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Catrambone V, Candia‐Rivera D, Valenza G. Intracortical brain-heart interplay: An EEG model source study of sympathovagal changes. Hum Brain Mapp 2024; 45:e26677. [PMID: 38656080 PMCID: PMC11041380 DOI: 10.1002/hbm.26677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 02/18/2024] [Accepted: 03/23/2024] [Indexed: 04/26/2024] Open
Abstract
The interplay between cerebral and cardiovascular activity, known as the functional brain-heart interplay (BHI), and its temporal dynamics, have been linked to a plethora of physiological and pathological processes. Various computational models of the brain-heart axis have been proposed to estimate BHI non-invasively by taking advantage of the time resolution offered by electroencephalograph (EEG) signals. However, investigations into the specific intracortical sources responsible for this interplay have been limited, which significantly hampers existing BHI studies. This study proposes an analytical modeling framework for estimating the BHI at the source-brain level. This analysis relies on the low-resolution electromagnetic tomography sources localization from scalp electrophysiological recordings. BHI is then quantified as the functional correlation between the intracortical sources and cardiovascular dynamics. Using this approach, we aimed to evaluate the reliability of BHI estimates derived from source-localized EEG signals as compared with prior findings from neuroimaging methods. The proposed approach is validated using an experimental dataset gathered from 32 healthy individuals who underwent standard sympathovagal elicitation using a cold pressor test. Additional resting state data from 34 healthy individuals has been analysed to assess robustness and reproducibility of the methodology. Experimental results not only confirmed previous findings on activation of brain structures affecting cardiac dynamics (e.g., insula, amygdala, hippocampus, and anterior and mid-cingulate cortices) but also provided insights into the anatomical bases of brain-heart axis. In particular, we show that the bidirectional activity of electrophysiological pathways of functional brain-heart communication increases during cold pressure with respect to resting state, mainly targeting neural oscillations in theδ $$ \delta $$ ,β $$ \beta $$ , andγ $$ \gamma $$ bands. The proposed approach offers new perspectives for the investigation of functional BHI that could also shed light on various pathophysiological conditions.
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Affiliation(s)
- Vincenzo Catrambone
- Neurocardiovascular Intelligence Laboratory & Department of Information Engineering & Bioengineering and Robotics Research Center, E. Piaggio, School of EngineeringUniversity of PisaPisaItaly
| | - Diego Candia‐Rivera
- Sorbonne Université, Paris Brain Institute (ICM), INRIA, CNRS, INSERM, AP‐HP, Hôpital Pitié‐SalpêtriŕeParisFrance
| | - Gaetano Valenza
- Neurocardiovascular Intelligence Laboratory & Department of Information Engineering & Bioengineering and Robotics Research Center, E. Piaggio, School of EngineeringUniversity of PisaPisaItaly
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2
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Hermann B, Candia‐Rivera D, Sharshar T, Gavaret M, Diehl J, Cariou A, Benghanem S. Aberrant brain-heart coupling is associated with the severity of post cardiac arrest brain injury. Ann Clin Transl Neurol 2024; 11:866-882. [PMID: 38243640 PMCID: PMC11021613 DOI: 10.1002/acn3.52000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 12/24/2023] [Indexed: 01/21/2024] Open
Abstract
OBJECTIVE To investigate autonomic nervous system activity measured by brain-heart interactions in comatose patients after cardiac arrest in relation to the severity and prognosis of hypoxic-ischemic brain injury. METHODS Strength and complexity of bidirectional interactions between EEG frequency bands (delta, theta, and alpha) and ECG heart rate variability frequency bands (low frequency, LF and high frequency, HF) were computed using a synthetic data generation model. Primary outcome was the severity of brain injury, assessed by (i) standardized qualitative EEG classification, (ii) somatosensory evoked potentials (N20), and (iii) neuron-specific enolase levels. Secondary outcome was the 3-month neurological status, assessed by the Cerebral Performance Category score [good (1-2) vs. poor outcome (3-4-5)]. RESULTS Between January 2007 and July 2021, 181 patients were admitted to ICU for a resuscitated cardiac arrest. Poor neurological outcome was observed in 134 patients (74%). Qualitative EEG patterns suggesting high severity were associated with decreased LF/HF. Severity of EEG changes were proportional to higher absolute values of brain-to-heart coupling strength (p < 0.02 for all brain-to-heart frequencies) and lower values of alpha-to-HF complexity (p = 0.049). Brain-to-heart coupling strength was significantly higher in patients with bilateral absent N20 and correlated with neuron-specific enolase levels at Day 3. This aberrant brain-to-heart coupling (increased strength and decreased complexity) was also associated with 3-month poor neurological outcome. INTERPRETATION Our results suggest that autonomic dysfunctions may well represent hypoxic-ischemic brain injury post cardiac arrest pathophysiology. These results open avenues for integrative monitoring of autonomic functioning in critical care patients.
