAP variations on the R-R interval (i.e., baroreflex-mediated influences), 2) specific perturbations affecting R-R interval independently of baroreflex circuit (e.g., rhythmic neural inputs modulating R-R interval independently of SAP at frequencies slower than respiration), and 3) influences of respiration-related sources acting independently of baroreflex pathway (e.g., rhythmic neural inputs modulating R-R interval independently of SAP at respiratory rate, including the effect of stimulation of low-pressure receptors). Under control conditions, alpha(XXAR) = 14.7 +/- 7.2 ms/mmHg. It decreases after nitroglycerine infusion and coronary artery occlusion, even though the decrease is significant only after nitroglycerine, and it is completely abolished by total arterial baroreceptor denervation. Moreover, alpha(XXAR) is comparable to or significantly smaller than (depending on the experimental condition) the baroreflex gains derived from sequence, power spectrum [at low frequency (LF) and high frequency (HF)], and cross-spectrum (at LF and HF) analyses and from less complex causal parametric models, thus demonstrating that simpler estimates may be biased by the contemporaneous presence of regulatory mechanisms other than baroreflex mechanisms.

Information domain analysis of cardiovascular variability signals: evaluation of regularity, synchronisation and co-ordination

A unifying general approach to measure regularity, synchronisation and co-ordination is proposed. This approach is based on conditional entropy and is specifically designed to deal with a small amount of data (a few hundred samples). Quantitative and reliable indexes of regularity, synchronisation and co-ordination (ranging from 0 to 1) are derived in a domain (i.e. the information domain) different from time and frequency domains. The method is applied to evaluate regularity, synchronisation and co-ordination among cardiovascular beat-to-beat variability signals during sympathetic activation induced by head-up tilt (T), during the perturbing action produced by controlled respiration at 10, 15 and 20 breaths/min (CR10, CR15 and CR20), and after peripheral muscarinic blockade provoked by the administration of low and high doses of atropine (LD and HD). It is found that: (1) regularity of the RR interval series is around 0.209; (2) this increases during T, CR10 and HD; (3) the systolic arterial pressure (SAP) series is more regular (0.406) and its regularity is not affected by the specified experimental conditions; (4) the muscle sympathetic (MS) series is a complex signal (0.093) and its regularity is not influenced by HD and LD; (5) the RR interval and SAP series are significantly, though weakly, synchronised (0.093) and their coupling increases during T, CR10 and CR15; (6) the RR interval and respiration are coupled (0.152) and their coupling increases during CR10; (7) SAP and respiration are significantly synchronised (0.108) and synchronisation increases during CR10; (8) MS and respiration are uncoupled and become coupled (0.119) after HD; (9) the RR interval, SAP and respiration are significantly co-ordinated (0.118) and co-ordination increases during CR10 and CR15; (10) during HD the co-ordination among SAP, MS and the respiratory signal is larger than that among the RR interval, SAP, MS and the respiratory signal, thus indicating that the RR interval contributes towards reducing co-ordination.

Assessment of arterial and cardiopulmonary baroreflex gains from simultaneous recordings of spontaneous cardiovascular and respiratory variability

OBJECTIVES

In usual models of cardiovascular regulation, arterial pressure drives RR interval through a simple baroreflex, and the influence of respiration is dismissed. We examined the applicability of a trivariate autoregressive model to obtain separate values of the gain of the arterial and non-arterial, i.e. cardiopulmonary, components of the lumped baroreflex, employing spontaneous RR interval, systolic arterial pressure and respiration variability.

DESIGN

We studied 30 normal subjects (age 37 +/- 1 years), both at rest and during standing, a condition known to enhance sympathetic activity while reducing venous return. Electrocardiogram was obtained by telemetry, arterial pressure by Finapres and respiration with a piezoelectric respiratory belt Data were acquired with a PC and processed with an ad hoc Windows program.

METHODS

We employed an additive and a linear multivariate approach to approximate overall gain of the arterial pressure-heart beat period baroreflex (alphalumped) and of its arterial (alphaart) and non-arterial, i.e. cardiopulmonary (alphacp), components, from continuous beat-by-beat series of RR interval, systolic arterial pressure variability and respiration, without using any non-physiological intervention.

RESULTS

The overall baroreflex gain at rest (alphalumped = 23.7 +/- 3.4 ms/mmHg) was subdivided into arterial (alphaart = 5.2 +/- 1.0 ms/mmHg) and cardiopulmonary (alphacp = 18.5 +/- 3.2ms/mmHg) components. During active orthostatism, alphaluumped was diminished to 10.0 +/- 2.2 ms/ mmHg. In addition, standing selectively reduced alphacp to 4.8 +/- 1.3 ms/mmHg, while alphaart was not significantly changed.

