Papers by VINCENZO CATRAMBONE
Supplementary material from "Functional brain–heart interplay extends to the multifractal domain
The study of functional brain–heart interplay has provided meaningful insights in cardiology and ... more The study of functional brain–heart interplay has provided meaningful insights in cardiology and neuroscience. Regarding biosignal processing, this interplay involves predominantly neural and heartbeat linear dynamics expressed via time and frequency domain-related features. However, the dynamics of central and autonomous nervous systems show nonlinear and multifractal behaviours, and the extent to which this behaviour influences brain–heart interactions is currently unknown. Here, we report a novel signal processing framework aimed at quantifying nonlinear functional brain–heart interplay in the non-Gaussian and multifractal domains that combines electroencephalography (EEG) and heart rate variability series. This framework relies on a maximal information coefficient analysis between nonlinear multiscale features derived from EEG spectra and from an inhomogeneous point-process model for heartbeat dynamics. Experimental results were gathered from 24 healthy volunteers during a resti...
Functional assessment of bidirectional cortical and peripheral neural control on heartbeat dynamics: a brain-heart study on thermal stress
NeuroImage, 2022
The study of functional brain-heart interplay (BHI) from non-invasive recordings has gained much ... more The study of functional brain-heart interplay (BHI) from non-invasive recordings has gained much interest in recent years. Previous endeavors aimed at understanding how the two dynamical systems exchange information, providing novel holistic biomarkers and important insights on essential cognitive aspects and neural system functioning. However, the interplay between cardiac sympathovagal and cortical oscillations still has much room for further investigation. In this study, we introduce a new computational framework for a functional BHI assessment, namely the Sympatho-Vagal Synthetic Data Generation Model, combining cortical (electroencephalography, EEG) and peripheral (cardiac sympathovagal) neural dynamics. The causal, bidirectional neural control on heartbeat dynamics was quantified on data gathered from 26 human volunteers undergoing a cold-pressor test. Results show that thermal stress induces heart-to-brain functional interplay sustained by EEG oscillations in the delta and gamma bands, primarily originating from sympathetic activity, whereas brain-to-heart interplay originates over central brain regions through sympathovagal control. The proposed methodology provides a viable computational tool for the functional assessment of the causal interplay between cortical and cardiac neural control.
Advances in Signal Processing Methods to Investigate Functional Brain-Heart Interplay
In this doctoral dissertation, advances in the study of functional Brain-Heart Interplay (BHI) ar... more In this doctoral dissertation, advances in the study of functional Brain-Heart Interplay (BHI) are reported. While the crucial role of the interaction between Central and Autonomous Nervous Systems has been highlighted in several clinical and physiological studies by investigating their anatomical, biochemical, and functional links, a few methodological endeavors reported on a quantitative description of such a fundamental interplay.<br>Here, I report on a novel, fully parametric methodological framework for the directional quantification of functional BHI using non-invasive brain and heartbeat monitoring, and experimental results are gathered in different physiological and pathological conditions.<br>The dissertation is organized as follows. An overview of fundamental BHI physiology is in the first Chapter, with evidences and significance from clinical studies. The second Chapter reports on the state of the art signal processing techniques that have been employed in mod...
Bioengineering, 2022
Background: Several methods have been proposed to estimate complexity in physiological time serie... more Background: Several methods have been proposed to estimate complexity in physiological time series observed at different time scales, with a particular focus on heart rate variability (HRV) series. In this frame, while several complexity quantifiers defined in the multiscale domain have already been investigated, the effectiveness of a multiscale Kolmogorov–Sinai (K-S) entropy has not been evaluated yet for the characterization of heartbeat dynamics. Methods: The use of the algorithmic information content, which is estimated through an effective compression algorithm, is investigated to quantify multiscale partition-based K-S entropy on publicly available experimental HRV series gathered from young and elderly subjects undergoing a visual elicitation task (Fantasia). Moreover, publicly available HRV series gathered from healthy subjects, as well as patients with atrial fibrillation and congestive heart failure in unstructured conditions have been analyzed as well. Results: Elderly p...
2020 11th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO), 2020
The continuous reciprocal interplay underlying cerebral and cardiovascular interactions has been ... more The continuous reciprocal interplay underlying cerebral and cardiovascular interactions has been shown to generate complex and nonlinear dynamics. To this extent, differences in induced cross-temporal dynamics are here investigated via wavelet-based multivariate multiscale analysis. Twelve features were extracted from both EEG and ECG recordings from 24 healthy subjects at rest and during a cold-pressor test. The proposed multivariate analysis using the eigenstructure of the multiscale decomposition was compared with a classical multivariate analysis. Preliminary results show that differences between experimental conditions are enhanced by the application of the proposed multivariate analysis.