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Affiliation(s)
- Bertrand Hermann
- Faculté de MédecineUniversité Paris CitéParisFrance
- Medical Intensive Care UnitHEGP Hospital, Assistance Publique ‐ Hôpitaux de Paris‐Centre (APHP.Centre)ParisFrance
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris (IPNP)Université Paris CitéParisFrance
| | - Diego Candia‐Rivera
- Sorbonne Université, Paris Brain Institute (ICM), INRIA, CNRS UMR 722, INSERM U1127, AP‐HP Hôpital Pitié‐SalpêtrièreParisFrance
| | - Tarek Sharshar
- Faculté de MédecineUniversité Paris CitéParisFrance
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris (IPNP)Université Paris CitéParisFrance
- GHU Paris Psychiatrie Neurosciences, Service hospitalo‐universitaire de Neuro‐anesthésie réanimationParisFrance
| | - Martine Gavaret
- Faculté de MédecineUniversité Paris CitéParisFrance
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris (IPNP)Université Paris CitéParisFrance
- Neurophysiology and Epileptology DepartmentGHU Paris Psychiatrie et NeurosciencesParisFrance
| | - Jean‐Luc Diehl
- Faculté de MédecineUniversité Paris CitéParisFrance
- Medical Intensive Care UnitHEGP Hospital, Assistance Publique ‐ Hôpitaux de Paris‐Centre (APHP.Centre)ParisFrance
- Université Paris Cité, INSERM, Innovative Therapies in HaemostasisParisFrance
- Biosurgical Research Lab (Carpentier Foundation)ParisFrance
| | - Alain Cariou
- Faculté de MédecineUniversité Paris CitéParisFrance
- Medical Intensive Care UnitCochin Hospital, Assistance Publique ‐ Hôpitaux de Paris‐Centre (APHP‐Centre)ParisFrance
- Paris‐Cardiovascular‐Research‐CenterINSERM U970ParisFrance
| | - Sarah Benghanem
- Faculté de MédecineUniversité Paris CitéParisFrance
- INSERM UMR 1266, Institut de Psychiatrie et Neurosciences de Paris (IPNP)Université Paris CitéParisFrance
- Medical Intensive Care UnitCochin Hospital, Assistance Publique ‐ Hôpitaux de Paris‐Centre (APHP‐Centre)ParisFrance
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Catrambone V, Zallocco L, Ramoretti E, Mazzoni MR, Sebastiani L, Valenza G. Integrative neuro-cardiovascular dynamics in response to test anxiety: A brain-heart axis study. Physiol Behav 2024; 276:114460. [PMID: 38215864 DOI: 10.1016/j.physbeh.2024.114460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 12/08/2023] [Accepted: 01/08/2024] [Indexed: 01/14/2024]
Abstract
Test anxiety (TA), a recognized form of social anxiety, is the most prominent cause of anxiety among students and, if left unmanaged, can escalate to psychiatric disorders. TA profoundly impacts both central and autonomic nervous systems, presenting as a dual manifestation of cognitive and autonomic components. While limited studies have explored the physiological underpinnings of TA, none have directly investigated the intricate interplay between the CNS and ANS in this context. In this study, we introduce a non-invasive, integrated neuro-cardiovascular approach to comprehensively characterize the physiological responses of 27 healthy subjects subjected to test anxiety induced via a simulated exam scenario. Our experimental findings highlight that an isolated analysis of electroencephalographic and heart rate variability data fails to capture the intricate information provided by a brain-heart axis assessment, which incorporates an analysis of the dynamic interaction between the brain and heart. With respect to resting state, the simulated examination induced a decrease in the neural control onto heartbeat dynamics at all frequencies, while the studying condition induced a decrease in the ascending heart-to-brain interplay at EEG oscillations up to 12Hz. This underscores the significance of adopting a multisystem perspective in understanding the complex and especially functional directional mechanisms underlying test anxiety.
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Affiliation(s)
- Vincenzo Catrambone
- Neurocardiovascular Intelligence Laboratory, Department of Information Engineering & Bioengineering and Robotics Research Center E. Piaggio, School of Engineering, University of Pisa, Pisa, Italy.
