The impact of healthy pregnancy on features of heart rate variability and pulse wave morphology derived from wrist-worn photoplethysmography.

Due to the association between dysfunctional maternal autonomic regulation and pregnancy complications, tracking non-invasive features of autonomic regulation derived from wrist-worn photoplethysmography (PPG) measurements may allow for the early detection of deteriorations in maternal health. However, even though a plethora of these features-specifically, features describing heart rate variability (HRV) and the morphology of the PPG waveform (morphological features)-exist in the literature, it is unclear which of these may be valuable for tracking maternal health. As an initial step towards clarity, we compute comprehensive sets of HRV and morphological features from nighttime PPG measurements. From these, using logistic regression and stepwise forward feature elimination, we identify the features that best differentiate healthy pregnant women from non-pregnant women, since these likely capture physiological adaptations necessary for sustaining healthy pregnancy. Overall, morphological features were more valuable for discriminating between pregnant and non-pregnant women than HRV features (area under the receiver operating characteristics curve of 0.825 and 0.74, respectively), with the systolic pulse wave deterioration being the most valuable single feature, followed by mean heart rate (HR). Additionally, we stratified the analysis by sleep stages and found that using features calculated only from periods of deep sleep enhanced the differences between the two groups. In conclusion, we postulate that in addition to HRV features, morphological features may also be useful in tracking maternal health and suggest specific features to be included in future research concerning maternal health.

Artificial intelligence-based radiomics on computed tomography of lumbar spine in subjects with fragility vertebral fractures.

PURPOSE: There is emerging evidence that radiomics analyses can improve detection of skeletal fragility. In this cross-sectional study, we evaluated radiomics features (RFs) on computed tomography (CT) images of the lumbar spine in subjects with or without fragility vertebral fractures (VFs). METHODS: Two-hundred-forty consecutive individuals (mean age 60.4 ± 15.4, 130 males) were evaluated by radiomics analyses on opportunistic lumbar spine CT. VFs were diagnosed in 58 subjects by morphometric approach on CT or XR-ray spine (D4-L4) images. DXA measurement of bone mineral density (BMD) was performed on 17 subjects with VFs. RESULTS: Twenty RFs were used to develop the machine learning model reaching 0.839 and 0.789 of AUROC in the train and test datasets, respectively. After correction for age, VFs were significantly associated with RFs obtained from non-fractured vertebrae indicating altered trabecular microarchitecture, such as low-gray level zone emphasis (LGLZE) [odds ratio (OR) 1.675, 95% confidence interval (CI) 1.215-2.310], gray level non-uniformity (GLN) (OR 1.403, 95% CI 1.023-1.924) and neighboring gray-tone difference matrix (NGTDM) contrast (OR 0.692, 95% CI 0.493-0.971). Noteworthy, no significant differences in LGLZE (p = 0.94), GLN (p = 0.40) and NGDTM contrast (p = 0.54) were found between fractured subjects with BMD T score < - 2.5 SD and those in whom VFs developed in absence of densitometric diagnosis of osteoporosis. CONCLUSIONS: Artificial intelligence-based analyses on spine CT images identified RFs associated with fragility VFs. Future studies are needed to test the predictive value of RFs on opportunistic CT scans in identifying subjects with primary and secondary osteoporosis at high risk of fracture.

Yersinia pestis: the Natural History of Plague.

The Gram-negative bacterium Yersinia pestis is responsible for deadly plague, a zoonotic disease established in stable foci in the Americas, Africa, and Eurasia. Its persistence in the environment relies on the subtle balance between Y. pestis-contaminated soils, burrowing and nonburrowing mammals exhibiting variable degrees of plague susceptibility, and their associated fleas. Transmission from one host to another relies mainly on infected flea bites, inducing typical painful, enlarged lymph nodes referred to as buboes, followed by septicemic dissemination of the pathogen. In contrast, droplet inhalation after close contact with infected mammals induces primary pneumonic plague. Finally, the rarely reported consumption of contaminated raw meat causes pharyngeal and gastrointestinal plague. Point-of-care diagnosis, early antibiotic treatment, and confinement measures contribute to outbreak control despite residual mortality. Mandatory primary prevention relies on the active surveillance of established plague foci and ectoparasite control. Plague is acknowledged to have infected human populations for at least 5,000 years in Eurasia. Y. pestis genomes recovered from affected archaeological sites have suggested clonal evolution from a common ancestor shared with the closely related enteric pathogen Yersinia pseudotuberculosis and have indicated that ymt gene acquisition during the Bronze Age conferred Y. pestis with ectoparasite transmissibility while maintaining its enteric transmissibility. Three historic pandemics, starting in 541 AD and continuing until today, have been described. At present, the third pandemic has become largely quiescent, with hundreds of human cases being reported mainly in a few impoverished African countries, where zoonotic plague is mostly transmitted to people by rodent-associated flea bites.

