Nervous–system–wise Functional Estimation of Directed Brain–Heart Interplay through Microstate Occurrences

Background: The quantification of functional brain–heart interplay (BHI) through analysis of the dynamics of the central and autonomic nervous systems provides effective biomarkers for cognitive, emotional, and autonomic state changes. Several computational models have been proposed to estimate BHI, focusing on a single sensor, brain region, or frequency activity. However, no models currently provide a directional estimation of such interplay at the organ level. Objective: This study proposes an analysis framework to estimate BHI that quantifies the directional information flow between whole–brain and heartbeat dynamics. Methods: System–wise directed functional estimation is performed through an ad-hoc symbolic transfer entropy implementation, which leverages on EEG-derived microstate series and on partition of heart rate variability series. The proposed framework is validated on two different experimental datasets: the first investigates the cognitive workload performed through mental arithmetic and the second focuses on an autonomic maneuver using a cold pressor test (CPT). Results: The experimental results highlight a significant bidirectional increase in BHI during cognitive workload with respect to the preceding resting phase and a higher descending interplay during a CPT compared to the preceding rest and following recovery phases. These changes are not detected by the intrinsic self entropy of isolated cortical and heartbeat dynamics. Conclusion: This study corroborates the literature on the BHI phenomenon under these experimental conditions and the new perspective provides novel insights from an organ–level viewpoint. Significance: A system–wise perspective of the BHI phenomenon may provide new insights into physiological and pathological processes that may not be completely understood at a lower level/scale of analysis

The role of the cerebellum in unconsciuos and conscious processing of emotions: a review

Studies from the past three decades have demonstrated that there is cerebellar involvement in the emotional domain. Emotional processing in humans requires both unconscious and conscious mechanisms. A significant amount of evidence indicates that the cerebellum is one of the cerebral structures that subserve emotional processing, although conflicting data have been reported on its function in unconscious and conscious mechanisms. This review discusses the available clinical, neuroimaging and neurophysiological data on this issue. We also propose a model in which the cerebellum acts as a mediator between the internal state and external environment for the unconscious and conscious levels of emotional processing

Dynamic fluctuations in ascending heart-to-brain communication under mental stress

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 c 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

Complex Brain-Heart Mapping in Mental and Physical Stress

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

Microstates of the cortical brain-heart axis

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

Effect of tDCS with an extracephalic reference electrode on cardio-respiratory and autonomic functions

<p>Abstract</p> <p>Background</p> <p>Transcranial direct current stimulation (tDCS) is used in human physiological studies and for therapeutic trials in patients with abnormalities of cortical excitability. Its safety profile places tDCS in the pole-position for translating in real-world therapeutic application. However, an episode of transient respiratory depression in a subject receiving tDCS with an extracephalic electrode led to the suggestion that such an electrode montage could modulate the brainstem autonomic centres.</p> <p>We investigated whether tDCS applied over the midline frontal cortex in 30 healthy volunteers (sham n = 10, cathodal n = 10, anodal n = 10) with an extracephalic reference electrode would modulate brainstem activity as reflected by the monitoring and stringent analysis of vital parameters: heart rate (variability), respiratory rate, blood pressure and sympatho-vagal balance.</p> <p>We reasoned that this study could lead to two opposite but equally interesting outcomes: 1) If tDCS with an extracephalic electrode modulated vital parameters, it could be used as a new tool to explore the autonomic nervous system and, even, to modulate its activity for therapeutic purposes. 2) On the opposite, if applying tDCS with an extracephalic electrode had no effect, it could thus be used safely in healthy human subjects. This outcome would significantly impact the field of non-invasive brain stimulation with tDCS. Indeed, on the one hand, using an extracephalic electrode as a genuine neutral reference (as opposed to the classical "bi-cephalic" tDCS montages which deliver bi-polar stimulation of the brain) would help to comfort the conclusions of several modern studies regarding the spatial location and polarity of tDCS. On the other hand, using an extracephalic reference electrode may impact differently on a given cortical target due to the change of direct current flow direction; this may enlarge the potential interventions with tDCS.</p> <p>Results</p> <p>Whereas the respiratory frequency decreased mildly over time and the blood pressure increased steadily, there was no differential impact of real (anodal or cathodal) <it>versus </it>sham tDCS. The heart rate remained stable during the monitoring period. The parameters reflecting the sympathovagal balance suggested a progressive shift over time favouring the sympathetic tone, again without differential impact of real <it>versus </it>sham tDCS.</p> <p>Conclusions</p> <p>Applying tDCS with an extracephalic reference electrode in healthy volunteers did not significantly modulate the activity of the brainstem autonomic centres. Therefore, using an extracephalic reference electrode for tDCS appears safe in healthy volunteers, at least under similar experimental conditions.</p