| | - Lorenzo Zallocco
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Eleonora Ramoretti
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Maria Rosa Mazzoni
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Laura Sebastiani
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy; Institute of Information Science and Technologies A. Faedo, ISTI-CNR, Pisa, Italy
| | - Gaetano Valenza
- Neurocardiovascular Intelligence Laboratory, Department of Information Engineering & Bioengineering and Robotics Research Center E. Piaggio, School of Engineering, University of Pisa, Pisa, Italy
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Kawashima T, Shiratori H, Amano K. The relationship between alpha power and heart rate variability commonly seen in various mental states. PLoS One 2024; 19:e0298961. [PMID: 38427683 PMCID: PMC10906897 DOI: 10.1371/journal.pone.0298961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 02/01/2024] [Indexed: 03/03/2024] Open
Abstract
The extensive exploration of the correlation between electroencephalogram (EEG) and heart rate variability (HRV) has yielded inconsistent outcomes, largely attributable to variations in the tasks employed in the studies. The direct relationship between EEG and HRV is further complicated by alpha power, which is susceptible to influences such as mental fatigue and sleepiness. This research endeavors to examine the brain-heart interplay typically observed during periods of music listening and rest. In an effort to mitigate the indirect effects of mental states on alpha power, subjective fatigue and sleepiness were measured during rest, while emotional valence and arousal were evaluated during music listening. Partial correlation analyses unveiled positive associations between occipital alpha2 power (10-12 Hz) and nHF, an indicator of parasympathetic activity, under both music and rest conditions. These findings underscore brain-heart interactions that persist even after the effects of other variables have been accounted for.
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Affiliation(s)
- Tomoya Kawashima
- Department of Psychological Science, College of Informatics and Human Communication, Kanazawa Institute of Technology, Nonoichi, Ishikawa, Japan
| | - Honoka Shiratori
- Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Kaoru Amano
- Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
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5
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Rosas FE, Candia-Rivera D, Luppi AI, Guo Y, Mediano PAM. Bayesian at heart: Towards autonomic outflow estimation via generative state-space modelling of heart rate dynamics. Comput Biol Med 2024; 170:107857. [PMID: 38244468 DOI: 10.1016/j.compbiomed.2023.107857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 11/24/2023] [Accepted: 12/11/2023] [Indexed: 01/22/2024]
Abstract
Recent research is revealing how cognitive processes are supported by a complex interplay between the brain and the rest of the body, which can be investigated by the analysis of physiological features such as breathing rhythms, heart rate, and skin conductance. Heart rate dynamics are of particular interest as they provide a way to track the sympathetic and parasympathetic outflow from the autonomic nervous system, which is known to play a key role in modulating attention, memory, decision-making, and emotional processing. However, extracting useful information from heartbeats about the autonomic outflow is still challenging due to the noisy estimates that result from standard signal-processing methods. To advance this state of affairs, we propose a novel approach in how to conceptualise and model heart rate: instead of being a mere summary of the observed inter-beat intervals, we introduce a modelling framework that views heart rate as a hidden stochastic process that drives the observed heartbeats. Moreover, by leveraging the rich literature of state-space modelling and Bayesian inference, our proposed framework delivers a description of heart rate dynamics that is not a point estimate but a posterior distribution of a generative model. We illustrate the capabilities of our method by showing that it recapitulates linear properties of conventional heart rate estimators, while exhibiting a better discriminative power for metrics of dynamical complexity compared across different physiological states.
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Affiliation(s)
- Fernando E Rosas
- School of Engineering and Informatics, University of Sussex, United Kingdom; Centre for Psychedelic Research, Department of Brain Science, Imperial College London, United Kingdom; Centre for Complexity Science, Imperial College London, London, United Kingdom; Centre for Eudaimonia and Human Flourishing, University of Oxford, United Kingdom.
| | - Diego Candia-Rivera
- Sorbonne Université, Paris Brain Institute (ICM), INRIA, CNRS, INSERM, AP-HP, Hôpital Pitié-Salpêtrière, 75013, Paris, France
| | - Andrea I Luppi
- University Division of Anaesthesia, University of Cambridge, Cambridge, United Kingdom; Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Yike Guo
- Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong
| | - Pedro A M Mediano
- Department of Computing, Imperial College London, South Kensington, London, United Kingdom; Department of Psychology, University of Cambridge, Cambridge, United Kingdom
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6
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Tendulkar M, Tendulkar R, Dhanda PS, Yadav A, Jain M, Kaushik P. Clinical potential of sensory neurites in the heart and their role in decision-making. Front Neurosci 2024; 17:1308232. [PMID: 38415053 PMCID: PMC10896837 DOI: 10.3389/fnins.2023.1308232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 11/29/2023] [Indexed: 02/29/2024] Open
Abstract
The process of decision-making is quite complex involving different aspects of logic, emotion, and intuition. The process of decision-making can be summarized as choosing the best alternative among a given plethora of options in order to achieve the desired outcome. This requires establishing numerous neural networks between various factors associated with the decision and creation of possible combinations and speculating their possible outcomes. In a nutshell, it is a highly coordinated process consuming the majority of the brain's energy. It has been found that the heart comprises an intrinsic neural system that contributes not only to the decision-making process but also the short-term and long-term memory. There are approximately 40,000 cells present in the heart known as sensory neurites which play a vital role in memory transfer. The heart is quite a mysterious organ, which functions as a blood-pumping machine and an endocrine gland, as well as possesses a nervous system. There are multiple factors that affect this heart ecosystem, and they directly affect our decision-making capabilities. These interlinked relationships hint toward the sensory neurites which modulate cognition and mood regulation. This review article aims to provide deeper insights into the various roles played by sensory neurites in decision-making and other cognitive functions. The article highlights the pivotal role of sensory neurites in the numerous brain functions, and it also meticulously discusses the mechanisms through which they modulate their effects.