CONCLUSIONS

A trivariate autoregressive model, that considers explicitly the influence of respiration, can subdivide overall, lumped, arterial pressure-heart period baroreflex gain, into two separate components, alphaart and alphacp. Only the latter is reduced by active orthostatism.

Evaluation of respiratory influences on left ventricular function parameters extracted from echocardiographic acoustic quantification

This study was designed to assess, using the echocardiographic acoustic quantification technique, the influence of respiration on left ventricular (LV) function and its modifications connected with the ageing process, quantifying in a non-invasive way the respiratory contribution to the LV volume variability. An automated algorithm is applied to extract the beat-to-beat measurements of LV function parameters from the LV volume signal, obtained from recordings lasting a few minutes. Mean values, amount of variability and spectral content were studied in a population of 17 normal young (mean age 25 +/- 1 years) and 12 normal old (mean age 64 +/- 2 years) subjects. Mean values of the beat-to-beat measurements of LV function parameters were able to point out alterations connected with the ageing process in peak filling rate, peak atrial filling rate and peak ejection rate. Spectral analysis, applied to the extracted variability series, displayed a predominance of the high-frequency (HF) component corresponding to respiration in all LV function parameters; moreover, age related changes of HF variability were observed in peak ejection rate. The HF power spectrum component of beat to beat series extracted from the LV signal can provide a non-invasive assessment of the fluctuations in ventricular parameters associated with respiration.

Conditional entropy approach for the evaluation of the coupling strength

A method that enables measurement of the degree of coupling between two signals is presented. The method is based on the definition of an uncoupling function calculating, by means of entropy rates, the minimum amount of independent information (i.e. the information carried by one signal which cannot be derived from the other). An estimator of the uncoupling function able to deal with short segments of data (a few hundred samples) is proposed, thus enabling the method to be used for usual experimental recordings. A synchronisation index is derived from the estimate of the uncoupling function by means of a minimisation procedure. It quantifies the maximum amount of information exchanged between the two signals. Simulations in which non-linear coordination schemes are produced and changes in the coupling strength are artificially induced are used to check the ability of the proposed index to measure the degree of synchronisation between signals. The synchronisation analysis is utilised to measure the coupling strength between the beat-to-beat variability of the sympathetic discharge and ventilation in decerebrate artificially ventilated cats and the degree of synchronisation between the beat-to-beat variability of the heart period and ventricular repolarisation interval in normal subjects and myocardial infarction patients. The sympathetic discharge and ventilation are strongly coupled and the coupling strength is not affected by manoeuvres capable of increasing or depressing sympathetic activity. The synchronisation is lost after spinalisation. The synchronisation analysis confirms that the heart period and ventricular repolarisation interval are well coordinated. In normal subjects, the synchronisation index is not modified by experimental conditions inducing changes in the sympathovagal balance. On the contrary, it strongly decreases after myocardial infarction, thus detecting and measuring the uncoupling between the heart period and ventricular repolarisation interval.

Assessment of the coupling between RTapex and RR interval as an index of temporal dispersion of ventricular repolarization

To evaluate the dynamic characteristics of the relationship between the RT and RR intervals we analyzed the RR/RTapex variability interaction with a dynamic parametric model whose parameters can be directly estimated from the beat-to-beat series RR and RTapex intervals. The model is designed to separate the fraction of RTapex variability driven by RR changes from that independent of RR variations and to quantify the gain and phase of the relationship between RR and RTapex intervals. The percentage of RTapex variability driven by RR variability was significantly greater in young normal subjects in comparison with postmyocardial infarction patients as well as with age-matched control subjects. This new approach based on the quantification of the RTapex variability dependent and independent of beat-to-beat RR interval changes could be used to quantify the degree of uncoupling between the two signals thus providing a new and noninvasive index of temporal dispersion of ventricular repolarization.

