Aroused with heart: Modulation of heartbeat evoked potential by arousal induction and its oscillatory correlates

Neural Interoceptive Processing Is Modulated by Deep Brain Stimulation to Subcallosal Cingulate Cortex for Treatment-Resistant Depression

BACKGROUND

Symptoms of depression are associated with impaired interoceptive processing of bodily sensation. The antidepressant effects of subcallosal cingulate deep brain stimulation (SCC DBS) include acute change in bodily sensation, and the SCC target is connected to cortical regions critically involved in interoception. This study tested whether cortical interoceptive processing is modulated by SCC DBS for treatment-resistant depression.

METHODS

In 8 patients receiving SCC DBS for treatment-resistant depression, we used electroencephalography to measure the heartbeat-evoked potential (HEP), a putative readout of neural interoception, before surgery and over 6 months of treatment with DBS. We also examined the immediate effect of DBS on the HEP and correlated HEP change over time with outcomes of treatment for depression.

RESULTS

HEP amplitude increased from baseline to 6 months of DBS treatment, and this increase was associated with faster antidepressant response. Recording with stimulation on (vs. off) had an immediate effect on HEP in the laboratory. Overall, modulation of the HEP was most pronounced in sensors over the left parietal cortex.

CONCLUSIONS

Brain-based evidence implies an interoceptive element in the mechanism of treatment efficacy with DBS for treatment-resistant depression and substantiates a theorized connection between interoception and depression.

Neural sensitivity to the heartbeat is modulated by spontaneous fluctuations in subjective arousal during wakeful rest

Spontaneous thoughts, occupying much of one's awake time in daily time, are often colored by emotional qualities. While spontaneous thoughts have been associated with various neural correlates, the relationship between subjective qualities of ongoing experiences and the brain's sensitivity to bodily signals (i.e., interoception) remains largely unexplored. Given the well-established role of interoception in emotion, clarifying this relationship may elucidate how processes relevant to mental health, such as arousal and anxiety, are regulated. We used EEG and ECG to measure the heartbeat evoked potential (HEP), an index of interoceptive processing, while 51 adult participants (34 male, 20 female) visually fixated on a cross image and let their minds wander freely. At pseudo-random intervals, participants reported their momentary level of arousal. This measure of subjective arousal was highly variable within and between individuals but was statistically unrelated to several markers of physiological arousal, including heart rate, heart rate variability, time on task, and EEG alpha power at posterior electrodes. A cluster-based permutation analysis revealed that the HEP amplitude was increased during low relative to high subjective arousal in a set of frontal electrodes during the 0.328 s - 0.364 s window after heartbeat onset. This HEP effect was more pronounced in individuals who reported high, relative to low, levels of state anxiety. Together, our results offer novel evidence that at varying levels of state anxiety, the brain differentially modulates sensitivity to bodily signals in coordination with the momentary, spontaneous experience of subjective arousal-a mechanism that may operate independently of physiological arousal.

Significance Statement

Our findings highlight the relationships between spontaneous fluctuations in subjective arousal, brain-body interactions, and anxiety, offering new insights into how interoception fluctuates with changes in internal states. By showing that interoceptive processing is heightened during lower subjective arousal and that this effect is amplified in individuals with higher state anxiety, our study suggests the brain adaptively downregulates interoceptive sensitivity in response to fluctuating internal states. These results have implications for understanding how spontaneous thoughts shape interoception and emotion, particularly in clinical contexts where dysregulated interoception is linked to anxiety and mood disorders. More broadly, our work underscores the need to distinguish between different forms of arousal, advancing understanding of the taxonomy and ways of measuring arousal.

Prediction of Alpha Power Using Multiple Subjective Measures and Autonomic Responses

Alpha oscillations are associated with various cognitive functions. However, the determinants of alpha power variation remain ambiguous, primarily due to its inconsistent associations with autonomic responses and subjective states under different experimental conditions. To thoroughly examine the correlations between alpha power variation and these factors, we implemented a range of experimental conditions, encompassing attentional and emotional tasks, as well as a resting-state. In addition to the electroencephalogram data, we gathered a suite of autonomic response measurements and subjective ratings. We employed multiple linear regression analysis, utilizing autonomic responses and subjective reports as predictors of alpha power. We also subtracted the aperiodic components for better estimation of the power of periodic alpha oscillations. Our results from two separately conducted experiments robustly demonstrated that the combined use of autonomic response measurements and subjective ratings effectively predicted the parietal-occipital periodic alpha power variation across a range of conditions. These predictions were supported by leave-one-participant-out cross-validation and cross-experiment validation, confirming that multiple linear relationships can be generalized to new participants. This study demonstrates the links of alpha power variations with autonomic responses and subjective states, suggesting that during investigations of the cognitive functions of alpha oscillations, it is important to consider the potential influences of autonomic responses and subjective states on alpha oscillations.

Exploring the Link Between Interoception and Symptom Severity in Premature Ventricular Contractions

Background/Objectives: The physiological basis underlying symptomatic versus asymptomatic premature ventricular contractions (PVCs) remains poorly understood. However, symptomatic PVCs can significantly impair quality of life. In patients without structural heart disease, symptom intensity is crucial for guiding management strategies and determining the need for medical or surgical intervention. In this study, we aimed, for the first time, to examine the associations between PVC symptoms and cardiac interoception. Methods: This study included 34 participants with PVCs (20 women; median age = 42 years; 17 participants had asymptomatic PVCs) without concomitant disorders. Interoception was assessed through interoceptive accuracy (IA) probed by two behavioral tests-mental tracking (MT) and heartbeat detection (HBD)-and the neurophysiological marker of cardiac interoception, the heartbeat-evoked potentials (HEPs). Symptom intensity scores reported by patients served as the response variable in the regression analysis, with IA and HEP as predictors. Other factors such as sex, age, percent of body fat, trait anxiety, and alexithymia were added to the models as confounding variables. Results: IAMT was significantly higher in patients with symptomatic PVCs. IAMT and HEP modulation for the HBD task were associated with symptom intensity. A combined regression model incorporating both metrics showed the highest predictive accuracy for symptom severity. Adding confounding variables improved model quality (lower AIC); however, only the male sex emerged as a significant negative predictor for symptom intensity. Conclusions: Our findings confirm a significant association between interoception and PVC symptom severity. Integrating behavioral and neurophysiological interoception measures enhances symptom prediction accuracy, suggesting new ways to develop diagnostic and non-invasive treatment strategies targeting interoception in PVC management.

The effect of cardiac phase on distractor suppression and motor inhibition in a stop-signal task

Past work has shown that stimuli timed to the cardiac systole, the time at which heartbeat feedback is transmitted to the brain, can be more effectively selected from conflicting information. Here, we investigated how the temporal alignment of distracting information to different phases of the cardiac cycle impacts inhibitory performance on a stop-signal task. While participants received the go-cue and anticipated a potential stop-signal, we presented several moving dots on the screen. The dots' change of movement direction was timed to occur 290 ms posterior to the R-peak (for cardiac systole) or right at the R-peak (for cardiac diastole) of in-time ECG recordings. In a third control condition, no distracting dots were shown. Behavioural results found participants were significantly better at inhibiting their motor response in systole relative to diastole distractor trials. Electrophysiological evidence found reduced P2 amplitudes for viewing the distractors and enhanced N2 amplitudes to the subsequent stop-signal in systole relative to diastole distractor trials. This indicated that systole bound distractors were suppressed more effectively than diastole bound ones which led to enhanced motor inhibition. Our results indicate that the brain shows greater visual selection efficiency for distracting information co-occurring with cardiac systole which has implications for enhanced motor processing at later stages of the trial sequence.