Frequency-domain analysis of fNIRS fluctuations induced by rhythmic mental arithmetic

Functional near-infrared spectroscopy (fNIRS) is an increasingly used technology for imaging neural correlates of cognitive processes. However, fNIRS signals are commonly impaired by task-evoked and spontaneous hemodynamic oscillations of non-cerebral origin, a major challenge in fNIRS research. In an attempt to isolate the task-evoked cortical response, we investigated the coupling between hemodynamic changes arising from superficial and deep layers during mental effort. For this aim, we applied a rhythmic mental arithmetic task to induce cyclic hemodynamic fluctuations suitable for effective frequency-resolved measurements. Twenty university students aged 18–25 years (eight males) underwent the task while hemodynamic changes were monitored in the forehead using a newly developed NIRS device, capable of multi-channel and multi-distance recordings. We found significant task-related fluctuations for oxy-and deoxy-hemoglobin, highly coherent across shallow and deep tissue layers, corroborating the strong influence of surface hemodynamics on deep fNIRS signals. Importantly, after removing such surface contamination by linear regression, we show that the frontopolar cortex response to a mental math task follows an unusual inverse oxygenation pattern. We confirm this finding by applying for the first time an alternative method to estimate the neural signal, based on transfer function analysis and phasor algebra. Altogether, our results demonstrate the feasibility of using a rhythmic mental task to impose an oscillatory state useful to separate true brain functional responses from those of non-cerebral origin. This separation appears to be essential for a better understanding of fNIRS data and to assess more precisely the dynamics of the neuro-visceral link

RESEARCH OF HUMAN FATIGUE AND MEASUREMENT PARAMETERS FOR WORKABILITY ASSESSMENT

Human fatigue is reduced working capability for certain period of time as the result of unusual or prolonged workload. Fatigue arises when the body’s energy requirements exceed its supply. Fatigue first manifests as reduced concentration capability causing movement coordination and precision disruption leading to decreasing workability. Fatigue is an object of research in physiology, psychology, work ergonomics, medicine, and biotechnology where each domain has a focus on mental fatigue. The functional state in the context of professional activity is defined as a complex of characteristics of functions and qualities that determine the fulfilment of labour activity. Furthermore, a comprehensive estimation of subject functional state in combination with other factors like subject self-assessment and objective performance tests (cognitive load tests) is a necessary input for the evaluation of workability and efficiency on task. The heterogeneous nature of fatigue as a systemic manifestation requires analysis of multiple key parameters which are relevant to the specific type. The current feasibility study focuses on human biological signal from electrical activity of heart, brain, muscles and skin potentials as well as temperature, position, and respiration to obtain diagnostic parameters reflecting the state of cardiovascular, muscles, and central nervous systems for physiological monitoring of vital signs. The fatigue physiological parameter and feature formalization aim to support the development of a platform with complex passive multi-level fatigue monitoring system and workability evaluation system designed in order to provide an integrated service

Physiological Noise: Definition, Estimation, and Characterization in Complex Biomedical Signals

Background: Nonlinear physiological systems exhibit complex dynamics driven by intrinsic dynamical noise. In cases where there is no specific knowledge or assumption about system dynamics, such as in physiological systems, it is not possible to formally estimate noise. Aim: We introduce a formal method to estimate the power of dynamical noise, referred to as physiological noise, in a closed form, without specific knowledge of the system dynamics. Methodology: Assuming that noise can be modeled as a sequence of independent, identically distributed (IID) random variables on a probability space, we demonstrate that physiological noise can be estimated through a nonlinear entropy profile. We estimated noise from synthetic maps that included autoregressive, logistic, and Pomeau-Manneville systems under various conditions. Noise estimation is performed on 70 heart rate variability series from healthy and pathological subjects, and 32 electroencephalographic (EEG) healthy series. Results: Our results showed that the proposed model-free method can discern different noise levels without any prior knowledge of the system dynamics. Physiological noise accounts for around 11% of the overall power observed in EEG signals and approximately 32% to 65% of the power related to heartbeat dynamics. Cardiovascular noise increases in pathological conditions compared to healthy dynamics, and cortical brain noise increases during mental arithmetic computations over the prefrontal and occipital regions. Brain noise is differently distributed across cortical regions. Conclusion: Physiological noise is very part neurobiological dynamics and can be measured using the proposed framework in any biomedical series