Quantifying electrocardiogram RT-RR variability interactions

A dynamic linear parametric model is designed to quantify the dependence of ventricular repolarisation duration variability on heart period changes and other immeasurable factors. The model analyses the beat-to-beat series of the RR duration and of the interval between R- and T-wave apexes (RT period). Directly from these two signals, a parametric identification procedure and spectral decomposition techniques allow RT variability to be divided into RR-related and RR-unrelated parts and allow the RT-RR transfer function to be calculated. RT variability is driven by RR changes at low frequency (LF, around 0.1 Hz) and high frequency (HF, at the respiratory rate), whereas, at very low frequencies, the RR-unrelated contribution to the total RT variability is remarkable. During tilt at LF the RR-related RT percentage power increases (p < 0.02), the RR-unrelated RT percentage power remains unchanged, the gain of the RT-RR relationship largely increases (p < 0.001), and the phase is not significantly modified. Both the RR-related and the RR-unrelated RT percentage powers at LF are not affected by controlled respiration, and an increase in the RT-RR gain at HF is observed (p < 0.02). The proposed analysis may help to describe the regulation of the ventricular repolarisation process and to extract indexes quantifying the coupling between heart period and ventricular repolarisation interval changes.

Performance assessment of standard algorithms for dynamic R-T interval measurement: comparison between R-Tapex and R-T(end) approach

Three automatic approaches to ventricular repolarisation duration measurement (R-Tapex, R-T(end threshold) and R-T(end fitting) methods) are compared on computer-generated and real ECG signals, in relation to their reliability in the presence of the most common electrocardiographic artefacts (i.e. additive broadband noise and additive and multiplicative periodical disturbances). Simulations permit the evaluation of the amount of R-T beat-to-beat variability induced by the artefacts. The R-T(end threshold) method performs better than the R-T(end fitting) one, and, hence, the latter should be used with caution when R-T(end) variability is addressed. Whereas the R-Tapex method is more robust with regard to broadband noise than the R-T(end threshold) one, the reverse situation is observed in the presence of periodical amplitude modulations. A high level of broadband noise dose not prevent the detection of the central frequency of underlying R-T periodical changes. Comparison between the power spectra of the beat-to-beat R-T variability series obtained from three orthogonal ECG leads (X,Y,Z) is used to assess the amount of real and artefactual variability in 13 normal subjects at rest. The R-Tapex series displays rhythms at high frequency (HF) with a percentage power on the Z lead (57.1 +/- 4.9) greater than that on the X and Y leads (41.9 +/- 4.6 and 46.1 +/- 4.9, respectively), probably because of respiratory-related artefacts affecting the Z lead more remarkably. More uniform HF power distributions over X,Y,Z leads are observed in the R-T(end threshold) series (31.8 +/- 3.8, 39.2 +/- 4.1 and 35.1 +/- 4.2, respectively), thus suggesting minor sensitivity of the R-T(end threshold) measure to respiratory-related artefacts.

Measuring regularity by means of a corrected conditional entropy in sympathetic outflow

A new method for measuring the regularity of a process over short data sequences is reported. This method is based on the definition of a new function (the corrected conditional entropy) and on the extraction of its minimum. This value is taken as an index in the information domain quantifying the regularity of the process. The corrected conditional entropy is designed to decrease in relation to the regularity of the process (like other estimates of the entropy rate), but it is able to increase when no robust statistic can be performed as a result of a limited amount of available samples. As a consequence of the minimisation procedure, the proposed index is obtained without an a-priori definition of the pattern length (i.e. of the embedding dimension of the reconstructed phase space). The method is validated on simulations and applied to beat-to-beat sequences of the sympathetic discharge obtained from decerebrate artificially ventilated cats. At control, regular, both quasiperiodic and periodic (locked to ventilation) dynamics are observed. During the sympathetic activation induced by inferior vena cava occlusion, the presence of phase-locked patterns and the increase in regularity of the sympathetic discharge evidence an augmented coupling between the sympathetic discharge and ventilation. The reduction of complexity of the neural control obtained by spinalization decreases the regularity in the sympathetic outflow, thus pointing to a weaker coupling between the sympathetic discharge and ventilation.

Spectral decomposition in multichannel recordings based on multivariate parametric identification

A method of spectral decomposition in multichannel recordings is proposed, which represents the results of multivariate (MV) parametric identification in terms of classification and quantification of different oscillating mechanisms. For this purpose, a class of MV dynamic adjustment (MDA) models in which a MV autoregressive (MAR) network of causal interactions is fed by uncorrelated autoregressive (AR) processes is defined. Poles relevant to the MAR network closed-loop interactions (cl-poles) and poles relevant to each AR input are disentangled and accordingly classified. The autospectrum of each channel can be divided into partial spectra each relevant to an input. Each partial spectrum is affected by the cl-poles and by the poles of the corresponding input; consequently, it is decomposed into the relevant components by means of the residual method. Therefore, different oscillating mechanisms, even at similar frequencies, are classified by different poles and quantified by the corresponding components. The structure of MDA models is quite flexible and can be adapted to various sets of available signals and a priori hypotheses about the existing interactions; a graphical layout is proposed that emphasizes the oscillation sources and the corresponding closed-loop interactions. Application examples relevant to cardiovascular variability are briefly illustrated.