Linking brain-heart interactions to emotional arousal in immersive virtual reality

The subjective experience of emotions is linked to the contextualized perception and appraisal of changes in bodily (e.g., heart) activity. Increased emotional arousal has been related to attenuated high-frequency heart rate variability (HF-HRV), lower EEG parieto-occipital alpha power, and higher heartbeat-evoked potential (HEP) amplitudes. We studied emotional arousal-related brain-heart interactions using immersive virtual reality (VR) for naturalistic yet controlled emotion induction. Twenty-nine healthy adults (13 women, age: 26 ± 3) completed a VR experience that included rollercoasters while EEG and ECG were recorded. Continuous emotional arousal ratings were collected during a video replay immediately after. We analyzed emotional arousal-related changes in HF-HRV as well as in BHIs using HEPs. Additionally, we used the oscillatory information in the ECG and the EEG to model the directional information flows between the brain and heart activity. We found that higher emotional arousal was associated with lower HEP amplitudes in a left fronto-central electrode cluster. While parasympathetic modulation of the heart (HF-HRV) and parieto-occipital EEG alpha power were reduced during higher emotional arousal, there was no evidence for the hypothesized emotional arousal-related changes in bidirectional information flow between them. Whole-brain exploratory analyses in additional EEG (delta, theta, alpha, beta and gamma) and HRV (low-frequency, LF, and HF) frequency bands revealed a temporo-occipital cluster, in which higher emotional arousal was linked to decreased brain-to-heart (i.e., gamma→HF-HRV) and increased heart-to-brain (i.e., LF-HRV → gamma) information flow. Our results confirm previous findings from less naturalistic experiments and suggest a link between emotional arousal and brain-heart interactions in temporo-occipital gamma power.

Effects of unconscious tactile stimuli on autonomic nervous activity and afferent signal processing

Autonomic nervous system (ANS) is a mechanism that regulates our internal environment. In recent years, the interest in how tactile stimuli presented directly to the body affect ANS function and cortical processing in humans has been renewed. However, it is not yet clear how subtle tactile stimuli below the level of consciousness affect human heart rate and cortical processing. To examine this, subthreshold electrical stimuli were presented to the left forearm of 43 participants during an image-viewing task, and electrocardiogram (ECG) and electroencephalogram (EEG) data were collected. The changes in the R-wave interval of the ECG immediately after the subthreshold electrical presentation and heartbeat-evoked potential (HEP), the afferent signal processing of cardiac activity, were measured. The results showed that heart rate decelerated immediately after the presentation of subthreshold electrical stimuli. The HEP during stimulus presentation was amplified for participants with greater heart rate acceleration immediately after this deceleration. The magnitude of these effects depended on the type of the subthreshold tactile stimuli. The results suggest that even with subthreshold stimulation, the changes in autonomic activity associated with orienting response and related afferent signal processing differ depending on the clarity of the tactile stimuli.

Towards an ecologically valid naturalistic cognitive neuroscience of memory and event cognition

The landscape of human memory and event cognition research has witnessed a transformative journey toward the use of naturalistic contexts and tasks. In this review, we track this progression from abrupt, artificial stimuli used in extensively controlled laboratory experiments to more naturalistic tasks and stimuli that present a more faithful representation of the real world. We argue that in order to improve ecological validity, naturalistic study designs must consider the complexity of the cognitive phenomenon being studied. Then, we review the current state of "naturalistic" event segmentation studies and critically assess frequently employed movie stimuli. We evaluate recently developed tools like lifelogging and other extended reality technologies to help address the challenges we identified with existing naturalistic approaches. We conclude by offering some guidelines that can be used to design ecologically valid cognitive neuroscience studies of memory and event cognition.

Heartbeat-related spectral perturbation of electroencephalogram reflects dynamic interoceptive attention states in the trial-by-trial classification analysis

Attending to heartbeats for interoceptive awareness initiates distinct electrophysiological responses synchronized with the R-peaks of an electrocardiogram (ECG), such as the heartbeat-evoked potential (HEP). Beyond HEP, this study proposes heartbeat-related spectral perturbation (HRSP), a time-frequency map of the R-peak locked electroencephalogram (EEG), and explores its characteristics in identifying interoceptive attention states using a classification approach. HRSPs of EEG brain components specified by independent component analysis (ICA) were used for the offline and online classification of interoceptive states. A convolutional neural network (CNN) designed specifically for HRSP was applied to publicly available data from a binary-state experiment (attending to self-heartbeats and white noise) and data from our four-state classification experiment (attending to self-heartbeats, white noise, time passage, and toe) with diverse input feature conditions of HRSP. From the dynamic state perspective, we evaluated the primary frequency bands of HRSP and the minimal number of averaging epochs required to reflect changing interoceptive attention states without compromising accuracy. We also assessed the utility of group ICA and models for classifying HRSP in new participants. The CNN for trial-by-trial HRSP with actual R-peaks demonstrated significantly higher classification accuracy than HRSP with sham, i.e., randomly positioned, R-peaks. Gradient-weighted class activation mapping highlighted the prominent role of theta and alpha bands between 200-600 ms post-R-peak-features absent in classifications using sham HRSPs. Online classification benefits from employing a group ICA and classification model, ensuring reliable accuracy without individual EEG precollection. These results suggest HRSP's potential to reflect interoceptive attention states, proposing transformative implications for clinical applications.

Individual Differences in Bodily Self-Consciousness and Its Neural Basis

Bodily self-consciousness (BSC), a subject of interdisciplinary interest, refers to the awareness of one's bodily states. Previous studies have noted the existence of individual differences in BSC, while neglecting the underlying factors and neural basis of such individual differences. Considering that BSC relied on integration from both internal and external self-relevant information, we here review previous findings on individual differences in BSC through a three-level-self model, which includes interoceptive, exteroceptive, and mental self-processing. The data show that cross-level factors influenced individual differences in BSC, involving internal bodily signal perceptibility, multisensory processing principles, personal traits shaped by environment, and interaction modes that integrate multiple levels of self-processing. Furthermore, in interoceptive processing, regions like the anterior cingulate cortex and insula show correlations with different perceptions of internal sensations. For exteroception, the parietal lobe integrates sensory inputs, coordinating various BSC responses. Mental self-processing modulates differences in BSC through areas like the medial prefrontal cortex. For interactions between multiple levels of self-processing, regions like the intraparietal sulcus involve individual differences in BSC. We propose that diverse experiences of BSC can be attributed to different levels of self-processing, which moderates one's perception of their body. Overall, considering individual differences in BSC is worth amalgamating diverse methodologies for the diagnosis and treatment of some diseases.

A neurophysiological profiling of the heartbeat-evoked potential in severe acquired brain injuries: A focus on unconsciousness

Unconsciousness in severe acquired brain injury (sABI) patients occurs with different cognitive and neural profiles. Perturbational approaches, which enable the estimation of proxies for brain reorganization, have added a new avenue for investigating the non-behavioural diagnosis of consciousness. In this prospective observational study, we conducted a comparative analysis of the topological patterns of heartbeat-evoked potentials (HEP) between patients experiencing a prolonged disorder of consciousness (pDoC) and patients emerging from a minimally consciousness state (eMCS). A total of 219 sABI patients were enrolled, each undergoing a synchronous EEG-ECG resting-state recording, together with a standardized consciousness diagnosis. A number of graph metrics were computed before/after the HEP (Before/After) using the R-peak on the ECG signal. The peak value of the global field power of the HEP was found to be significantly higher in eMCS patients with no difference in latency. Power spectrum was not able to discriminate consciousness neither Before nor After. Node assortativity and global efficiency were found to vary with different trends at unconsciousness. Lastly, the Perturbational Complexity Index of the HEP was found to be significantly higher in eMCS patients compared with pDoC. Given that cortical elaboration of peripheral inputs may serve as a non-behavioural determinant of consciousness, we have devised a low-cost and translatable technique capable of estimating causal proxies of brain functionality with an endogenous, non-invasive stimulus. Thus, we present an effective means to enhance consciousness assessment by incorporating the interaction between the autonomic nervous system (ANS) and central nervous system (CNS) into the loop.