2020 11th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO), 2020
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific r... more HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
Toward brain–heart computer interfaces: a study on the classification of upper limb movements using multisystem directional estimates
Journal of Neural Engineering, 2021
Objective. Brain–computer interfaces (BCIs) exploit computational features from brain signals to ... more Objective. Brain–computer interfaces (BCIs) exploit computational features from brain signals to perform a given task. Despite recent neurophysiology and clinical findings indicating the crucial role of functional interplay between brain and cardiovascular dynamics in locomotion, heartbeat information remains to be included in common BCI systems. In this study, we exploit the multidimensional features of directional and functional interplay between electroencephalographic and heartbeat spectra to classify upper limb movements into three classes. Approach. We gathered data from 26 healthy volunteers that performed 90 movements; the data were processed using a recently proposed framework for brain–heart interplay (BHI) assessment based on synthetic physiological data generation. Extracted BHI features were employed to classify, through sequential forward selection scheme and k-nearest neighbors algorithm, among resting state and three classes of movements according to the kind of inte...
Quantifying partition-based Kolmogorov-Sinai Entropy on Heart Rate Variability: a young vs. elderly study
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Characterization of upper limb movement-related EEG dynamics through fractional integrated autoregressive modeling
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Recognizing motor imagery tasks from EEG oscillations through a novel ensemble-based neural network architecture
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
U-Limb: A multi-modal, multi-center database on arm motion control in healthy and post-stroke conditions
GigaScience, 2021
Background Shedding light on the neuroscientific mechanisms of human upper limb motor control, in... more Background Shedding light on the neuroscientific mechanisms of human upper limb motor control, in both healthy and disease conditions (e.g., after a stroke), can help to devise effective tools for a quantitative evaluation of the impaired conditions, and to properly inform the rehabilitative process. Furthermore, the design and control of mechatronic devices can also benefit from such neuroscientific outcomes, with important implications for assistive and rehabilitation robotics and advanced human-machine interaction. To reach these goals, we believe that an exhaustive data collection on human behavior is a mandatory step. For this reason, we release U-Limb, a large, multi-modal, multi-center data collection on human upper limb movements, with the aim of fostering trans-disciplinary cross-fertilization. Contribution This collection of signals consists of data from 91 able-bodied and 65 post-stroke participants and is organized at 3 levels: (i) upper limb daily living activities, dur...
2018 Computing in Cardiology Conference (CinC), 2018
Recent modeling advances have successfully derived time-varying estimates of nonlinear heartbeat ... more Recent modeling advances have successfully derived time-varying estimates of nonlinear heartbeat dynamics, whose quantifiers mainly rely on first-order moments (i.e., average over time). While, these metrics account for the information carried by the tonic (slow trend) nonlinear dynamics, they fail to quantify potentially meaningful information nested in the superimposed phasic (high-frequency) activity of the physiological series. In this study, we investigate new metrics from phasic activity of time-varying bispectral indexes, which are derived from nonlinear point-process modeling of heartbeat dynamics. Instantaneous phasic activity is derived using wavelet decomposition of time-varying bispectral power, and quantified using the area under the curve (AUC) and variance (VAR) metrics. Results, gathered from ECG series from 22 healthy volunteers undergoing cold-pressor test (CPT), show that phasic components of low-frequency (LL) instantaneous bispectra significantly change between ...
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020
It is well known that physiological systems show complex and nonlinear behaviours. In spite of th... more It is well known that physiological systems show complex and nonlinear behaviours. In spite of that, functional near-infrared spectroscopy (fNIRS) is usually analyzed in the time and frequency domains with the assumption that metabolic activity is generated from a linear system. To leverage the full information provided by fNIRS signals, in this study we investigate topological entropy in fNIRS series collected from 10 healthy subjects during mental mental arithmetic task. While sample entropy and fuzzy entropy were used to estimate time series irregularity, distribution entropy was used to estimate time series complexity. Our findings show that entropy estimates may provide complementary characterization of fNIRS dynamics with respect to reference time domain measurements. This finding paves the way to further investigate functional activation in fNIRS in different case studies using nonlinear and complexity system theory.