Linear multivariate models for physiological signal analysis: theory

The general linear parametric multivariate modelling concept is presented. This model combines a variety of different kinds of multivariate linear models. The concept of partial spectral analysis is derived from the general model. Some emphasis is laid on the causality demands of the model, and it is shown that the classic strictly-causal structure must be abandoned in order to utilise the modelling in many practical situations. Two special sub-class models are described in detail: the multivariate autoregressive model and the multivariate dynamic adjustment model. Furthermore, time-varying modelling is considered. The modelling of the real system is presented on a general level as a system identification cycle. The application of the methods to real physiological data is presented in the companion paper.

Linear multivariate models for physiological signal analysis: applications

Some applications of linear multivariate modelling methods in the analysis of physiological signals are presented. These applications illustrate the methods in the analysis of cardiovascular dynamics, which has been one of the main application fields of the multivariate modelling during the last ten years. It is demonstrated that physiologically meaningful information about the causal interactions in the cardiovascular system can be drawn from the routinely available clinical signals. Both static and dynamic conditions are considered.

Classification of coupling patterns among spontaneous rhythms and ventilation in the sympathetic discharge of decerebrate cats

The spontaneous low- and high-frequency rhythms in the sympathetic discharge of decerebrate artificially ventilated cats are affected by external ventilation. Two graphical methods (i.e. the space-time separation plot and the frequency tracking locus) are used to classify the non-linear interactions. The observed behaviours in the sympathetic discharge consist of phase-locked periodic dynamics (at various frequency ratios with ventilation), quasiperiodic and aperiodic patterns. They depend on the experimental condition. In control condition the sympathetic discharge appears more frequently locked to each ventilatory cycle (1:1 dynamics). However, some cases of quasiperiodic dynamics are found. A sympathetic activation stimulus, such as inferior vena cava occlusion, is able to synchronize slow rhythms in the sympathetic discharge to a subharmonic of ventilation. During a sympathetic inhibition stimulus, such as aortic constriction, 1:1 dynamics is detected but the amplitude of the sympathetic responses can be modulated by unlocked slow rhythms. Moreover some cases of aperiodic dynamics are observed. Vagotomy reduces the 1:1 coupling between sympathetic outflow and ventilation. Vagotomy plus spinalisation disrupts periodic dynamics in the sympathetic discharge so that irregular and complex patterns are found.

Spectral analysis of short term R-Tapex interval variability during sinus rhythm and fixed atrial rate

Analysis of heart rate variability has been proven useful in stratifying post myocardial patients at risk and in evaluating autonomic dysfunction. Recently augmented inter-lead variability of the QT interval has been associated with increased mortality as a result of arrhythmia and proposed as a marker of dispersion of ventricular repolarization. As the duration of the QT interval is largely dependent upon the length of the preceding cardiac cycle it is tempting to analyse whether neural mechanisms might also directly exert additional modulation. Using autoregressive algorithms we therefore analysed RR and R-Tapex interval variabilities in 15 normal subjects during sinus rhythm and in six patients with a fixed atrial rate. In controls mean R-Tapex interval and variance measured on the vector magnitude were, respectively, 245 +/- 6 ms and 5.1 +/- 0.7 ms2. Spectral analysis of R-Tapex indicated the presence of two spectral components which corresponded to the low and high frequency components of heart rate variability. In R-Tapex variability, high frequency (44 +/- 4 nu) was predominant over low frequency (29 +/- 4 nu). During controlled respiration, a manoeuvre associated with enhanced vagal modulation of sinus node, there was a further increase in high frequency (58 +/- 4 nu) whereas during tilt the low frequency component of R-Tapex variability became predominant (57 +/- 6 nu). In patients with a fixed atrial rate, variance was extremely low (3 +/- 0.9 ms2) and only a respiration-related high frequency component was recognizable in spectral analysis of RR and R-Tapex variabilities. This component was likely to depend upon mechanically induced changes in cardiac vector orientation. These data indicate that during sinus rhythm short-term R-Tapex interval variability is characterized by the same rhythmical components present in RR variability. However, the presence of a very low variance and of only a high frequency component in patients in whom the physiological variability of sinus node is abolished by atrial pacing. suggests that neural modulatory mechanisms do not exert a direct effect on the length of the R-Tapex interval.