Heartbeat-evoked potentials following voluntary hyperventilation in epilepsy patients: respiratory influences on cardiac interoception

Introduction

Current evidence indicates a modulating role of respiratory processes in cardiac interoception, yet whether altered breathing patterns influence heartbeat-evoked potentials (HEP) remains inconclusive.

Methods

Here, we examined the effects of voluntary hyperventilation (VH) as part of a clinical routine examination on scalp-recorded HEPs in epilepsy patients (N = 80).

Results

Using cluster-based permutation analyses, HEP amplitudes were compared across pre-VH and post-VH conditions within young and elderly subgroups, as well as for the total sample. No differences in the HEP were detected for younger participants or across the full sample, while an increased late HEP during pre-VH compared to post-VH was fond in the senior group, denoting decreased cardiac interoceptive processing after hyperventilation.

Discussion

The present study, thus, provides initial evidence of breathing-related HEP modulations in elderly epilepsy patients, emphasizing the potential of HEP as an interoceptive neural marker that could partially extend to the representation of pulmonary signaling. We speculate that aberrant CO2-chemosensing, coupled with disturbances in autonomic regulation, might constitute the underlying pathophysiological mechanism behind the obtained effect. Available databases involving patient records of routine VH assessment may constitute a valuable asset in disentangling the interplay of cardiac and ventilatory interoceptive information in various patient groups, providing thorough clinical data to parse, as well as increased statistical power and estimates of effects with higher precision through large-scale studies.

Heartbeat-evoked neural response abnormalities in generalized anxiety disorder during peripheral adrenergic stimulation

Hyperarousal symptoms in generalized anxiety disorder (GAD) are often incongruent with the observed physiological state, suggesting that abnormal processing of interoceptive signals is a characteristic feature of the disorder. To examine the neural mechanisms underlying interoceptive dysfunction in GAD, we evaluated whether adrenergic modulation of cardiovascular signaling differentially affects the heartbeat-evoked potential (HEP), an electrophysiological marker of cardiac interoception, during concurrent electroencephalogram and functional magnetic resonance imaging (EEG-fMRI) scanning. Intravenous infusions of the peripheral adrenergic agonist isoproterenol (0.5 and 2.0 micrograms, μg) were administered in a randomized, double-blinded and placebo-controlled fashion to dynamically perturb the cardiovascular system while recording the associated EEG-fMRI responses. During the 0.5 μg isoproterenol infusion, the GAD group (n = 24) exhibited significantly larger changes in HEP amplitude in an opposite direction than the healthy comparison (HC) group (n = 24). In addition, the GAD group showed significantly larger absolute HEP amplitudes than the HC group during saline infusions, when cardiovascular tone did not increase. No significant group differences in HEP amplitude were identified during the 2.0 μg isoproterenol infusion. Using analyzable blood oxygenation level-dependent fMRI data from participants with concurrent EEG-fMRI data (21 GAD and 21 HC), we found that the aforementioned HEP effects were uncorrelated with fMRI signals in the insula, ventromedial prefrontal cortex, dorsal anterior cingulate cortex, amygdala, and somatosensory cortex, brain regions implicated in cardiac signal processing in prior fMRI studies. These findings provide additional evidence of dysfunctional cardiac interoception in GAD and identify neural processes at the electrophysiological level that may be independent from blood oxygen level-dependent responses during peripheral adrenergic stimulation.

Heartbeat evoked potentials and autonomic arousal during dissociative seizures: insights from electrophysiology and neuroimaging

Introduction

Dissociative seizures often occur in the context of dysregulated affective arousal and entail dissociative symptoms such as a disintegration of bodily awareness. However, the interplay between affective arousal and changes in interoceptive processing at the onset of dissociative seizures is not well understood.

Methods

Using retrospective routine data obtained from video-electroencephalography telemetry in a university hospital epilepsy monitoring unit, we investigate ictal changes in cardiac indices of autonomic arousal and heartbeat evoked potentials (HEPs) in 24 patients with dissociative seizures.

Results

Results show autonomic arousal during seizures with increased heart rate and a shift towards sympathetic activity. Compared with baseline, ictal HEP amplitudes over central and right prefrontal electrodes (F8, Fz) were significantly less pronounced during seizures, suggesting diminished cortical representation of interoceptive information. Significant correlations between heart rate variability measures and HEPs were observed at baseline, with more sympathetic and less parasympathetic activity related to less pronounced HEPs. Interestingly, these relationships weakened during seizures, suggesting a disintegration of autonomic arousal and interoceptive processing during dissociative seizures. In a subgroup of 16 patients, MRI-based cortical thickness analysis found a correlation with HEP amplitudes in the left somatosensory association cortex.

Conclusions

These findings possibly represent an electrophysiological hint of how autonomic arousal could negatively impact bodily awareness in dissociative seizures, and how these processes might be related to underlying brain structure.

Interoception as a function of hypnotizability during rest and a heartbeat counting task

The hypnotizability-related differences in morpho-functional characteristics of the insula could at least partially account for the differences in interoceptive accuracy (IA) observed between high and low hypnotizable individuals (highs, lows). Our aim was to investigate interoceptive processing in highs, lows, and medium hypnotizable individuals (mediums), who represent most of the population, during a 10-minute open eyes relaxation condition (Part 1) and three repetitions of consecutive 2-minute open eyes, closed eyes, and heartbeat counting conditions, followed by a 2-minute post-counting condition (Part 2). Electrocardiogram and electroencephalogram were recorded in 14 highs, 14 mediums, and 18 lows, classified according to the Stanford Hypnotic Susceptibility Scale: Form A. Heartbeat-evoked cortical potentials (HEP) were extracted throughout the entire session, and IA index was obtained for the heartbeat counting task (HCT). In Part 1, significant hypnotizability-related differences were observed in the right central region in both early and late HEP components, with lows showing positive amplitudes and highs/mediums showing negative amplitudes. In Part 2, the same group differences were limited to the early component. Moreover, in the left frontal regions, only mediums modified their HEP during the counting task with respect to the open/closed eyes conditions, whereas highs displayed HEP differences between counting and post-counting rest. HCT did not show significant group differences. In conclusion, highs and mediums seem to be more similar than mediums and lows regarding HEP, despite the absence of significant differences in HCT. Nonetheless, a negative correlation between hypnotizability scores and HEP amplitudes was observed in the regions showing group differences.

The Neurophysiology of Interoceptive Disruptions in Trauma-Exposed Populations

In the aftermath of psychological trauma, many individuals experience perturbations in interoception, a term that broadly references the ability to accurately detect body signals and integrate these signals with emotional states. These interoceptive disruptions can manifest in different ways, including blunting or amplification of sensitivity to internal physiological signals. In this chapter we review extant neurophysiological research on interoception in trauma-exposed populations, with a particular focus on the effects of chronic interpersonal trauma, such as childhood maltreatment and racial discrimination. We explore research that used different types of interoceptive assays, from self-report measures to electrophysiological and neuroimaging tools to characterize the disruptions in pain perception, interoceptive acuity, and physiological responses that may arise after a traumatic event. Finally, we discuss interventions that are designed to target interoceptive mechanisms, from exposure-based therapies to mindfulness-based practices, as well as future directions in trauma interoception research.

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.

The relationship between alpha power and heart rate variability commonly seen in various mental states

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.