Assessing an Automatic Procedure of Extraction of Physiological Parameters from Skin using Video Photoplethysmography.

Video Photoplethysmography (vPPG) allows for estimation of blood volume pulse (BVP) from the skin by means of a video camera recording at high frequency rate. The estimation procedure presents several drawbacks in its application to real world conditions, such as light changes or movements that often generate artifacts in the extracted BVP waveform. In addition, the process requires a skin segmentation algorithm to distinguish skin pixels from the background. To date, even the most refined skin segmentation algorithms still need a manual definition that could lead to incorrect pixel classification, and consequently to a decrease in the signal-to-noise ratio (SNR). We here propose a fully autonomic procedure able to extract BVP from video recordings of the skin in real world conditions.The experimental protocol is designed to record the signals of interest and to evaluate changes in the Autonomic Nervous System modulation of the heart during a baseline condition and a controlled breathing phase. Video recordings are gathered from 4 young healthy subjects (age: 21±1 years). vPPG signals are processed in order to extract the BVP waveform, and a peak detection algorithm detects pulse wave peaks that are then used to compute specific measures of heart rate variability (HRV).The procedure is successfully validated by comparing the extracted HRV measures against those extracted using a finger photoplethysmograph (fPPG) using three different skin segmentation algorithms from BVP signals.

A 2,000-year-old specimen with intraerythrocytic Bartonella quintana.

Photogrammetry and cascading microscopy investigations of dental pulp specimens collected from 2,000-year-old individuals buried in a Roman necropolis in Besançon, France, revealed unprecedented preserved tissular and cellular morphology. Photogrammetry yielded 3-D images of the smallest archaeological human remains ever recovered. Optical microscopy examinations after standard haematoxylin-phloxine-saffron staining and anti-glycophorin A immunohistochemistry exposed dental pulp cells, in addition erythrocytes were visualised by electron microscopy, which indicated the ancient dental pulp trapped a blood drop. Fluorescence in situ hybridisation applied on red blood cells revealed the louse-borne pathogen Bartonella quintana, a finding confirmed by polymerase chain reaction assays. Through paleohistology and paleocytology, we demonstrate that the ancient dental pulp preserved intact blood cells at the time of the individual's death, offering an unprecedented opportunity to engage in direct and indirect tests to diagnose pathogens in ancient buried individuals.

Late sodium current blocker GS967 inhibits persistent currents induced by familial hemiplegic migraine type 3 mutations of the SCN1A gene.

BACKGROUND: Familial hemiplegic migraine (FHM) is a group of genetic migraine, associated with hemiparesis and aura. Three causative different genes have been identified, all of which are involved in membrane ion transport. Among these, SCN1A encodes the voltage-gated Na+ channel Nav1.1, and FHM caused by mutations of SCN1A is named FHM3. For 7 of the 12 known FHM3-causing SCNA1 mutations functional consequences have been investigated, and even if gain of function effect seems to be a predominant phenotype, for several mutations conflicting results have been obtained and the available data do not reveal a univocal FHM3 pathomechanism. METHODS: To obtain a more complete picture, here, we characterized by patch clamp approach the remaining 5 mutations (Q1489H, I1498M, F1499 L, M1500 V, F1661 L) in heterologous expression systems. RESULTS: With the exception of I1498M, all mutants exhibited the same current density as WT and exhibited a shift of the steady state inactivation to more positive voltages, an accelerated recovery from inactivation, and an increase of the persistent current, revealing that most FHM3 mutations induce a gain of function. We also determined the effect of GS967, a late Na+ current blocker, on the above mentioned mutants as well as on previously characterized ones (L1649Q, L1670 W, F1774S). GS967 inhibited persistent currents of all SCNA1 FMH3-related mutants and dramatically slowed the recovery from fast inactivation of WT and mutants, consistent with the hypothesis that GS967 specifically binds to and thereby stabilizes the fast inactivated state. Simulation of neuronal firing showed that enhanced persistent currents cause an increase of ionic fluxes during action potential repolarization and consequent accumulation of K+ and/or exhaustion of neuronal energy resources. In silico application of GS967 largely reduced net ionic currents in neurons without impairing excitability. CONCLUSION: In conclusion, late Na+ current blockers appear a promising specific pharmacological treatment of FHM3.