2020 11th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO), 2020
Recent studies have proposed computational models for a functional brain-heart interplay (BHI) as... more Recent studies have proposed computational models for a functional brain-heart interplay (BHI) assessment based on electroencephalography (EEG). Nevertheless, the role of the EEG electrical reference on such BHI estimates has not been investigated yet. Here we present a pilot study assessing BHI in 4 minutes resting-state in 10 healthy subjects through methods including heartbeat-evoked potentials (HEP) and oscillations, Maximal Information Coefficient, and our recently proposed model based on Synthetic Data Generation (SDG). EEG signals were re-referenced to the Cz channel, common average, mastoids, and Laplacian. Results for EEG power in the $\alpha$ band indicate that the most significant differences between BHI methods are with the Laplacian reference while a higher agreement exists between HEP and SDG approaches.
Functional Directional Brain-Heart Interplay Correlates of Dreaming: a Pilot Study
2020 11th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO), 2020
Functional brain-heart interplay (BHI) plays an important role in sleep, however its mediating ro... more Functional brain-heart interplay (BHI) plays an important role in sleep, however its mediating role during a dreaming experience is yet unknown. To this end, in this pilot study we characterize functional directional BHI in two healthy subjects using heart rate variability and electroencephalographic series gathered from REM sleep that leads to a dream recall. Preliminary results show significant differences between non-dream and dream recalls and suggest that dream increases from-brain-to-heart fronto-parietal activity and reduces from-heart-to-brain fronto-occipital activity.
Brain dynamics recorded through electroencephalography (EEG) have been proven to be the output of... more 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 ind...
Cardiac sympathovagal activity initiates a functional brain-body response to emotional processing
A century-long debate on bodily states and emotions persists. While the involvement of bodily act... more A century-long debate on bodily states and emotions persists. While the involvement of bodily activity in emotion physiology is widely recognized, the specificity and causal role of such activity related to brain dynamics has not yet been demonstrated. We hypothesize that the peripheral neural monitoring and control of cardiovascular activity prompts and sustains brain dynamics during an emotional experience, so these afferent inputs are processed by the brain by triggering a concurrent efferent information transfer to the body. To this end, we investigated the functional brain-heart interplay under emotion elicitation in publicly available data from 62 healthy participants using a computational model based on synthetic data generation of EEG and ECG signals. Our findings show that sympathovagal activity plays a leading and causal role in initiating the emotional response, in which ascending modulations from vagal activity precede neural dynamics and correlate to the reported level ...
American Journal of Physiology-Regulatory, Integrative and Comparative Physiology
Dreams may be recalled after awakening from sleep following a defined electroencephalographic pat... more Dreams may be recalled after awakening from sleep following a defined electroencephalographic pattern that involves local decreases in low-frequency activity in the posterior cortical regions. While a dreaming experience implies bodily changes at many organ-, system-, and timescale-levels, the entity and causal role of such peripheral changes in a conscious dream experience are unknown. We performed a comprehensive, causal, multivariate analysis of physiological signals acquired during REM sleep at night, including high-density EEG and peripheral dynamics including electrocardiography and blood pressure. In this preliminary study, we investigated multiple recalls and non-recalls of dream experiences using data from nine healthy volunteers. The aim was not only to investigate the changes in central and autonomic dynamics associated with dream recalls and non-recalls, but also to characterize the central-peripheral dynamical and (causal) directional interactions, and the temporal rela...
An Inhomogeneous Point-process Model for the Assessment of the Brain-to-Heart Functional Interplay: a Pilot Study
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
We propose a novel computational framework for the estimation of functional directional brain-to-... more We propose a novel computational framework for the estimation of functional directional brain-to-heart interplay in an instantaneous fashion. The framework is based on inhomogeneous point-process models for human heartbeat dynamics and employs inverse-Gaussian probability density functions characterizing the timing of R-peak events. The instantaneous estimation of the functional directional coupling is based on the definition of point-process transfer entropy, which is here retrieved from heart rate variability (HRV) and Electroencephalography (EEG) power spectral series gathered from 12 healthy subjects undergoing significant sympathovagal changes induced by a cold-pressor test. Results suggest that EEG oscillations dynamically influence heartbeat dynamics with specific time delays in the 30-60s and 90-120s ranges, and through a functional activity over specific cortical regions.
Functional Analysis of Upper-Limb Movements in the Cartesian Domain
Biosystems & Biorobotics
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Papers by VINCENZO CATRAMBONE