Exploring the neural underpinnings of chord prediction uncertainty: an electroencephalography (EEG) study

Predictive processing in the brain, involving interaction between interoceptive (bodily signal) and exteroceptive (sensory) processing, is essential for understanding music as it encompasses musical temporality dynamics and affective responses. This study explores the relationship between neural correlates and subjective certainty of chord prediction, focusing on the alignment between predicted and actual chord progressions in both musically appropriate chord sequences and random chord sequences. Participants were asked to predict the final chord in sequences while their brain activity was measured using electroencephalography (EEG). We found that the stimulus preceding negativity (SPN), an EEG component associated with predictive processing of sensory stimuli, was larger for non-harmonic chord sequences than for harmonic chord progressions. Additionally, the heartbeat evoked potential (HEP), an EEG component related to interoceptive processing, was larger for random chord sequences and correlated with prediction certainty ratings. HEP also correlated with the N5 component, found while listening to the final chord. Our findings suggest that HEP more directly reflects the subjective prediction certainty than SPN. These findings offer new insights into the neural mechanisms underlying music perception and prediction, emphasizing the importance of considering auditory prediction certainty when examining the neural basis of music cognition.

Cardiac interoception in infants: Behavioral and neurophysiological measures in various emotional and self-related contexts

Interoception, the perception of internal bodily signals, is fundamental to our sense of self. Even though theoretical accounts suggest an important role for interoception in the development of the self, empirical investigations are limited, particularly in infancy. Previous studies used preferential-looking paradigms to assess the detection of sensorimotor and multisensory contingencies in infancy, usually related to proprioception and touch. So far, only one recent study reported that infants discriminated between audiovisual stimuli presented synchronously or asynchronously with their heartbeat. This discrimination was related to the amplitude of the infant's heartbeat evoked potentials (HEP), a neural correlate of interoception. In the current study, we measured looking preferences between synchronous and asynchronous visuocardiac (bimodal), and audiovisuocardiac (trimodal) stimuli as well as the HEP in conditions of different emotional contexts and with different degrees of self-relatedness in a mirror-like setup. While the infants preferred trimodal to bimodal stimuli, we did not observe the predicted differences between synchronous and asynchronous stimulation. Furthermore, the HEP was not modulated by emotional context or self-relatedness. These findings do not support previously published results and highlight the need for further studies on the early development of interoception in relation to the development of the self.

Elevated EEG heartbeat-evoked potentials in adolescents with more ADHD symptoms

INTRODUCTION

Symptoms of attention deficit hyperactivity disorder (ADHD) are associated with a variety of mental abnormalities, but little is known about the perception and processing of internal signals, i.e., interoception, in individuals with ADHD symptoms. This study aimed to investigate the association between ADHD symptoms and the heartbeat-evoked potential (HEP), known as a neural correlate of automatic interoceptive processing of cardiac signals, in adolescents.

METHODS

HEPs of 47 healthy adolescent participants (53.2 % female) with a mean age of 14.29 years were measured during an emotional face recognition task. In addition, participants completed a self-report screening for ADHD symptoms.

RESULTS

ADHD symptoms were positively related to the HEP activity during the task in three of eight EEG sectors in the left hemisphere, as well as in all sectors in the right hemisphere.

DISCUSSION

This study is the first to demonstrate preliminary a relationship between the strength of HEP activity and ADHD symptoms in awake subjects. This finding of higher HEP amplitudes in subjects with more ADHD symptoms can be interpreted in terms of (i) increased arousal, (ii) altered neural processing of internal processes in an emotion-relevant task, and (iii) a misaligned precision-weighting process of task-irrelevant stimuli according to the predictive coding framework. These different interpretations could be reflected by previous studies showing heterogeneity of psychological deficits in individuals with ADHD symptoms. However, the generalizability to patients with diagnosed ADHD is limited due to the measurement tool for ADHD symptoms and the sample characteristics.

Time-varying information measures: an adaptive estimation of information storage with application to brain-heart interactions

Network Physiology is a rapidly growing field of study that aims to understand how physiological systems interact to maintain health. Within the information theory framework the information storage (IS) allows to measure the regularity and predictability of a dynamic process under stationarity assumption. However, this assumption does not allow to track over time the transient pathways occurring in the dynamical activity of a physiological system. To address this limitation, we propose a time-varying approach based on the recursive least squares algorithm (RLS) for estimating IS at each time instant, in non-stationary conditions. We tested this approach in simulated time-varying dynamics and in the analysis of electroencephalographic (EEG) signals recorded from healthy volunteers and timed with the heartbeat to investigate brain-heart interactions. In simulations, we show that the proposed approach allows to track both abrupt and slow changes in the information stored in a physiological system. These changes are reflected in its evolution and variability over time. The analysis of brain-heart interactions reveals marked differences across the cardiac cycle phases of the variability of the time-varying IS. On the other hand, the average IS values exhibit a weak modulation over parieto-occiptal areas of the scalp. Our study highlights the importance of developing more advanced methods for measuring IS that account for non-stationarity in physiological systems. The proposed time-varying approach based on RLS represents a useful tool for identifying spatio-temporal dynamics within the neurocardiac system and can contribute to the understanding of brain-heart interactions.

Removing the cardiac field artifact from the EEG using neural network regression

When EEG recordings are used to reveal interactions between central-nervous and cardiovascular processes, the cardiac field artifact (CFA) poses a major challenge. Because the electric field generated by cardiac activity is also captured by scalp electrodes, the CFA arises as a heavy contaminant whenever EEG data are analyzed time-locked to cardio-electric events. A typical example is measuring stimulus-evoked potentials elicited at different phases of the cardiac cycle. Here, we present a nonlinear regression method deploying neural networks that allows to remove the CFA from the EEG signal in such scenarios. We train neural network models to predict R-peak centered EEG episodes based on the ECG and additional CFA-related information. In a second step, these trained models are used to predict and consequently remove the CFA in EEG episodes containing visual stimulation occurring time-locked to the ECG. We show that removing these predictions from the signal effectively removes the CFA without affecting the intertrial phase coherence of stimulus-evoked activity. In addition, we provide the results of an extensive grid search suggesting a set of appropriate model hyperparameters. The proposed method offers a replicable way of removing the CFA on the single-trial level, without affecting stimulus-related variance occurring time-locked to cardiac events. Disentangling the cardiac field artifact (CFA) from the EEG signal is a major challenge when investigating the neurocognitive impact of cardioafferent traffic by means of the EEG. When stimuli are presented time-locked to the cardiac cycle, both sources of variance are systematically confounded. Here, we propose a regression-based approach deploying neural network models to remove the CFA from the EEG. This approach effectively removes the CFA on a single-trial level and is purely data-driven, providing replicable results.

Aesthetic and physiological effects of naturalistic multimodal music listening

Compared to audio only (AO) conditions, audiovisual (AV) information can enhance the aesthetic experience of a music performance. However, such beneficial multimodal effects have yet to be studied in naturalistic music performance settings. Further, peripheral physiological correlates of aesthetic experiences are not well-understood. Here, participants were invited to a concert hall for piano performances of Bach, Messiaen, and Beethoven, which were presented in two conditions: AV and AO. They rated their aesthetic experience (AE) after each piece (Experiment 1 and 2), while peripheral signals (cardiorespiratory measures, skin conductance, and facial muscle activity) were continuously measured (Experiment 2). Factor scores of AE were significantly higher in the AV condition in both experiments. LF/HF ratio, a heart rhythm that represents activation of the sympathetic nervous system, was higher in the AO condition, suggesting increased arousal, likely caused by less predictable sound onsets in the AO condition. We present partial evidence that breathing was faster and facial muscle activity was higher in the AV condition, suggesting that observing a performer's movements likely enhances motor mimicry in these more voluntary peripheral measures. Further, zygomaticus ('smiling') muscle activity was a significant predictor of AE. Thus, we suggest physiological measures are related to AE, but at different levels: the more involuntary measures (i.e., heart rhythms) may reflect more sensory aspects, while the more voluntary measures (i.e., muscular control of breathing and facial responses) may reflect the liking aspect of an AE. In summary, we replicate and extend previous findings that AV information enhances AE in a naturalistic music performance setting. We further show that a combination of self-report and peripheral measures benefit a meaningful assessment of AE in naturalistic music performance settings.