The central autonomic network at rest: Uncovering functional MRI correlates of time-varying autonomic outflow.

Peripheral measures of autonomic nervous system (ANS) activity at rest have been extensively employed as putative biomarkers of autonomic cardiac control. However, a comprehensive characterization of the brain-based central autonomic network (CAN) sustaining cardiovascular oscillations at rest is missing, limiting the interpretability of these ANS measures as biomarkers of cardiac control. We evaluated combined cardiac and fMRI data from 34 healthy subjects from the Human Connectome Project to detect brain areas functionally linked to cardiovagal modulation at rest. Specifically, we combined voxel-wise fMRI analysis with instantaneous heartbeat and spectral estimates obtained from inhomogeneous linear point-process models. We found exclusively negative associations between cardiac parasympathetic activity at rest and a widespread network including bilateral anterior insulae, right dorsal middle and left posterior insula, right parietal operculum, bilateral medial dorsal and ventrolateral posterior thalamic nuclei, anterior and posterior mid-cingulate cortex, medial frontal gyrus/pre-supplementary motor area. Conversely, we found only positive associations between instantaneous heart rate and brain activity in areas including frontopolar cortex, dorsomedial prefrontal cortex, anterior, middle and posterior cingulate cortices, superior frontal gyrus, and precuneus. Taken together, our data suggests a much wider involvement of diverse brain areas in the CAN at rest than previously thought, which could reflect a differential (both spatially and directionally) CAN activation according to the underlying task. Our insight into CAN activity at rest also allows the investigation of its impairment in clinical populations in which task-based fMRI is difficult to obtain (e.g., comatose patients or infants).

Correction to: The 1000IBD project: multi-omics data of 1000 inflammatory bowel disease patients; data release 1.

Following publication of the original article [1], the authors.

The Dallol Geothermal Area, Northern Afar (Ethiopia)-An Exceptional Planetary Field Analog on Earth.

The Dallol volcano and its associated hydrothermal field are located in a remote area of the northern Danakil Depression in Ethiopia, a region only recently appraised after decades of inaccessibility due to severe political instability and the absence of infrastructure. The region is notable for hosting environments at the very edge of natural physical-chemical extremities. It is surrounded by a wide, hyperarid salt plain and is one of the hottest (average annual temperatureDallol: 36-38°C) and most acidic natural systems (pHDallol ≈0) on Earth. Spectacular geomorphologies and mineral deposits produced by supersaturated hydrothermal waters and brines are the result of complex interactions between active and inactive hydrothermal alteration of the bedrock, sulfuric hot springs and pools, fumaroles and geysers, and recrystallization processes driven by hydrothermal waters, degassing, and rapid evaporation. The study of planetary field analog environments plays a crucial role in characterizing the physical and chemical boundaries within which life can exist on Earth and other planets. It is essential for the definition and assessment of the conditions of habitability on other planets, including the possibility for biosignature preservation and in situ testing of technologies for life detection. The Dallol area represents an excellent Mars analog environment given that the active volcanic environment, the associated diffuse hydrothermalism and hydrothermal alteration, and the vast acidic sulfate deposits are reminiscent of past hydrothermal activity on Mars. The work presented in this paper is an overview of the Dallol volcanic area and its hydrothermal field that integrates previous literature with observations and results obtained from field surveys and monitoring coupled with sample characterization. In so doing, we highlight its exceptional potential as a planetary field analog as well as a site for future astrobiological and exploration programs.

