Brain-heart interactions in the neurobiology of consciousness

Mapping Early Brain-Body Interactions: Associations of Fetal Heart Rate Variation with Newborn Brainstem, Hypothalamic, and Dorsal Anterior Cingulate Cortex Functional Connectivity

The autonomic nervous system (ANS) regulates the body's physiology, including cardiovascular function. As the ANS develops during the second to third trimester, fetal heart rate variability (HRV) increases while fetal heart rate (HR) decreases. In this way, fetal HR and HRV provide an index of fetal ANS development and future neurobehavioral regulation. Fetal HR and HRV have been associated with child language ability and psychomotor development behavior in toddlerhood. However, their associations with postbirth autonomic brain systems, such as the brainstem, hypothalamus, and dorsal anterior cingulate cortex (dACC), have yet to be investigated even though brain pathways involved in autonomic regulation are well established in older individuals. We assessed whether fetal HR and HRV were associated with the brainstem, hypothalamic, and dACC functional connectivity in newborns. Data were obtained from 60 pregnant individuals (ages 14-42) at 24-27 and 34-37 weeks of gestation using a fetal actocardiograph to generate fetal HR and HRV. During natural sleep, their infants (38 males and 22 females) underwent a fMRI scan between 40 and 46 weeks of postmenstrual age. Our findings relate fetal heart indices to brainstem, hypothalamic, and dACC connectivity and reveal connections with widespread brain regions that may support behavioral and emotional regulation. We demonstrated the basic physiologic association between fetal HR indices and lower- and higher-order brain regions involved in regulatory processes. This work provides the foundation for future behavioral or physiological regulation research in fetuses and infants.

The Predictive Potential of Heart Rate Variability for Depression

Heart rate variability (HRV),a measure of the fluctuations in the intervals between consecutive heartbeats, is an indicator of changes in the autonomic nervous system. A chronic reduction in HRV has been repeatedly linked to clinical depression. However, the chronological and mechanistic aspects of this relationship, between the neural, physiological, and psychopathological levels, remain unclear. In this review we present evidence by which changes in HRV might precede the onset of depression. We describe several pathways that can facilitate this relationship. First, we examine a theoretical model of the impact of autonomic imbalance on HRV and its role in contributing to mood dysregulation and depression. We then highlight brain regions that are regulating both HRV and emotion, suggesting these neural regions, and the Insula in particular, as potential mediators of this relationship. We also present additional possible mediating mechanisms involving the immune system and inflammation processes. Lastly, we support this model by showing evidence that modification of HRV with biofeedback leads to an improvement in some symptoms of depression. The possibility that changes in HRV precede the onset of depression is critical to put to the test, not only because it could provide insights into the mechanisms of the illness but also because it may offer a predictive anddiagnosticphysiological marker for depression. Importantly, it could also help to develop new effective clinical interventions for treating depression.

Timing along the cardiac cycle modulates neural signals of reward-based learning

Natural fluctuations in cardiac activity modulate brain activity associated with sensory stimuli, as well as perceptual decisions about low magnitude, near-threshold stimuli. However, little is known about the relationship between fluctuations in heart activity and other internal representations. Here we investigate whether the cardiac cycle relates to learning-related internal representations - absolute and signed prediction errors. We combined machine learning techniques with electroencephalography with both simple, direct indices of task performance and computational model-derived indices of learning. Our results demonstrate that just as people are more sensitive to low magnitude, near-threshold sensory stimuli in certain cardiac phases, so are they more sensitive to low magnitude absolute prediction errors in the same cycles. However, this occurs even when the low magnitude prediction errors are associated with clearly suprathreshold sensory events. In addition, participants exhibiting stronger differences in their prediction error representations between cardiac cycles exhibited higher learning rates and greater task accuracy.