Interoceptive rhythms in the brain

Sensing internal bodily signals, or interoception, is fundamental to maintain life. However, interoception should not be viewed as an isolated domain, as it interacts with exteroception, cognition and action to ensure the integrity of the organism. Focusing on cardiac, respiratory and gastric rhythms, we review evidence that interoception is anatomically and functionally intertwined with the processing of signals from the external environment. Interactions arise at all stages, from the peripheral transduction of interoceptive signals to sensory processing and cortical integration, in a network that extends beyond core interoceptive regions. Interoceptive rhythms contribute to functions ranging from perceptual detection up to sense of self, or conversely compete with external inputs. Renewed interest in interoception revives long-standing issues on how the brain integrates and coordinates information in distributed regions, by means of oscillatory synchrony, predictive coding or multisensory integration. Considering interoception and exteroception in the same framework paves the way for biological modes of information processing specific to living organisms.

A Review of Recurrent Neural Network-Based Methods in Computational Physiology

Artificial intelligence and machine learning techniques have progressed dramatically and become powerful tools required to solve complicated tasks, such as computer vision, speech recognition, and natural language processing. Since these techniques have provided promising and evident results in these fields, they emerged as valuable methods for applications in human physiology and healthcare. General physiological recordings are time-related expressions of bodily processes associated with health or morbidity. Sequence classification, anomaly detection, decision making, and future status prediction drive the learning algorithms to focus on the temporal pattern and model the nonstationary dynamics of the human body. These practical requirements give birth to the use of recurrent neural networks (RNNs), which offer a tractable solution in dealing with physiological time series and provide a way to understand complex time variations and dependencies. The primary objective of this article is to provide an overview of current applications of RNNs in the area of human physiology for automated prediction and diagnosis within different fields. Finally, we highlight some pathways of future RNN developments for human physiology.

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.

Brain State Relays Self-Processing and Heartbeat-Evoked Cortical Responses

The self has been proposed to be grounded in interoceptive processing, with heartbeat-evoked cortical activity as a neurophysiological marker of this processing. However, inconsistent findings have been reported on the relationship between heartbeat-evoked cortical responses and self-processing (including exteroceptive- and mental-self-processing). In this review, we examine previous research on the association between self-processing and heartbeat-evoked cortical responses and highlight the divergent temporal-spatial characteristics and brain regions involved. We propose that the brain state relays the interaction between self-processing and heartbeat-evoked cortical responses and thus accounts for the inconsistency. The brain state, spontaneous brain activity which highly and continuously changes in a nonrandom way, serves as the foundation upon which the brain functions and was proposed as a point in an extremely high-dimensional space. To elucidate our assumption, we provide reviews on the interactions between dimensions of brain state with both self-processing and heartbeat-evoked cortical responses. These interactions suggest the relay of self-processing and heartbeat-evoked cortical responses by brain state. Finally, we discuss possible approaches to investigate whether and how the brain state impacts the self-heart interaction.

The reality of virtual reality

Virtual reality (VR) has become a popular tool for investigating human behavior and brain functions. Nevertheless, it is unclear whether VR constitutes an actual form of reality or is more like an advanced simulation. Determining the nature of VR has been mostly achieved by self-reported presence measurements, defined as the feeling of being submerged in the experience. However, subjective measurements might be prone to bias and, most importantly, do not allow for a comparison with real-life experiences. Here, we show that real-life and VR height exposures using 3D-360° videos are mostly indistinguishable on a psychophysiological level (EEG and HRV), while both differ from a conventional 2D laboratory setting. Using a fire truck, three groups of participants experienced a real-life (N = 25), a virtual (N = 24), or a 2D laboratory (N = 25) height exposure. Behavioral and psychophysiological results suggest that identical exogenous and endogenous cognitive as well as emotional mechanisms are deployed to process the real-life and virtual experience. Specifically, alpha- and theta-band oscillations in line with heart rate variability, indexing vigilance, and anxiety were barely indistinguishable between those two conditions, while they differed significantly from the laboratory setup. Sensory processing, as reflected by beta-band oscillations, exhibits a different pattern for all conditions, indicating further room for improving VR on a haptic level. In conclusion, the study shows that contemporary photorealistic VR setups are technologically capable of mimicking reality, thus paving the way for the investigation of real-world cognitive and emotional processes under controlled laboratory conditions. For a video summary, see https://youtu.be/fPIrIajpfiA.

Dual interaction between heartbeat-evoked responses and stimuli

Heartbeat-evoked responses (HERs) can interact with external stimuli and play a crucial role in shaping perception, self-related processes, and emotional processes. On the one hand, the external stimulus could modulate HERs. On the other hand, the HERs could affect cognitive processing of the external stimulus. Whether the same neural mechanism underlies these two processes, however, remains unclear. Here, we investigated this interactive mechanism by measuring HERs using magnetoencephalography (MEG) and two name perception tasks. Specifically, we tested (1) how hearing a subject's own name (SON) modulates HERs and (2) how the judgment of an SON is biased by prestimulus HERs. The results showed a dual interaction between HERs and SON. In particular, SON can modulate HERs for heartbeats occurring from 200 to 1200 ms after SON presentation. In addition, prestimulus HERs can bias the SON judgment when a stimulus is presented. Importantly, MEG activities from these two types of interactions differed in spatial and temporal patterns, suggesting that they may be associated with distinct neural pathways. These findings extend our understanding of brain-heart interactions.

Neurophysiological and Subjective Analysis of VR Emotion Induction Paradigm

The ecological validity of emotion-inducing scenarios is essential for emotion research. In contrast to the classical passive induction paradigm, immersive VR fully engages the psychological and physiological components of the subject, which is considered an ecologically valid paradigm for studying emotion. Several studies investigate the emotional responses to different VR tasks or games using subjective scales. However, little research regards VR as an eliciting material, especially when systematically analyzing emotional processes in VR from a neurophysiological perspective. To fill this gap and scientifically evaluate VR's ability to be used as an active method for emotion elicitation, we investigate the dynamic relationship between explicit information (subjective evaluations) and implicit information (objective neurophysiological data). A total of 28 participants are enlisted to watch eight VR videos while their SAM/IPQ scores and EEG data are recorded simultaneously. In ecologically valid scenarios, the subjective results demonstrate that VR has significant advantages for evoking emotion in arousal-valence. This conclusion is backed by our examination of objective neurophysiological evidence that VR videos effectively induce high-arousal emotions. In addition, we obtain features of critical channels and frequency oscillations associated with emotional valence, thereby validating previous research in more lifelike circumstances. In particular, we discover hemispheric asymmetry in the occipital region under high and low emotional arousal, which adds to our understanding of neural features and the dynamics of emotional arousal. As a result, we successfully integrate EEG and VR to demonstrate that VR is more pragmatic for evoking natural feelings and is beneficial for emotional research. Our research has set a precedent for new methodologies of using VR induction paradigms to acquire a more reliable explanation of affective computing.