The 1000IBD project: multi-omics data of 1000 inflammatory bowel disease patients; data release 1.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic complex disease of the gastrointestinal tract. Patients with IBD can experience a wide range of symptoms, but the pathophysiological mechanisms that cause these individual differences in clinical presentation remain largely unknown. In consequence, IBD is currently classified into subtypes using clinical characteristics. If we are to develop a more targeted treatment approach, molecular subtypes of IBD need to be discovered that can be used as new drug targets. To achieve this, we need multiple layers of molecular data generated from the same IBD patients. CONSTRUCTION AND CONTENT: We initiated the 1000IBD project ( https://1000ibd.org ) to prospectively follow more than 1000 IBD patients from the Northern provinces of the Netherlands. For these patients, we have collected a uniquely large number of phenotypes and generated multi-omics profiles. To date, 1215 participants have been enrolled in the project and enrolment is on-going. Phenotype data collected for these participants includes information on dietary and environmental factors, drug responses and adverse drug events. Genome information has been generated using genotyping (ImmunoChip, Global Screening Array and HumanExomeChip) and sequencing (whole exome sequencing and targeted resequencing of IBD susceptibility loci), transcriptome information generated using RNA-sequencing of intestinal biopsies and microbiome information generated using both sequencing of the 16S rRNA gene and whole genome shotgun metagenomic sequencing. UTILITY AND DISCUSSION: All molecular data generated within the 1000IBD project will be shared on the European Genome-Phenome Archive ( https://ega-archive.org , accession no: EGAS00001002702). The first data release, detailed in this announcement and released simultaneously with this publication, will contain basic phenotypes for 1215 participants, genotypes of 314 participants and gut microbiome data from stool samples (315 participants) and biopsies (107 participants) generated by tag sequencing the 16S gene. Future releases will comprise many more additional phenotypes and -omics data layers. 1000IBD data can be used by other researchers as a replication cohort, a dataset to test new software tools, or a dataset for applying new statistical models. CONCLUSIONS: We report on the establishment and future development of the 1000IBD project: the first comprehensive multi-omics dataset aimed at discovering IBD biomarker profiles and treatment targets.

Heartbeat Dynamics Analysis under Cold-Pressure Test using Wavelet p-Leader Non-Gaussian Multiscale Expansions.

Multiscale and multifractal (MF) analyses have been proven an effective tool for the characterisation of heartbeat dynamics in physiological and pathological conditions. However, pre-processing methods for the unevenly sampled heartbeat interval series are known to affect the estimation of MF properties. In this study, we employ a recently proposed method based on wavelet p-leaders MF spectra to estimate MF properties from cardiovascular variability series, which are also pre-processed through an inhomogeneous point-process modelling. Particularly, we exploit a non-Gaussian multiscale expansion to study changes in heartbeat dynamics as a response to a sympathetic elicitation given by the cold-pressor test. By comparing MF estimates from raw heartbeat series and the point-process model, results suggest that the proposed modelling provides features statistically discerning between stress and resting condition at different time scales. These findings contribute to a comprehensive characterization of autonomic nervous system activity on cardiovascular control during cold-pressor elicitation.

Resting State Neural Correlates of Cardiac Sympathetic Dynamics in Healthy Subjects.

Recent advances in functional Magnetic Resonance Imaging (fMRI) research have uncovered the existence of the central autonomic network (CAN), which comprises brain regions whose activity correlates with autonomic nervous system dynamics. By exploiting the spectral paradigm of heartbeat dynamics, cortical and sub-cortical areas functionally linked to vagal activity have been identified. However, due to methodological limitations, functional neural correlates of cardiac sympathetic dynamics remain uncharacterized. To this extent, we exploit the high spatiotemporal resolution of fMRI data from the Human Connectome Project to study the CAN activity by correlating a recently proposed instantaneous characterization of sympathetic activity (the sympathetic activity index - SAI) from heartbeat dynamics. SAI estimates are embedded into the probabilistic modeling of inhomogeneous point-processes, and are derived from a combination of disentangling coefficients linked to the orthonormal Laguerre functions. By analyzing resting state recordings from 34 young healthy people, we obtain positive correlations between instantaneous SAI estimates and a number of brain regions including frontal pole, insular cortex, frontal and temporal gyri, lateral occipital cortex, paracingulate and cingulate gyri, precuneus and temporal fusiform cortices, as well as thalamus, caudate nucleus, putamen, brain-stem, hippocampus, amygdala, and nucleus accumbens. Our findings significantly extend current knowledge on the CAN, opening new avenues in the characterization of healthy and pathological states in humans.

Quantification of Different Regulatory Pathways Contributing to Heartbeat Dynamics during Multiple Stimuli: a Proof of the Concept.