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Affiliation(s)
- Mugdha Tendulkar
- K. J. Somaiya Medical College and Research Centre, Mumbai, India
| | - Reshma Tendulkar
- Vivekanand Education Society's College of Pharmacy, Mumbai, India
| | | | - Alpa Yadav
- Department of Botany, Indira Gandhi University, Rewari, India
| | - Mukul Jain
- Cell and Developmental Biology Lab, Center of Research for Development, Parul University, Vadodara, India
- Department of Life Sciences, Parul Institute of Applied Sciences, Parul University, Vadodara, India
| | - Prashant Kaushik
- Chaudhary Charan Singh Haryana Agricultural University, Hisar, India
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Xu Z, Soh Z, Kurota Y, Kimura Y, Hirano H, Sasaoka T, Yoshino A, Tsuji T. Neuroimaging-based evidence for sympathetic correlation between brain activity and peripheral vasomotion during pain anticipation. Sci Rep 2024; 14:3383. [PMID: 38337009 PMCID: PMC10858222 DOI: 10.1038/s41598-024-53921-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/06/2024] [Indexed: 02/12/2024] Open
Abstract
Anticipation of pain engenders anxiety and fear, potentially shaping pain perception and governing bodily responses such as peripheral vasomotion through the sympathetic nervous system (SNS). Sympathetic innervation of vascular tone during pain perception has been quantified using a peripheral arterial stiffness index; however, its innervation role during pain anticipation remains unclear. This paper reports on a neuroimaging-based study designed to investigate the responsivity and attribution of the index at different levels of anticipatory anxiety and pain perception. The index was measured in a functional magnetic resonance imaging experiment that randomly combined three visual anticipation cues and painful stimuli of two intensities. The peripheral and cerebral responses to pain anticipation and perception were quantified to corroborate bodily responsivity, and their temporal correlation was also assessed to identify the response attribution of the index. Contrasting with the high responsivity across levels of pain sensation, a low responsivity of the index across levels of anticipatory anxiety revealed its specificity across pain experiences. Discrepancies between the effects of perception and anticipation were validated across regions and levels of brain activity, providing a brain basis for peripheral response specificity. The index was also characterized by a 1-s lag in both anticipation and perception of pain, implying top-down innervation of the periphery. Our findings suggest that the SNS responds to pain in an emotion-specific and sensation-unbiased manner, thus enabling an early assessment of individual pain perception using this index. This study integrates peripheral and cerebral hemodynamic responses toward a comprehensive understanding of bodily responses to pain.
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Affiliation(s)
- Ziqiang Xu
- Graduate School of Advanced Science and Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8527, Japan
| | - Zu Soh
- Graduate School of Advanced Science and Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8527, Japan.
| | - Yuta Kurota
- Graduate School of Advanced Science and Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8527, Japan
| | - Yuya Kimura
- Graduate School of Advanced Science and Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8527, Japan
| | - Harutoyo Hirano
- Department of Medical Equipment Engineering, Clinical Collaboration Unit, School of Medical Sciences, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Takafumi Sasaoka
- Center for Brain, Mind and KANSEI Sciences Research, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, Hiroshima, 734-8553, Japan
| | - Atsuo Yoshino
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, Hiroshima, 734-8551, Japan
| | - Toshio Tsuji
- Graduate School of Advanced Science and Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8527, Japan.
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8
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Catrambone V, Valenza G. Microstates of the cortical brain-heart axis. Hum Brain Mapp 2023; 44:5846-5857. [PMID: 37688575 PMCID: PMC10619395 DOI: 10.1002/hbm.26480] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 08/04/2023] [Accepted: 08/24/2023] [Indexed: 09/11/2023] Open
Abstract
Electroencephalographic (EEG) microstates are brain states with quasi-stable scalp topography. Whether such states extend to the body level, that is, the peripheral autonomic nerves, remains unknown. We hypothesized that microstates extend at the brain-heart axis level as a functional state of the central autonomic network. Thus, we combined the EEG and heartbeat dynamics series to estimate the directional information transfer originating in the cortex targeting the sympathovagal and parasympathetic activity oscillations and vice versa for the afferent functional direction. Data were from two groups of participants: 36 healthy volunteers who were subjected to cognitive workload induced by mental arithmetic, and 26 participants who underwent physical stress induced by a cold pressure test. All participants were healthy at the time of the study. Based on statistical testing and goodness-of-fit evaluations, we demonstrated the existence of microstates of the functional brain-heart axis, with emphasis on the cerebral cortex, since the microstates are derived from EEG. Such nervous-system microstates are spatio-temporal quasi-stable states that exclusively refer to the efferent brain-to-heart direction. We demonstrated brain-heart microstates that could be associated with specific experimental conditions as well as brain-heart microstates that are non-specific to tasks.