Predictive coding, multisensory integration, and attentional control: A multicomponent framework for lucid dreaming

Lucid dreaming (LD) is a mental state in which we realize not being awake but are dreaming while asleep. It often involves vivid, perceptually intense dream images as well as peculiar kinesthetic sensations, such as flying, levitating, or out-of-body experiences. LD is in the cross-spotlight of cognitive neuroscience and sleep research as a particular case to study consciousness, cognition, and the neural background of dream experiences. Here, we present a multicomponent framework for the study and understanding of neurocognitive mechanisms and phenomenological aspects of LD. We propose that LD is associated with prediction error signals arising during sleep and occurring at higher or lower levels of the processing hierarchy. Prediction errors are resolved by generating a superordinate self-model able to integrate ambiguous stimuli arriving from sensory periphery and higher-order cortical regions. While multisensory integration enables lucidity maintenance and contributes to peculiar kinesthetic experiences, attentional control facilitates multisensory integration by dynamically regulating the balance between the influence of top-down mental models and the precision weighting of bottom-up sensory inputs. Our novel framework aims to link neural correlates of LD with current concepts of sleep and arousal regulation and provide testable predictions on interindividual differences in LD as well as neurocognitive mechanisms inducing lucid dreams.

Dynamic coupling between the central and autonomic cardiac nervous systems in patients with refractory epilepsy: A pilot study

The heart and brain are reciprocally interconnected and engage in two-way communication for homeostatic regulation. Epilepsy is considered a network disease that also affects the autonomic nervous system (ANS). The neurovisceral integration model (NVM) proposes that cardiac vagal tone, indexed by heart rate variability (HRV), can indicate the functional integrity of cognitive neural networks. ANS activity and the pattern of oscillatory EEG activity covary during the transition of arousal states and associations between cortical and autonomic activity are reflected by HRV. Cognitive dysfunction is one of the common comorbidities that occur in epilepsy, including memory, attention, and processing difficulties. Recent studies have shown evidence for the active involvement of alpha activity in cognitive processes through its active role in the control of neural excitability in the cortex through top-down modulation of cortical networks. In the present pilot study, we evaluated the association between resting EEG oscillatory behavior and ANS function in patients with refractory epilepsy. Our results show: (1) In patients with refractory epilepsy, there is a strong positive correlation between HRV and the power of cortical oscillatory cortical activity in all studied EEG bands (delta, theta, alpha, and beta) in all regions of interest in both hemispheres, the opposite pattern found in controls which had low or negative correlation between these variables; (2) higher heartbeat evoked potential amplitudes in patients with refractory epilepsy than in controls. Taken together, these results point to a significant alteration in heart-brain interaction in patients with refractory epilepsy.

Interoception Underlies Therapeutic Effects of Mindfulness Meditation for Posttraumatic Stress Disorder: A Randomized Clinical Trial

BACKGROUND

Mindfulness-based interventions have proven efficacy in treating posttraumatic stress disorder (PTSD), but the neurobiological mechanism underlying the therapeutic effects is unknown. As mindfulness meditation cultivates attention to the present moment and bodily sensations, neural functions related to interoception (i.e., central processes of bodily signals) might be such a mechanism.

METHODS

We conducted a clinical trial in which veterans with PTSD were randomly assigned to receive an 8-week mindfulness-based stress reduction (MBSR) intervention (n = 47) or an active control intervention (present-centered group therapy; n = 51). We assessed pre- and postintervention PTSD symptoms and electroencephalography measures of neural outcomes, including spontaneous brain activity, cognitive task-related brain responses, and interoceptive brain responses (heartbeat-evoked brain responses). We conducted statistical causal mediation analyses using treatment type as a predictor, pre- and postintervention measures of symptom severity as treatment response, and the neural outcomes as mediators.

RESULTS

Compared with the control group, the MBSR group had greater improvements in PTSD symptoms and increases in spontaneous alpha power (8-13 Hz), task-related frontal theta power (4-7 Hz in 140-220 ms after stimulus), and frontal theta heartbeat-evoked brain responses (3-5 Hz and 265-336 ms after R peak). The mediation analysis using latent difference score modeling revealed that only changes in frontal theta heartbeat-evoked brain responses mediated the MBSR treatment effect.

CONCLUSIONS

Mindfulness meditation improves brain functions of attentional control and resting brain states reflective of internally oriented relaxation. However, interoceptive neural functions enhanced by MBSR seem to be a primary cerebral mechanism that improves symptoms of PTSD.

Allostatic-Interoceptive Overload in Frontotemporal Dementia

BACKGROUND

The predictive coding theory of allostatic-interoceptive load states that brain networks mediating autonomic regulation and interoceptive-exteroceptive balance regulate the internal milieu to anticipate future needs and environmental demands. These functions seem to be distinctly compromised in behavioral variant frontotemporal dementia (bvFTD), including alterations of the allostatic-interoceptive network (AIN). Here, we hypothesize that bvFTD is typified by an allostatic-interoceptive overload.

METHODS

We assessed resting-state heartbeat evoked potential (rsHEP) modulation as well as its behavioral and multimodal neuroimaging correlates in patients with bvFTD relative to healthy control subjects and patients with Alzheimer's disease (N = 94). We measured 1) resting-state electroencephalography (to assess the rsHEP, prompted by visceral inputs and modulated by internal body sensing), 2) associations between rsHEP and its neural generators (source location), 3) cognitive disturbances (cognitive state, executive functions, facial emotion recognition), 4) brain atrophy, and 5) resting-state functional magnetic resonance imaging functional connectivity (AIN vs. control networks).

RESULTS

Relative to healthy control subjects and patients with Alzheimer's disease, patients with bvFTD presented more negative rsHEP amplitudes with sources in critical hubs of the AIN (insula, amygdala, somatosensory cortex, hippocampus, anterior cingulate cortex). This exacerbated rsHEP modulation selectively predicted the patients' cognitive profile (including cognitive decline, executive dysfunction, and emotional impairments). In addition, increased rsHEP modulation in bvFTD was associated with decreased brain volume and connectivity of the AIN. Machine learning results confirmed AIN specificity in predicting the bvFTD group.

CONCLUSIONS

Altogether, these results suggest that bvFTD may be characterized by an allostatic-interoceptive overload manifested in ongoing electrophysiological markers, brain atrophy, functional networks, and cognition.

Cardiac-Brain Dynamics Depend on Context Familiarity and Their Interaction Predicts Experience of Emotional Arousal

Our brain continuously interacts with the body as we engage with the world. Although we are mostly unaware of internal bodily processes, such as our heartbeats, they may be influenced by and in turn influence our perception and emotional feelings. Although there is a recent focus on understanding cardiac interoceptive activity and interaction with brain activity during emotion processing, the investigation of cardiac-brain interactions with more ecologically valid naturalistic emotional stimuli is still very limited. We also do not understand how an essential aspect of emotions, such as context familiarity, influences affective feelings and is linked to statistical interaction between cardiac and brain activity. Hence, to answer these questions, we designed an exploratory study by recording ECG and EEG signals for the emotional events while participants were watching emotional movie clips. Participants also rated their familiarity with the stimulus on the familiarity scale. Linear mixed effect modelling was performed in which the ECG power and familiarity were considered as predictors of EEG power. We focused on three brain regions, including prefrontal (PF), frontocentral (FC) and parietooccipital (PO). The analyses showed that the interaction between the power of cardiac activity in the mid-frequency range and the power in specific EEG bands is dependent on familiarity, such that the interaction is stronger with high familiarity. In addition, the results indicate that arousal is predicted by cardiac-brain interaction, which also depends on familiarity. The results support emotional theories that emphasize context dependency and interoception. Multimodal studies with more realistic stimuli would further enable us to understand and predict different aspects of emotional experience.

Cardiac sympathetic-vagal activity initiates a functional brain-body response to emotional arousal

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.

