BHI Estimation Methodology

Catrambone, Vincenzo; Valenza, Gaetano

doi:10.1007/978-3-030-79934-2_2

Cited by 3 publications

(7 citation statements)

References 102 publications

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“…BHI has conceptually been linked to the Brain-Heart Axis, a functional system comprising all neural, mechanical, hormonal, and electrical communication pathways between the CNS and ANS. Recent findings highlight that BHI dynamics are highly directional Candia-Rivera et al (2022 ); Catrambone and Valenza (2021 ); Pereira et al (2013 ); Catrambone et al (2021a ); Malandrone et al (2024 ). In healthy individuals, on the one hand, directional BHI is modulated by stress Catrambone et al (2024 ); Candia-Rivera et al (2023 ), as well as emotional processing Candia-Rivera et al (2022 ), with the ascending heart-to-brain changes occurring first in time.…”

Section: Introductionmentioning

confidence: 98%

“…More generally, broader clinical data suggests that a patient’s mood, as well as brain and car-diovascular dynamics are casually related, and so mood disorders may be linked to changes in the CNS-ANS interplay, often referred to as functional Brain–Heart Interplay (BHI) Catrambone and Valenza (2021 ); Taggart et al (2011 ); Valenza (2023 ); Catrambone et al (2021a ); Malandrone et al (2024 ); Verdonk et al (2024 ); Blickle et al (2024 ); Schulz et al (2022 ); Terhaar et al (2012 ). BHI has conceptually been linked to the Brain-Heart Axis, a functional system comprising all neural, mechanical, hormonal, and electrical communication pathways between the CNS and ANS.…”

Section: Introductionmentioning

confidence: 99%

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Impaired functional brain-heart interplay sustains emotion dysregulation in depressed individuals

Catrambone,

Mura,

Patron

et al. 2024

Preprint

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Depression is a leading worldwide cause of mental disorders and disability, strongly affecting emotional processing and regulation. Its dysfunctional psycho-physiological dynamics may be part of the a nervous-system-wise symptomatology, impacting not only patients’ psyche but also significantly influencing functional cardiovascular dynamics. Therefore, depression serves as an exemplary pathological manifestation of the dysfunctional interaction between the central and autonomic nervous systems. While recent literature has been developing specific techniques to quantify such interactions, often referred to as functional Brain-Heart Interplay (BHI), the quantitative role of BHI dynamics in depression is largely unknown. This study aims to experimentally unveil BHI patterns specific to emotional regulation and processing in subjects exhibiting depressive symptoms compared to healthy controls. Results were gathered from a cohort of 72 individuals and indicate that depressive symptoms are associated with a continuous efferent central-to-peripheral hyperactivity and an afferent peripheral-to-central hypoactivity. This hypoactivity appears to be specific to negative emotional processing. This study offers novel insights into the systemic investigation of the neuro-physiological bases of depression.

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Impaired functional brain-heart interplay sustains emotion dysregulation in depressed individuals

Catrambone,

Mura,

Patron

et al. 2024

Preprint

Self Cite

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“…The CAN consists of several components comprising sympathetic and parasympathetic connections to the central nervous system (CNS) and is strictly involved in the definition of functional brain‐heart interplay (BHI). Indeed, the BHI represents the functional outcome of a network of chemical, electrical, and anatomical connections that originates in the CAN (Benarroch, 1993 ; Catrambone & Valenza, 2021 ; Quadt et al, 2022 ; Thome et al, 2017 ; Valenza et al, 2019 ; Valenza et al, 2020 ). Research on functional BHI revealed through the analysis of the EEG and heart rate variability (HRV) series revealed that healthy BHI variations occur as physiological responses to several events, such as emotion perception (Candia‐Rivera, Catrambone, Thayer, et al, 2022 ), alternating sleep stages (Silvani et al, 2016 ), cognitive load (Yu et al, 2018 ), intentional movements (Catrambone, Averta, et al, 2021 ), and autonomic maneuvers (Catrambone, Talebi, et al, 2021 ; Jerath & Barnes, 2009 ).…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, BHI time‐series alterations have been reportedly associated with neuropathological conditions, such as mild depression (Catrambone, Messerotti Benvenuti, et al, 2021 ), epilepsy (Pernice et al, 2022 ), and schizophrenia (Schulz et al, 2013 ). Functional BHI is a directional phenomenon, meaning that the influence of brain activity on cardiovascular function is not necessarily equivalent to the influence of heart activity on cerebral dynamics (Catrambone, Messerotti Benvenuti, et al, 2021 ; Catrambone & Valenza, 2021 ; Catrambone & Valenza, 2023 ). Moreover, BHI is a dynamic process that changes over time and in response to physiological conditions.…”