The dynamical interplay between brain and heart is mediated by several feedback mechanisms including the central autonomic network and baroreflex loop at a peripheral level, also for a short-term regulation. State of the art focused on the characterization of each regulatory pathway through a single stressor elicitation. However, no studies targeted the actual quantification of different mediating routes leading to the generation of heartbeat dynamics, particularly in case of combined exogenous stimuli. In this study, we propose a new approach based on computational modeling to quantify the contribution of multiple concurrent stimuli in modulating cardiovascular dynamics. In this preliminary attempt, the model estimates the high-frequency power of heartbeat dynamics, and derives disentangling coefficients quantifying the effect of multiple elicitations. Model evaluation is performed on healthy rate variability (HRV) series from fourteen healthy subjects undergoing physical (tilt-table) and mental stressors (aritmetics), as well as their combined administration. Results indicate that, at a group-wise level, in base of concurrent physical and mental elicitations, the physical stressor contributes for the 85% of the resulting heartbeat dynamics. These findings are in agreement with the current knowledge on heartbeat regulatory systems, providing valuable perspectives on the quantification of underlying generative mechanisms of HRV.

Characterizing autonomic response to arousing visual-auditory multi-modal task in Autism Spectrum Disorder (ASD).

Sensory abnormalities are widespread in Autism Spectrum Disorder (ASD). However, their definition is still quite subjective and vague. Here we propose a novel approach for characterization of Autonomic Nervous System responses to sensory stimulation based on electrocardiogram (ECG) assessment. In particular, we develop a preliminary study where autonomic responses of both autistic (ASD = 5) and neurotypical (NT = 5) participants have been evaluated in terms of changes in responsiveness to repeated stimuli. Autonomic control has been estimated via high-frequency heart rate variability (HF-HRV) and low-frequency HRV (LF-HRV). Results show significant differences among groups for the HRV measures (p value = 0.0158), supported by expected changes of HF (p value = 0.0079) and LF (p value = 0.0079) trends over stimulations. We thus conclude that an overall decrease in autonomic arousal can give important insights for devising new habituation metrics in NT and ASD individuals.

Identification and Tracking of Physiological Parameters from Skin using Video Photoplethysmography.

In recent years, there has been a growing interest in video Photoplethysmography (vPPG), a technique able to estimate cardiovascular parameters from video recordings of the skin. Despite the growing interest in vPPG technology, there are still problems in extracting the correct waveform of blood volume pulse, mainly due to real world artifacts, such as changes in light condition and movement artifacts. Another important issue is the correct definition of skin against background. Therefore, we propose an algorithm of skin detection that is able to recognize skin pixels solid to variations of luminosity. We recorded the signals of interest during an experimental protocol designed to provide thermal stimulation and observe the resulting Autonomic Nervous System changes. Experimental data were gathered from 10 young healthy subjects (age: 21±2 years). Video recordings are processed using a band-pass filter and then an automatic algorithm of peak detection is applied to detect the pulse wave peaks, then used to estimate heart rate variability (HRV). The efficiency and stability of the algorithm are compared against finger-PPG waveforms. Preliminary results show an overall statistical agreement between time and frequency domain indexes. However, further efforts are required to improve the estimation of frequency components, particularly during rest.

Wavelet p-Leader Non-Gaussian Multiscale Expansions for EEG series: an Exploratory Study on Cold-Pressor Test.

Brain dynamics recorded through electroencephalography (EEG) have been proven to be the output of a nonstationary and nonlinear system. Thus, multifractality of EEG series has been exploited as a useful tool for a neurophysiological characterization in health and disease. However, the role of EEG multifractality under peripheral stress is unknown. In this study, we propose to make use of a novel tool, the recently defined non-Gaussian multiscale analysis, to investigate brain dynamics in the range of 4-8Hz following a cold-pressor test versus a resting state. The method builds on the wavelet p-leader multifractal spectrum to quantify different types of departure from Gaussian and linear properties, and is compared here to standard linear descriptive indices. Results suggest that the proposed non-Gaussian multiscale indices were able to detect expected changes over the somatosensory and premotor cortices, over regions different from those detected by linear analyses. They further indicate that preferred responses for the contralateral somatosensory cortex occur at scales 2.5s and 5s. These findings contribute to the characterization of the so-called central autonomic network, linking dynamical changes at a peripheral and a central nervous system levels.