Brain–Heart Interaction and the Experience of Flow While Playing a Video Game

The flow state – an experience of complete absorption in an activity – is linked with less self-referential processing and increased arousal. We used the heart-evoked potential (HEP), an index representing brain–heart interaction, as well as indices of peripheral physiology to assess the state of flow in individuals playing a video game. 22 gamers and 21 non-gamers played the video game Thumper for 25 min while their brain and cardiorespiratory signals were simultaneously recorded. The more participants were absorbed in the game, the less they thought about time and the faster time passed subjectively. On the cortical level, the fronto-central HEP amplitude was significantly lower while playing the game compared to resting states before and after the game, reflecting less self-referential processing while playing. This HEP effect corresponded with lower activity during gameplay in brain regions contributing to interoceptive processing. The HEP amplitude predicted the level of absorption in the game. While the HEP amplitude was overall lower during the gaming session than during the resting states, within the gaming session the amplitude of HEP was positively associated with absorption. Since higher absorption was related to higher performance in the game, the higher HEP in more absorbed individuals reflects more efficient brain–heart interaction, which is necessary for efficient game play. On the physiological level, a higher level of flow was associated with increased overall sympathetic activity and less inhibited parasympathetic activity toward the end of the game. These results are building blocks for future neurophysiological assessments of flow.

The heartbeat evoked potential is a questionable biomarker in nightmare disorder: A replication study

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Perogamvros et al. (2013) examined heart beat evoked potential (HEP) in nightmare sufferers.

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Increased HEP was proposed to be a robust biomarker in nightmare disorder.

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We aimed to replicate the original study in two separate and larger databases.

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We did not confirm the original finding showing differential HEP in REM sleep.

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Our data cast doubts on the utility of HEP as a biomarker in nightmare disorder.

Frequent nightmares are highly prevalent and constitute a risk factor for a wide range of psychopathological conditions. Despite its prevalence and clinical relevance however, the pathophysiological mechanisms of nightmares are poorly understood. A recent study (Perogamvros et, al 2019) examined the heart beat evoked potential (HEP) in a small group of nightmare sufferers (N = 11) and matched healthy controls (N = 11) and observed markedly different (Hedges’ g = 1.42 [0.62–2.22]) HEP response across the groups during Rapid Eye Movement (REM) sleep. Moreover, the HEP correlated with depression scores in the nightmare group only. The authors concluded that the HEP in REM sleep could be used as a trait-like biomarker reflecting pathological emotional-and sleep regulation in nightmare disorder. To replicate the above study, we performed the same analyses of HEPs in two separate, and larger databases comprising the polysomnographic recordings of nightmare sufferers and matched controls (N_{Study 1} = 39 ; N_{Study 2} = 41). In contrast to the original findings, we did not observe significant differences in HEP across the two groups in either of the two databases. Moreover, we found no associations between depression scores and HEP amplitudes in the relevant spatiotemporal cluster. Our data cast doubts on the utility of HEP as a biomarker in the diagnostic and treatment procedures of nightmare disorder and suggests that the interpretation of HEP as a marker of impaired arousal and emotional processing during REM sleep is premature and requires further validation.

Cognitive processing of a common stimulus synchronizes brains, hearts, and eyes

Neural, physiological, and behavioral signals synchronize between human subjects in a variety of settings. Multiple hypotheses have been proposed to explain this interpersonal synchrony, but there is no clarity under which conditions it arises, for which signals, or whether there is a common underlying mechanism. We hypothesized that cognitive processing of a shared stimulus is the source of synchrony between subjects, measured here as intersubject correlation (ISC). To test this, we presented informative videos to participants in an attentive and distracted condition and subsequently measured information recall. ISC was observed for electro-encephalography, gaze position, pupil size, and heart rate, but not respiration and head movements. The strength of correlation was co-modulated in the different signals, changed with attentional state, and predicted subsequent recall of information presented in the videos. There was robust within-subject coupling between brain, heart, and eyes, but not respiration or head movements. The results suggest that ISC is the result of effective cognitive processing, and thus emerges only for those signals that exhibit a robust brain-body connection. While physiological and behavioral fluctuations may be driven by multiple features of the stimulus, correlation with other individuals is co-modulated by the level of attentional engagement with the stimulus.

Decoding subjective emotional arousal from EEG during an immersive virtual reality experience

Immersive virtual reality (VR) enables naturalistic neuroscientific studies while maintaining experimental control, but dynamic and interactive stimuli pose methodological challenges. We here probed the link between emotional arousal, a fundamental property of affective experience, and parieto-occipital alpha power under naturalistic stimulation: 37 young healthy adults completed an immersive VR experience, which included rollercoaster rides, while their EEG was recorded. They then continuously rated their subjective emotional arousal while viewing a replay of their experience. The association between emotional arousal and parieto-occipital alpha power was tested and confirmed by (1) decomposing the continuous EEG signal while maximizing the comodulation between alpha power and arousal ratings and by (2) decoding periods of high and low arousal with discriminative common spatial patterns and a long short-term memory recurrent neural network. We successfully combine EEG and a naturalistic immersive VR experience to extend previous findings on the neurophysiology of emotional arousal towards real-world neuroscience.

How do we relate to our heart? Neurobehavioral differences across three types of engagement with cardiac interoception

Standard measures of interoception are typically limited to the conscious perception of heartbeats. However, the fundamental purpose of interoceptive signaling, is to regulate the body. We present a novel biofeedback paradigm to explore the neurobehavioral consequences of three different types of engagement with cardiac interoception (Attend, Feel, Regulate) while participants perform a 'cardiac recognition' task. For both the Feel and Regulate conditions, participants displayed enhanced recognition of their own heartbeat, accompanied by larger heartbeat-evoked potentials (HEPs), suggesting that these approaches could be used interchangeably. Importantly, meta-cognitive interoceptive insight was highest in the Regulate condition, indicative of stronger engagement with interoceptive signals in addition to greater ecological validity. Only in the passive interoception condition (Feel) was a significant association found between accuracy in recognising one's own heartbeat and the amplitude of HEPs. Overall, our results imply that active conditions have an important role to play in future investigation of interoception.

Cortical monitoring of cardiac activity during rapid eye movement sleep: the heartbeat evoked potential in phasic and tonic rapid-eye-movement microstates

Sleep is a fundamental physiological state that facilitates neural recovery during periods of attenuated sensory processing. On the other hand, mammalian sleep is also characterized by the interplay between periods of increased sleep depth and environmental alertness. Whereas the heterogeneity of microstates during non-rapid-eye-movement (NREM) sleep was extensively studied in the last decades, transient microstates during rapid-eye-movement (REM) sleep received less attention. REM sleep features two distinct microstates: phasic and tonic. Previous studies indicate that sensory processing is largely diminished during phasic REM periods, whereas environmental alertness is partially reinstated when the brain switches into tonic REM sleep. Here, we investigated interoceptive processing as quantified by the heartbeat evoked potential (HEP) during REM microstates. We contrasted the HEPs of phasic and tonic REM periods using two separate databases that included the nighttime polysomnographic recordings of healthy young individuals (N = 20 and N = 19). We find a differential HEP modulation of a late HEP component (after 500 ms post-R-peak) between tonic and phasic REM. Moreover, the late tonic HEP component resembled the HEP found in resting wakefulness. Our results indicate that interoception with respect to cardiac signals is not uniform across REM microstates, and suggest that interoceptive processing is partially reinstated during tonic REM periods. The analyses of the HEP during REM sleep may shed new light on the organization and putative function of REM microstates.