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Affiliation(s)
- Vincenzo Catrambone
- Neurocardiovascular Intelligence Laboratory, Bioengineering and Robotics Research Center E. Piaggio, & Department of Information Engineering, School of EngineeringUniversity of PisaPisaItaly
| | - Gaetano Valenza
- Neurocardiovascular Intelligence Laboratory, Bioengineering and Robotics Research Center E. Piaggio, & Department of Information Engineering, School of EngineeringUniversity of PisaPisaItaly
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Ghouse A, Candia-Rivera D, Valenza G. Nonlinear neural patterns are revealed in high frequency functional near infrared spectroscopy analysis. Brain Res Bull 2023; 203:110759. [PMID: 37716513 DOI: 10.1016/j.brainresbull.2023.110759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 07/29/2023] [Accepted: 09/11/2023] [Indexed: 09/18/2023]
Abstract
Functional Near Infrared Spectroscopy (fNIRS) is a useful tool for measuring hemoglobin concentration. Linear theory of the hemodynamic response function supports low frequency analysis (<0.2 Hz). However, we hypothesized that nonlinearities, arising from the complex neurovascular interactions sustaining vasomotor tone, may be revealed in higher frequency components of fNIRS signals. To test this hypothesis, we simulated nonlinear hemodynamic models to explore how blood flow autoregulation changes may alter evoked neurovascular signals in high frequencies. Next, we analyzed experimental fNIRS data to compare neural representations between fast (0.2-0.6 Hz) and slow (<0.2 Hz) waves, demonstrating that only nonlinear representations quantified by sample entropy are distinct between these frequency bands. Finally, we performed group-level distance correlation analysis to show that the cortical distribution of activity is independent only in the nonlinear analysis of fast and slow waves. Our study highlights the importance of analyzing nonlinear higher frequency effects seen in fNIRS for a comprehensive analysis of cortical neurovascular activity. Furthermore, it motivates further exploration of the nonlinear dynamics driving regional blood flow and hemoglobin concentrations.
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Affiliation(s)
- Ameer Ghouse
- Bioengineering and Robotics Research Center "E. Piaggio", School of Engineering, University of Pisa, Italy.
| | - Diego Candia-Rivera
- Sorbonne Université, Paris Brain Institute (ICM), INRIA, CNRS, INSERM, AP-HP, Hôpital Pitié-Salpêtrière, Paris, France
| | - Gaetano Valenza
- Department of Information Engineering, School of Engineering, University of Pisa, Italy; Bioengineering and Robotics Research Center "E. Piaggio", School of Engineering, University of Pisa, Italy.
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Dijkstra E, van Dijk H, Vila-Rodriguez F, Zwienenberg L, Rouwhorst R, Coetzee JP, Blumberger DM, Downar J, Williams N, Sack AT, Arns M. Transcranial Magnetic Stimulation-Induced Heart-Brain Coupling: Implications for Site Selection and Frontal Thresholding-Preliminary Findings. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:939-947. [PMID: 37881544 PMCID: PMC10593873 DOI: 10.1016/j.bpsgos.2023.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 12/21/2022] [Accepted: 01/06/2023] [Indexed: 01/26/2023] Open
Abstract
Background Neurocardiac-guided transcranial magnetic stimulation (TMS) uses repetitive TMS (rTMS)-induced heart rate deceleration to confirm activation of the frontal-vagal pathway. Here, we test a novel neurocardiac-guided TMS method that utilizes heart-brain coupling (HBC) to quantify rTMS-induced entrainment of the interbeat interval as a function of TMS cycle time. Because prior neurocardiac-guided TMS studies indicated no association between motor and frontal excitability threshold, we also introduce the approach of using HBC to establish individualized frontal excitability thresholds for optimally dosing frontal TMS. Methods In studies 1A and 1B, we validated intermittent theta burst stimulation (iTBS)-induced HBC (2 seconds iTBS on; 8 seconds off: HBC = 0.1 Hz) in 15 (1A) and 22 (1B) patients with major depressive disorder from 2 double-blind placebo-controlled studies. In study 2, HBC was measured in 10 healthy subjects during the 10-Hz "Dash" protocol (5 seconds 10-Hz on; 11 seconds off: HBC = 0.0625 Hz) applied with 15 increasing intensities to 4 evidence-based TMS locations. Results Using blinded electrocardiogram-based HBC analysis, we successfully identified sham from real iTBS sessions (accuracy: study 1A = 83%, study 1B = 89.5%) and found a significantly stronger HBC at 0.1 Hz in active compared with sham iTBS (d = 1.37) (study 1A). In study 2, clear dose-dependent entrainment (p = .002) was observed at 0.0625 Hz in a site-specific manner. Conclusions We demonstrated rTMS-induced HBC as a function of TMS cycle time for 2 commonly used clinical protocols (iTBS and 10-Hz Dash). These preliminary results supported individual site specificity and dose-response effects, indicating that this is a potentially valuable method for clinical rTMS site stratification and frontal thresholding. Further research should control for TMS side effects, such as pain of stimulation, to confirm these findings.