Two thousand years of epidemics in Marseille and the Mediterranean Basin.

Marseille has been exposed to epidemics for two millennia, including plague, cholera and yellow fever. This long-standing exposure to epidemics has given the people of Marseilles a particular expertise in fighting epidemics. Lazarets and other quarantine measures were implemented as a response to preventing the further spread of the disease in the community. The Institut Hospitalier Universitaire Méditerranée Infection is paving the way today, with its responses built on the region's long history and knowledge of epidemics, infectious diseases and medical microbiology.

The Role of Baroreflex Sensitivity in Acute Hypotensive Episodes Prediction in the Intensive Care Unit.

A life threatening condition in Intensive Care Unit (ICU) is the Acute Hypotensive Episode (AHE). Patients experiencing an AHE may suffer from irreversible organ damage associated with increased mortality. Predicting the onset of AHE could be of pivotal importance to establish appropriate and timely interventions. We propose a method that, using waveforms widely acquired in ICU, like Arterial Blood Pressure (ABP) and Electrocardiogram (ECG), will extract features relative to the cardiac system to predict whether or not a patient will experience a hypotensive episode. Specifically, we want to assess if there are hidden patterns in the dynamics of baroreflex able to improve the prediction of AHEs. We will investigate the predictive power of features related to the baroreflex by performing classifications with and without them. Results are obtained using 17 classifiers belonging to different model families: classification trees, Support Vector Machines (SVMs), K-Nearest Neighbors (KNNs) replicated with different set of hyper-parameters and logistic regression. On average, the use of baroreflex features in the AHE prediction process increases the Area Under the Curve (AUC) by 10%.

A New Sympathovagal Balance Index from Electrodermal Activity and Instantaneous Vagal Dynamics: A Preliminary Cold Pressor Study.

Sympathovagal balance, an autonomic index resulting from the sympathetic and parasympathetic influences on cardiovascular control, has been extensively used in the research practice. The current assessment is based on analyzing Heart Rate Variability (HRV) series in the frequency domain by regarding the ratio between the low and high frequency components (LF/HF). Nevertheless, LF and HF powers are known to be both influenced by vagal activity which strongly bias the accuracy of this method. To this extent, in this study we combine time-varying estimates from electrodermal activity (EDA) and HRV to propose a novel index of sympathovagal balance. Particularly, sympathetic activity is estimated from the EDA power calculated within the 0.045-0.25Hz bandwidth $(EDA_{Symp})$, whereas parasympathetic dynamics is measured instantaneously through a point-process modeling framework devised for heartbeat dynamics $(HF_{pp})$. We test our new index $SV = EDA_{Symp/HF_{pp}}$ on data gathered from 22 healthy subjects (7 females and 15 males) undergoing a 3 minutes gold standard protocol for sympathetic elicitation as the cold-pressor test (CPT). Results show that the activation of the proposed sympathovagal tone is consistent with CPT elicitation and is associated with a significantly higher statistical discriminant power than the standard LF/HF ratio, also revealing different dynamics between female and male subjects.

Resting-state brain correlates of cardiovascular complexity.

While estimates of complex heartbeat dynamics have provided effective prognostic and diagnostic markers for a wide range of pathologies, brain correlates of complex cardiac measures in general and of complex sympatho-vagal dynamics in particular are still unknown. In this study we combine resting state functional Magnetic Resonance Imaging (fMRI) and physiological signal acquisition from 34 healthy subjects selected from the Human Connectome Project (HCP) repository with inhomogeneous point-process approximate and sample heartbeat entropy measures (ipApEn and ipSampEn) to investigate brain areas involved in complex cardiovascular control. Our results show that activity in the Temporal Gyrus, Frontal Orbital Cortex, Temporal Fusiform and Opercular cortices, Planum Temporale, and Paracingulate cortex are negatively correlated with ipApEn dynamics. Activity in the same cortical areas as well as in the Temporal Fusiform cortex are negatively correlated with ipSampEn dynamics. No significant positive correlations were found. These pioneering results suggest that cardiovascular complexity at rest is linked to a few specific cortical brain structures, including crucial areas connected with parasympathetic outflow. This corroborates the hypothesis of a multidimensional central network which controls nonlinear cardiac dynamics under a predominantly vagally-driven tone.