A framework for quantifying the coupling between brain connectivity and heartbeat dynamics: Insights into the disrupted network physiology in Parkinson's disease

Parkinson's disease (PD) often shows disrupted brain connectivity and autonomic dysfunctions, progressing alongside with motor and cognitive decline. Recently, PD has been linked to a reduced sensitivity to cardiac inputs, that is, cardiac interoception. Altogether, those signs suggest that PD causes an altered brain-heart connection whose mechanisms remain unclear. Our study aimed to explore the large-scale network disruptions and the neurophysiology of disrupted interoceptive mechanisms in PD. We focused on examining the alterations in brain-heart coupling in PD and their potential connection to motor symptoms. We developed a proof-of-concept method to quantify relationships between the co-fluctuations of brain connectivity and cardiac sympathetic and parasympathetic activities. We quantified the brain-heart couplings from electroencephalogram and electrocardiogram recordings from PD patients on and off dopaminergic medication, as well as in healthy individuals at rest. Our results show that the couplings of fluctuating alpha and gamma connectivity with cardiac sympathetic dynamics are reduced in PD patients, as compared to healthy individuals. Furthermore, we show that PD patients under dopamine medication recover part of the brain-heart coupling, in proportion with the reduced motor symptoms. Our proposal offers a promising approach to unveil the physiopathology of PD and promoting the development of new evaluation methods for the early stages of the disease.

Acute encephalopathy in the ICU: a practical approach

PURPOSE OF REVIEW

Acute encephalopathy (AE) - which frequently develops in critically ill patients with and without primary brain injury - is defined as an acute process that evolves rapidly and leads to changes in baseline cognitive status, ranging from delirium to coma. The diagnosis, monitoring, and management of AE is challenging. Here, we discuss advances in definitions, diagnostic approaches, therapeutic options, and implications to outcomes of the clinical spectrum of AE in ICU patients without primary brain injury.

RECENT FINDINGS

Understanding and definitions of delirium and coma have evolved. Delirium is a neurocognitive disorder involving impairment of attention and cognition, usually fluctuating, and developing over hours to days. Coma is a state of unresponsiveness, with absence of command following, intelligible speech, or visual pursuit, with no imaging or neurophysiological evidence of cognitive motor dissociation. The CAM-ICU(-7) and the ICDSC are validated, guideline-recommended tools for clinical delirium assessment, with identification of clinical subtypes and stratification of severity. In comatose patients, the roles of continuous EEG monitoring and neuroimaging have grown for the early detection of secondary brain injury and treatment of reversible causes.

SUMMARY

Evidence-based pharmacologic treatments for delirium are limited. Dexmedetomidine is effective for mechanically ventilated patients with delirium, while haloperidol has minimal effect of delirium but may have other benefits. Specific treatments for coma in nonprimary brain injury are still lacking.

Aberrant brain-heart coupling is associated with the severity of post cardiac arrest brain injury

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.

Bayesian at heart: Towards autonomic outflow estimation via generative state-space modelling of heart rate dynamics

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.

Blood pressure pulsations modulate central neuronal activity via mechanosensitive ion channels

The transmission of the heartbeat through the cerebral vascular system causes intracranial pressure pulsations. We discovered that arterial pressure pulsations can directly modulate central neuronal activity. In a semi-intact rat brain preparation, vascular pressure pulsations elicited correlated local field oscillations in the olfactory bulb mitral cell layer. These oscillations did not require synaptic transmission but reflected baroreceptive transduction in mitral cells. This transduction was mediated by a fast excitatory mechanosensitive ion channel and modulated neuronal spiking activity. In awake animals, the heartbeat entrained the activity of a subset of olfactory bulb neurons within ~20 milliseconds. Thus, we propose that this fast, intrinsic interoceptive mechanism can modulate perception-for example, during arousal-within the olfactory bulb and possibly across various other brain areas.

Reduced Heartbeat-Evoked Responses in a Near-Death Case Report

BACKGROUND AND PURPOSE

Whether brain-heart communication continues under ventricular fibrillation (VF) remains to be determined. There is weak evidence of physiological changes in cortical activity under VF. Moreover, brain-heart communication has not previously been studied in this condition. We aimed to measure parallel changes in heart-rate variability (HRV), cortical activity, and brain-heart interactions in a patient who experienced VF.

METHODS

The EEG and EKG signals for the case report were acquired for approximately 20 h. We selected different 1-min-long segments based on the changes in the EKG waveform. We present the changes in heartbeat-evoked responses (HERs), HRV, and EEG power for each selected segment.