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Affiliation(s)
- Eva Dijkstra
- Heart & Brain Group, Brainclinics Foundation, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Neurowave, Amsterdam, the Netherlands
| | - Hanneke van Dijk
- Heart & Brain Group, Brainclinics Foundation, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Fidel Vila-Rodriguez
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Lauren Zwienenberg
- Heart & Brain Group, Brainclinics Foundation, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Synaeda Psycho Medisch Centrum, Leeuwarden, the Netherlands
| | - Renée Rouwhorst
- Heart & Brain Group, Brainclinics Foundation, Nijmegen, the Netherlands
- Neurocare group Netherlands, The Hague, the Netherlands
| | - John P. Coetzee
- Department Of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, California
| | - Daniel M. Blumberger
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Jonathan Downar
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Nolan Williams
- Department Of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, California
| | - Alexander T. Sack
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Martijn Arns
- Heart & Brain Group, Brainclinics Foundation, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
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11
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Catrambone V, Valenza G. Complex Brain-Heart Mapping in Mental and Physical Stress. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2023; 11:495-504. [PMID: 37817820 PMCID: PMC10561752 DOI: 10.1109/jtehm.2023.3280974] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 04/29/2023] [Accepted: 05/25/2023] [Indexed: 10/12/2023]
Abstract
OBJECTIVE The central and autonomic nervous systems are deemed complex dynamic systems, wherein each system as a whole shows features that the individual system sub-components do not. They also continuously interact to maintain body homeostasis and appropriate react to endogenous and exogenous stimuli. Such interactions are comprehensively referred to functional brain-heart interplay (BHI). Nevertheless, it remains uncertain whether this interaction also exhibits complex characteristics, that is, whether the dynamics of the entire nervous system inherently demonstrate complex behavior, or if such complexity is solely a trait of the central and autonomic systems. Here, we performed complexity mapping of the BHI dynamics under mental and physical stress conditions. METHODS AND PROCEDURES Electroencephalographic and heart rate variability series were obtained from 56 healthy individuals performing mental arithmetic or cold-pressure tasks, and physiological series were properly combined to derive directional BHI series, whose complexity was quantified through fuzzy entropy. RESULTS The experimental results showed that BHI complexity is mainly modulated in the efferent functional direction from the brain to the heart, and mainly targets vagal oscillations during mental stress and sympathovagal oscillations during physical stress. CONCLUSION We conclude that the complexity of BHI mapping may provide insightful information on the dynamics of both central and autonomic activity, as well as on their continuous interaction. CLINICAL IMPACT This research enhances our comprehension of the reciprocal interactions between central and autonomic systems, potentially paving the way for more accurate diagnoses and targeted treatments of cardiovascular, neurological, and psychiatric disorders.
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Affiliation(s)
- Vincenzo Catrambone
- Neurocardiovascular Intelligence Laboratory, Bioengineering and Robotics Research Center E. Piaggio, and Department of Information EngineeringSchool of EngineeringUniversity of Pisa56126PisaItaly
| | - Gaetano Valenza
- Neurocardiovascular Intelligence Laboratory, Bioengineering and Robotics Research Center E. Piaggio, and Department of Information EngineeringSchool of EngineeringUniversity of Pisa56126PisaItaly
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Candia-Rivera D, Norouzi K, Ramsøy TZ, Valenza G. Dynamic fluctuations in ascending heart-to-brain communication under mental stress. Am J Physiol Regul Integr Comp Physiol 2023; 324:R513-R525. [PMID: 36802949 PMCID: PMC10026986 DOI: 10.1152/ajpregu.00251.2022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
Abstract
Dynamical information exchange between central and autonomic nervous systems, as referred to functional brain-heart interplay, occurs during emotional and physical arousal. It is well documented that physical and mental stress lead to sympathetic activation. Nevertheless, the role of autonomic inputs in nervous system-wise communication under mental stress is yet unknown. In this study, we estimated the causal and bidirectional neural modulations between electroencephalogram (EEG) oscillations and peripheral sympathetic and parasympathetic activities using a recently proposed computational framework for a functional brain-heart interplay assessment, namely the sympathovagal synthetic data generation model. Mental stress was elicited in 37 healthy volunteers by increasing their cognitive demands throughout three tasks associated with increased stress levels. Stress elicitation induced an increased variability in sympathovagal markers, as well as increased variability in the directional brain-heart interplay. The observed heart-to-brain interplay was primarily from sympathetic activity targeting a wide range of EEG oscillations, whereas variability in the efferent direction seemed mainly related to EEG oscillations in the γ band. These findings extend current knowledge on stress physiology, which mainly referred to top-down neural dynamics. Our results suggest that mental stress may not cause an increase in sympathetic activity exclusively as it initiates a dynamic fluctuation within brain-body networks including bidirectional interactions at a brain-heart level. We conclude that directional brain-heart interplay measurements may provide suitable biomarkers for a quantitative stress assessment and bodily feedback may modulate the perceived stress caused by increased cognitive demand.