Section: Introductionmentioning

confidence: 99%

Microstates of the cortical brain‐heart axis

Catrambone,

Valenza

2023

Human Brain Mapping

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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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“…A vast number of analytical and computational approaches have been recently developed to characterize brain-heart interactions. These approaches are specifically devised to quantify the functional coupling between two synchronized time series, one representing the CNS and the other the ANS [11,12,[22][23][24][25][26][27][28][29][30]. The methods developed include simple pairwise linear correlation metrics such as the Pearson's correlation coefficient [24][25][26], time-delay stability linked to the maximum cross-correlation function between the two systems [20], coupling and coherence measures such as synchronization likelihood [27], the Maximal Information Coefficient quantifying linear and nonlinear coupling between concurrent brain-heart outflows [23,28], Joint Symbolic Analysis [29], convergent cross mapping (CCM) assessing bivariate directed nonlinear interactions between dynamical systems [31], or even synthetic data generation models [22,30].…”

Section: Introductionmentioning

confidence: 99%

Pairwise and higher-order measures of brain-heart interactions in children with temporal lobe epilepsy

Pernice¹,

Faes²,

Feucht³

et al. 2022

J. Neural Eng.

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Objective:While it is well-known that epilepsy has a clear impact on the activity of both the central nervous system (CNS) and the autonomic nervous system (ANS), its role on the complex interplay between CNS and ANS has not been fully elucidated yet. In this work, pairwise and higher-order predictability measures based on the concepts of Granger causality (GC) and Partial Information Decomposition (PID) were applied on time series of electroencephalographic (EEG) brain wave amplitude and heart rate variability (HRV) in order to investigate directed brain-heart interactions associated with the occurrence of focal epilepsy. Approach:HRV and the envelopes of δ and α EEG activity recorded from ipsilateral (ipsi-EEG) and contralateral (contra-EEG) scalp regions were analyzed in 18 children suffering from temporal lobe epilepsy monitored during pre-ictal, ictal and post-ictal periods. After linear parametric model identification, we compared pairwise GC measures computed between HRV and a single EEG component with PID measures quantifying the unique, redundant and synergistic information transferred from ipsi-EEG and contra-EEG to HRV. Main results:The analysis of GC revealed a dominance of the information transfer from EEG to HRV and negligible transfer from HRV to EEG, suggesting that CNS activities drive the ANS modulation of the heart rhythm, but did not evidence clear differences between δ and α rhythms, ipsi-EEG and contra-EEG, or pre- and post-ictal periods. On the contrary, PID revealed that epileptic seizures induce a reorganization of the interactions from brain to heart, as the unique predictability of HRV originated from the ipsi-EEG for the δ waves and from the contra-EEG for the α waves in the pre-ictal phase, while these patterns were reversed after the seizure. Significance:These results highlight the importance of considering higher-order interactions elicited by PID for the study of the neuro-autonomic effects of focal epilepsy, and may have neurophysiological and clinical implications.

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BHI Estimation Methodology

Cited by 3 publications

References 102 publications

Impaired functional brain-heart interplay sustains emotion dysregulation in depressed individuals

Impaired functional brain-heart interplay sustains emotion dysregulation in depressed individuals

Microstates of the cortical brain‐heart axis

Pairwise and higher-order measures of brain-heart interactions in children with temporal lobe epilepsy

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