The heartbeat evoked potential does not support strong interoceptive sensibility in trait mindfulness

The enhancement of body awareness is proposed as one of the cognitive mechanisms that characterize mindfulness. To date, this hypothesis is supported by self-report and behavioral measures but still lacks physiological evidence. The current study investigated relation between trait mindfulness (i.e., individual differences in the ability to be mindful in daily life) and body awareness in combining a self-report measure (Multidimensional Assessment of Interoceptive Awareness [MAIA] questionnaire) with analysis of the heartbeat evoked potential (HEP), which is an event-related potential reflecting the cortical processing of the heartbeat. The HEP data were collected from 17 healthy participants under five minutes of resting-state condition. In addition, each participant completed the Freiburg Mindfulness Inventory and the MAIA questionnaire. Taking account of the important variability of HEP effects, analyses were replicated with the same participants three times (in three distinct sessions). First, group-level analyses showed that HEP amplitude and trait mindfulness do not correlate. Secondly, we observed that HEP amplitude could positively correlate with self-reported body awareness; however, this association was unreliable over time. Interestingly, we found that HEP measure shows very poor reliability over time at the individual level, potentially explaining the lack of reliable association between HEP and psychological traits. Lastly, a reliable positive correlation was found between self-reported trait mindfulness and body awareness. Taken together, these findings provide preliminary evidence that the HEP might not support the increased subjective body awareness in trait mindfulness, thus suggesting that perhaps objective and subjective measures of body awareness could be independent.

On the estimate of music appraisal from surface EEG: a dynamic-network approach based on cross-sensor PAC measurements

Objective.The aesthetic evaluation of music is strongly dependent on the listener and reflects manifold brain processes that go well beyond the perception of incident sound. Being a high-level cognitive reaction, it is difficult to predict merely from the acoustic features of the audio signal and this poses serious challenges to contemporary music recommendation systems. We attempted to decode music appraisal from brain activity, recorded via wearable EEG, during music listening.Approach.To comply with the dynamic nature of music stimuli, cross-frequency coupling measurements were employed in a time-evolving manner to capture the evolving interactions between distinct brain-rhythms during music listening. Brain response to music was first represented as a continuous flow of functional couplings referring to both regional and inter-regional brain dynamics and then modelled as an ensemble of time-varying (sub)networks. Dynamic graph centrality measures were derived, next, as the final feature-engineering step and, lastly, a support-vector machine was trained to decode the subjective music appraisal. A carefully designed experimental paradigm provided the labeled brain signals.Main results.Using data from 20 subjects, dynamic programming to tailor the decoder to each subject individually and cross-validation, we demonstrated highly satisfactory performance (MAE= 0.948,R²= 0.63) that can be attributed, mostly, to interactions of left frontal gamma rhythm. In addition, our music-appraisal decoder was also employed in a part of the DEAP dataset with similar success. Finally, even a generic version of the decoder (common for all subjects) was found to perform sufficiently.Significance.A novel brain signal decoding scheme was introduced and validated empirically on suitable experimental data. It requires simple operations and leaves room for real-time implementation. Both the code and the experimental data are publicly available.

The breathing brain: The potential of neural oscillations for the understanding of respiratory perception in health and disease

Dyspnea or breathlessness is a symptom occurring in multiple acute and chronic illnesses, however, the understanding of the neural mechanisms underlying its subjective experience is limited. In this topical review, we propose neural oscillatory dynamics and cross-frequency coupling as viable candidates for a neural mechanism underlying respiratory perception, and a technique warranting more attention in respiration research. With the evidence for the potential of neural oscillations in the study of normal and disordered breathing coming from disparate research fields with a limited history of interdisciplinary collaboration, the main objective of the review was to converge the existing research and suggest future directions. The existing findings show that distinct limbic and cortical activations, as measured by hemodynamic responses, underlie dyspnea, however, the time-scale of these activations is not well understood. The recent findings of oscillatory neural activity coupled with the respiratory rhythm could provide the solution to this problem, however, more research with a focus on dyspnea is needed. We also touch on the findings of distinct spectral patterns underlying the changes in breathing due to experimental manipulations, meditation and disease. Subsequently, we suggest general research directions and specific research designs to supplement the current knowledge using neural oscillation techniques. We argue for the benefits of interdisciplinary collaboration and the converging of neuroimaging and behavioral methods to best explain the emergence of the subjective and aversive individual experience of dyspnea.

Psychological and Physiological Signatures of Music Listening in Different Listening Environments-An Exploratory Study

We compared music emotion ratings and their physiological correlates when the participants listened to music at home and in the laboratory. We hypothesized that music emotions are stronger in a familiar environment, that is, at home. Participants listened to their self-selected favorite and neutral music excerpts at home and in the laboratory for 10 min in each environment. They completed the questionnaires about their emotional states and gave saliva samples for the analyses of the stress hormone cortisol. We found that in the context of music listening, the participants’ emotion ratings differed between home and the laboratory. Furthermore, the cortisol levels were generally lower at home than in the laboratory and decreased after music listening at home and in the laboratory. However, the modulatory effects of music listening on cortisol levels did not differ between the home and the laboratory. Our exploratory multimethodological data offer novel insight about the psychological and physiological consequences of music listening. These data reveal the sensitivity of the current research methods to investigate human emotions in various contexts without excluding the use of laboratory environment in investigating them.

Systematic review and meta-analysis of the relationship between the heartbeat-evoked potential and interoception

The Heartbeat Evoked Potential (HEP) has been proposed as a neurophysiological marker of interoceptive processing. Despite its use to validate interoceptive measures and to assess interoceptive functioning in clinical groups, the empirical evidence for a relationship between HEP amplitude and interoceptive processing, including measures of such processing, is scattered across several studies with varied designs. The aim of this systematic review and meta-analysis was to examine the body of HEP-interoception research, and consider the associations the HEP shows with various direct and indirect measures of interoception, and how it is affected by manipulations of interoceptive processing. Specifically, we assessed the effect on HEP amplitude of manipulating attention to the heartbeat; manipulating participants' arousal; the association between the HEP and behavioural measures of cardiac interoception; and comparisons between healthy and clinical groups. Following database searches and screening, 45 studies were included in the systematic review and 42 in the meta-analyses. We noted variations in the ways individual studies have attempted to address key confounds, particularly the cardiac field artefact. Meta-analytic summaries indicated there were moderate to large effects of attention, arousal, and clinical status on the HEP, and a moderate association between HEP amplitude and behavioural measures of interoception. Problematically, the reliability of the meta-analytic effects documented here remain unknown, given the lack of standardised protocols for measuring the HEP. Thus, it is possible effects are driven by confounds such as cardiac factors or somatosensory effects.

A New Technique to Measure the Level of Interest Using Heartbeat-Evoked Brain Potential

Abstract. Interest is a positive emotion related to attention. The event-related brain potential (ERP) probe technique is a useful method to evaluate the level of interest in dynamic stimuli. However, even in the irrelevant probe technique, the probe is presented as a physical stimulus and steals the observer’s attentional resources, although no overt response is required. Therefore, the probe might become a problematic distractor, preventing deep immersion of participants. Heartbeat-evoked brain potential (HEP) is a brain activity, time-locked to a cardiac event. No probe is required to obtain HEP data. Thus, we aimed to investigate whether the HEP can be used to evaluate the level of interest. Twenty-four participants (12 males and 12 females) watched attractive and unattractive individuals of the opposite sex in interesting and uninteresting videos (7 min each), respectively. We performed two techniques each for both the interesting and the uninteresting videos: the ERP probe and the HEP techniques. In the former, somatosensory stimuli were presented as task-irrelevant probes while participants watched videos: frequent (80%) and infrequent (20%) stimuli were presented at each wrist in random order. In the latter, participants watched videos without the probe. The P2 amplitude in response to the somatosensory probe was smaller and the positive wave amplitudes of HEP were larger while watching the videos of attractive individuals than while watching the videos of unattractive ones. These results indicate that the HEP technique is a useful method to evaluate the level of interest without an external probe stimulus.