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Affiliation(s)
- Diego Candia-Rivera
- Department of Information Engineering & Bioengineering and Robotics Research Center E. Piaggio, School of Engineering, University of Pisa, Pisa, Italy
| | - Kian Norouzi
- Department of Applied Neuroscience, Neurons, Inc., Taastrup, Denmark
- Faculty of Management, University of Tehran, Tehran, Iran
| | - Thomas Zoëga Ramsøy
- Department of Applied Neuroscience, Neurons, Inc., Taastrup, Denmark
- Faculty of Neuroscience, Singularity University, Santa Clara, California, United States
| | - Gaetano Valenza
- Department of Information Engineering & Bioengineering and Robotics Research Center E. Piaggio, School of Engineering, University of Pisa, Pisa, Italy
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Candia-Rivera D. Modeling brain-heart interactions from Poincaré plot-derived measures of sympathetic-vagal activity. MethodsX 2023; 10:102116. [PMID: 36970022 PMCID: PMC10034502 DOI: 10.1016/j.mex.2023.102116] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 03/06/2023] [Indexed: 03/09/2023] Open
Abstract
Recent studies suggest that the interaction between the brain and heart plays a key role in cognitive processes, and measuring these interactions is crucial for understanding the interaction between the central and autonomic nervous systems. However, studying this bidirectional interplay presents methodological challenges, and there is still much room for exploration. This paper presents a new computational method called the Poincaré Sympathetic-Vagal Synthetic Data Generation Model (PSV-SDG) for estimating brain-heart interactions. The PSV-SDG combines EEG and cardiac sympathetic-vagal dynamics to provide time-varying and bidirectional estimators of mutual interplay. The method is grounded in the Poincaré plot, a heart rate variability method to estimate sympathetic-vagal activity that can account for potential non-linearities. This algorithm offers a new approach and computational tool for functional assessment of the interplay between EEG and cardiac sympathetic-vagal activity. The method is implemented in MATLAB under an open-source license. • A new brain-heart interaction modeling approach is proposed. • The modeling is based on coupled synthetic data generators of EEG and heart rate series. • Sympathetic and vagal activities are gathered from Poincaré plot geometry.
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Candia-Rivera D, Sappia MS, Horschig JM, Colier WNJM, Valenza G. Confounding effects of heart rate, breathing rate, and frontal fNIRS on interoception. Sci Rep 2022; 12:20701. [PMID: 36450811 PMCID: PMC9712694 DOI: 10.1038/s41598-022-25119-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 11/24/2022] [Indexed: 12/02/2022] Open
Abstract
Recent studies have established that cardiac and respiratory phases can modulate perception and related neural dynamics. While heart rate and respiratory sinus arrhythmia possibly affect interoception biomarkers, such as heartbeat-evoked potentials, the relative changes in heart rate and cardiorespiratory dynamics in interoceptive processes have not yet been investigated. In this study, we investigated the variation in heart and breathing rates, as well as higher functional dynamics including cardiorespiratory correlation and frontal hemodynamics measured with fNIRS, during a heartbeat counting task. To further investigate the functional physiology linked to changes in vagal activity caused by specific breathing rates, we performed the heartbeat counting task together with a controlled breathing rate task. The results demonstrate that focusing on heartbeats decreases breathing and heart rates in comparison, which may be part of the physiological mechanisms related to "listening" to the heart, the focus of attention, and self-awareness. Focusing on heartbeats was also observed to increase frontal connectivity, supporting the role of frontal structures in the neural monitoring of visceral inputs. However, cardiorespiratory correlation is affected by both heartbeats counting and controlled breathing tasks. Based on these results, we concluded that variations in heart and breathing rates are confounding factors in the assessment of interoceptive abilities and relative fluctuations in breathing and heart rates should be considered to be a mode of covariate measurement of interoceptive processes.