RESULTS

The overall physiological activity appeared to deteriorate as VF proceeded. Brain-heart interactions measured using HERs disappeared, with a few aberrant amplitudes appearing occasionally. The parallel changes in EEG and HRV were not pronounced, suggesting the absence of bidirectional neural control.

CONCLUSIONS

Our measurements of brain-heart interactions suggested that the evolving VF impairs communication between the central and autonomic nervous systems. These results may support that reduced brain-heart interactions reflect loss of consciousness and deterioration in the overall health state.

Conscious processing of global and local auditory irregularities causes differentiated heartbeat-evoked responses

Recent research suggests that brain-heart interactions are associated with perceptual and self-consciousness. In this line, the neural responses to visceral inputs have been hypothesized to play a leading role in shaping our subjective experience. This study aims to investigate whether the contextual processing of auditory irregularities modulates both direct neuronal responses to the auditory stimuli (ERPs) and the neural responses to heartbeats, as measured with heartbeat-evoked responses (HERs). HERs were computed in patients with disorders of consciousness, diagnosed with a minimally conscious state or unresponsive wakefulness syndrome. We tested whether HERs reflect conscious auditory perception, which can potentially provide additional information for the consciousness diagnosis. EEG recordings were taken during the local-global paradigm, which evaluates the capacity of a patient to detect the appearance of auditory irregularities at local (short-term) and global (long-term) levels. The results show that local and global effects produce distinct ERPs and HERs, which can help distinguish between the minimally conscious state and unresponsive wakefulness syndrome patients. Furthermore, we found that ERP and HER responses were not correlated suggesting that independent neuronal mechanisms are behind them. These findings suggest that HER modulations in response to auditory irregularities, especially local irregularities, may be used as a novel neural marker of consciousness and may aid in the bedside diagnosis of disorders of consciousness with a more cost-effective option than neuroimaging methods.

Variable cardiac responses in rhesus macaque monkeys after discrete mediodorsal thalamus manipulations

The control of some physiological parameters, such as the heart rate, is known to have a role in cognitive and emotional processes. Cardiac changes are also linked to mental health issues and neurodegeneration. Thus, it is not surprising that many of the brain structures typically associated with cognition and emotion also comprise a circuit-the central automatic network-responsible for the modulation of cardiovascular output. The mediodorsal thalamus (MD) is involved in higher cognitive processes and is also known to be connected to some of the key neural structures that regulate cardiovascular function. However, it is unclear whether the MD has any role in this circuitry. Here, we show that discrete manipulations (microstimulation during anaesthetized functional neuroimaging or localized cytotoxin infusions) to either the magnocellular or the parvocellular MD subdivisions led to observable and variable changes in the heart rate of female and male rhesus macaque monkeys. Considering the central positions that these two MD subdivisions have in frontal cortico-thalamocortical circuits, our findings suggest that MD contributions to autonomic regulation may interact with its identified role in higher cognitive processes, representing an important physiological link between cognition and emotion.

Modulation of the heartbeat evoked cortical potential by hypnotizability and hypnosis

Hypnotizability is a psychophysiological trait measured by scales and associated with several differences, including interoceptive accuracy and the morpho-functional characteristics of interoception-related brain regions. The aim of the study was to assess whether the amplitude of the heartbeat evoked cortical potential (HEP), a correlate of interoceptive accuracy, differs in participants with low (lows) and high (highs) hypnotizability scores (assessed by the Stanford Hypnotic Susceptibility Scale, Form A) before and after the induction of hypnosis. ECG and EEG were monitored in 16 highs and 15 lows during an experimental session, including open eyes baseline (B), closed eyes relaxation (R), hypnotic induction (IND), neutral hypnosis (NH), and post session baseline (Post). No significant difference was observed between groups and conditions in autonomic variables. The HEP amplitude was lower in highs than in lows at the right parietal site, likely due to hypnotizability related differences in the functional connection between the right insula and parietal cortex. It increased in highs and decreased in lows across the session, possibly due to the highs' preeminently internally directed attention and to the lows' possible disengagement from the task. Since interoception is involved in several cognitive-emotional functions, its hypnotizability related differences may contribute to the variability of experience and behavior in daily life.

Multidimensional assessment of heartbeat-evoked responses in disorders of consciousness

Because consciousness does not necessarily translate into overt behaviour, detecting residual consciousness in noncommunicating patients remains a challenge. Bedside diagnostic methods based on EEG are promising and cost-effective alternatives to detect residual consciousness. Recent evidence showed that the cortical activations triggered by each heartbeat, namely, heartbeat-evoked responses (HERs), can detect through machine learning the presence of minimal consciousness and distinguish between overt and covert minimal consciousness. In this study, we explore different markers to characterize HERs to investigate whether different dimensions of the neural responses to heartbeats provide complementary information that is not typically found under standard event-related potential analyses. We evaluated HERs and EEG average non-locked to heartbeats in six types of participants: healthy state, locked-in syndrome, minimally conscious state, vegetative state/unresponsive wakefulness syndrome, comatose and brain-dead patients. We computed a series of markers from HERs that can generally separate the unconscious from the conscious. Our findings indicate that HER variance and HER frontal segregation tend to be higher in the presence of consciousness. These indices, when combined with heart rate variability, have the potential to enhance the differentiation between different levels of awareness. We propose that a multidimensional evaluation of brain-heart interactions could be included in a battery of tests to characterize disorders of consciousness. Our results may motivate further exploration of markers in brain-heart communication for the detection of consciousness at the bedside. The development of diagnostic methods based on brain-heart interactions may be translated into more feasible methods for clinical practice.

Association of Hypnotizability, Interoception, and Emotion

The present scoping review reports the reciprocal relations between hypnotizability, interoception, and emotion. Brain morpho-functional differences may account for the lower interoceptive accuracy, higher interoceptive sensitivity, and different emotional strategies observed in highly hypnotizable participants with respect to medium-to-low hypnotizables. Since interoception is relevant to both physical and mental health and hypnotizability can predict both interoceptive abilities and the efficacy of interoception-based mental training, this allows for the development of new forms of treatment and rehabilitation.

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 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.

Modeling brain-heart interactions from Poincaré plot-derived measures of sympathetic-vagal activity

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.

Confounding effects of heart rate, breathing rate, and frontal fNIRS on interoception

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.

Neuroscience of consciousness in the locked-in syndrome: Prognostic and diagnostic review

The neurological illness known as a locked-in syndrome is brought on by damage to the brainstem, usually as a consequence of a stroke. It is characterized by total paralysis with intact consciousness and cognitive capacity. The subjective experiences of people with locked-in syndrome are poorly understood. Presently, there is no systematic evaluation developed to describe them. The most compelling resources come from individuals' own words; however, only a small fraction of these accounts have been explored. When it comes to bioethics, locked-in syndrome protocols are almost completely absent. Investigations on how people with this condition feel about their sense of continuity are of importance. Utilizing the locked-in syndrome to pose questions on embodied cognition and levels of consciousness could serve as a lens through which to examine problems in the phenomenology of neuroparalysis and communication. Care and quality of patients' lives might be improved by an effort to understand this condition better, and ontological questions like "what makes a person a person?," "what makes a person appear in continuity?," and "what are the dynamics of embodiment and intersubjectivity?" might be better explored through that lens. This article aims to explore some biomedical factors that contribute to locked-in syndrome and offers some prognostic and diagnostic recommendations for this rare condition.

From Brain-Body Function to Conscious Interactions

In this review, we discuss empirical results inspiring the introduction of a formal mathematical multilayer model for the biological neuroscience of conscious experience. First, we motivate the discussion through evidence regarding the dynamic brain. Second, we review different brain-body couplings associated with conscious experience and its potential role in driving brain dynamics. Third, we introduce the machinery of multilayer networks to account for several types of interactions in brain-body systems. Then, a multilayer structure consists of two main generalizations: a formal semantic to study biological systems, and an integrative account for several signatures and models of consciousness. Finally, under this framework, we define composition of layers to account for entangled features of brain-body systems related to conscious experience. As such, a multilayer mathematical framework is highly integrative and thus may be more complete than other models. In this short review, we discuss a variety of empirical results inspiring the introduction of a formal mathematical multilayer model for the biological neuroscience of conscious experience.