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Affiliation(s)
- Diego Candia-Rivera
- Bioengineering and Robotics Research Center E. Piaggio & Department of Information Engineering, School of Engineering, University of Pisa, 56122, Pisa, Italy.
| | - M Sofía Sappia
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW, Elst, The Netherlands
- Donders Institute for Brain, Behaviour and Cognition, Radboud University Nijmegen, 6525 EN, Nijmegen, The Netherlands
| | - Jörn M Horschig
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW, Elst, The Netherlands
| | - Willy N J M Colier
- Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW, Elst, The Netherlands
| | - Gaetano Valenza
- Bioengineering and Robotics Research Center E. Piaggio & Department of Information Engineering, School of Engineering, University of Pisa, 56122, Pisa, Italy
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Candia-Rivera D. Brain-heart interactions in the neurobiology of consciousness. CURRENT RESEARCH IN NEUROBIOLOGY 2022; 3:100050. [PMID: 36685762 PMCID: PMC9846460 DOI: 10.1016/j.crneur.2022.100050] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 07/23/2022] [Accepted: 07/27/2022] [Indexed: 01/25/2023] Open
Abstract
Recent experimental evidence on patients with disorders of consciousness revealed that observing brain-heart interactions helps to detect residual consciousness, even in patients with absence of behavioral signs of consciousness. Those findings support hypotheses suggesting that visceral activity is involved in the neurobiology of consciousness, and sum to the existing evidence in healthy participants in which the neural responses to heartbeats reveal perceptual and self-consciousness. More evidence obtained through mathematical modeling of physiological dynamics revealed that emotion processing is prompted by an initial modulation from ascending vagal inputs to the brain, followed by sustained bidirectional brain-heart interactions. Those findings support long-lasting hypotheses on the causal role of bodily activity in emotions, feelings, and potentially consciousness. In this paper, the theoretical landscape on the potential role of heartbeats in cognition and consciousness is reviewed, as well as the experimental evidence supporting these hypotheses. I advocate for methodological developments on the estimation of brain-heart interactions to uncover the role of cardiac inputs in the origin, levels, and contents of consciousness. The ongoing evidence depicts interactions further than the cortical responses evoked by each heartbeat, suggesting the potential presence of non-linear, complex, and bidirectional communication between brain and heartbeat dynamics. Further developments on methodologies to analyze brain-heart interactions may contribute to a better understanding of the physiological dynamics involved in homeostatic-allostatic control, cognitive functions, and consciousness.
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Candia-Rivera D, Catrambone V, Barbieri R, Valenza G. A new framework for modeling the bidirectional interplay between brain oscillations and cardiac sympathovagal activity. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:1957-1960. [PMID: 36083927 DOI: 10.1109/embc48229.2022.9871169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The study of functional brain-heart interplay (BHI) aims to describe the dynamical interactions between central and peripheral autonomic nervous systems. Here, we introduce the Sympathovagal Synthetic Data Generation Model, which constitutes a new computational framework for the assessment of functional BHI. The model estimates the bidirectional interplay with novel quantifiers of cardiac sympathovagal activity gathered from Laguerre expansions of RR series (from the ECG), as an alternative to the classical spectral analysis. The main features of the model are time-varying coupling coefficients linking Electroencephalography (EEG) oscillations and cardiac sympathetic or parasympathetic activity, for either ascending or descending direction of the information flow. In this proof-of-concept study, functional BHI is quantified in the direction from-heart-to-brain, on data from 16 human volunteers undergoing a cold-pressor test. Results show that thermal stress induces heart-to-brain functional interplay originating from sympathetic and parasympathetic activities and sustaining EEG oscillations mainly in the δ and γ bands. The proposed computational framework could provide a viable tool for the functional assessment of the causal interplay between cortical and cardiac sympathovagal dynamics.
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Cardiac sympathetic-vagal activity initiates a functional brain-body response to emotional arousal. Proc Natl Acad Sci U S A 2022; 119:e2119599119. [PMID: 35588453 PMCID: PMC9173754 DOI: 10.1073/pnas.2119599119] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
We investigate the temporal dynamics of brain and cardiac activities in healthy subjects who underwent an emotional elicitation through videos. We demonstrate that, within the first few seconds, emotional stimuli modulate heartbeat activity, which in turn stimulates an emotion intensity (arousal)–specific cortical response. The emotional processing is then sustained by a bidirectional brain–heart interplay, where the perceived arousal level modulates the amplitude of ascending heart-to-brain neural information flow. These findings may constitute fundamental knowledge linking neurophysiology and psychiatric disorders, including the link between depressive symptoms and cardiovascular disorders. 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 control on 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 subjects using a computational model based on synthetic data generation of electroencephalography and electrocardiography 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 of arousal. The subsequent dynamic interplay observed between the central and autonomic nervous systems sustains the processing of emotional arousal. These findings should be particularly revealing for the psychophysiology and neuroscience of emotions.
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