When the Heart Meets the Mind: Exploring the Brain-Heart Interaction during Time Perception.

Recent studies suggest that time estimation relies on bodily rhythms and interoceptive signals. We provide the first direct electrophysiological evidence suggesting an association between the brain's processing of heartbeat and duration judgment. We examined heartbeat-evoked potential (HEP) and contingent negative variation (CNV) during an auditory duration-reproduction task and a control reaction-time task spanning 4, 8, and 12 s intervals, in both male and female participants. Interoceptive awareness was assessed with the Self-Awareness Questionnaire (SAQ) and interoceptive accuracy through the heartbeat-counting task (HCT). Results revealed that SAQ scores, but not the HCT, correlated with mean reproduced durations with higher SAQ scores associating with longer and more accurate duration reproductions. Notably, the HEP amplitude changes during the encoding phase of the timing task, particularly within 130-270 ms (HEP1) and 470-520 ms (HEP2) after the R-peak, demonstrated interval-specific modulations that did not emerge in the control task. A significant ramp-like increase in HEP2 amplitudes occurred during the duration-encoding phase of the timing but not during the control task. This increase within the reproduction phase of the timing task correlated significantly with the reproduced durations for the 8 s and the 4 s intervals. The larger the increase in HEP2, the greater the under-reproduction of the estimated duration. CNV components during the encoding phase of the timing task were more negative than those in the reaction-time task, suggesting greater executive resources orientation toward time. We conclude that interoceptive awareness (SAQ) and cortical responses to heartbeats (HEP) predict duration reproductions, emphasizing the embodied nature of time.

Blind individuals' enhanced ability to sense their own heartbeat is related to the thickness of their occipital cortex.

Blindness is associated with heightened sensory abilities, such as improved hearing and tactile acuity. Moreover, recent evidence suggests that blind individuals are better than sighted individuals at perceiving their own heartbeat, suggesting enhanced interoceptive accuracy. Structural changes in the occipital cortex have been hypothesized as the basis of these behavioral enhancements. Indeed, several studies have shown that congenitally blind individuals have increased cortical thickness within occipital areas compared to sighted individuals, but how these structural differences relate to behavioral enhancements is unclear. This study investigated the relationship between cardiac interoceptive accuracy and cortical thickness in 23 congenitally blind individuals and 23 matched sighted controls. Our results show a significant positive correlation between performance in a heartbeat counting task and cortical thickness only in the blind group, indicating a connection between structural changes in occipital areas and blind individuals' enhanced ability to perceive heartbeats.

Rhesus monkeys have an interoceptive sense of their beating hearts.

The sensation of internal bodily signals, such as when your stomach is contracting or your heart is beating, plays a critical role in broad biological and psychological functions ranging from homeostasis to emotional experience and self-awareness. The evolutionary origins of this capacity and, thus, the extent to which it is present in nonhuman animals remain unclear. Here, we show that rhesus monkeys (Macaca mulatta) spend significantly more time viewing stimuli presented asynchronously, as compared to synchronously, with their heartbeats. This is consistent with evidence previously shown in human infants using a nearly identical experimental paradigm, suggesting that rhesus monkeys have a human-like capacity to integrate interoceptive signals from the heart with exteroceptive audiovisual information. As no prior work has demonstrated behavioral evidence of innate cardiac interoceptive ability in nonhuman animals, these results have important implications for our understanding of the evolution of this ability and for establishing rhesus monkeys as an animal model for human interoceptive function and dysfunction. We anticipate that this work may also provide an important model for future psychiatric research, as disordered interoceptive processing is implicated in a wide variety of psychiatric conditions.

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.

Listen to your heart: Trade-off between cardiac interoceptive processing and visual exteroceptive processing.

Internal bodily signals, such as heartbeats, can influence conscious perception of external sensory information. Spontaneous shifts of attention between interoception and exteroception have been proposed as the underlying mechanism, but direct evidence is lacking. Here, we used steady-state visual evoked potential (SSVEP) frequency tagging to independently measure the neural processing of visual stimuli that were concurrently presented but varied in heartbeat coupling in healthy participants. Although heartbeat coupling was irrelevant to participants' task of detecting brief color changes, we found decreased SSVEPs for systole-coupled stimuli and increased SSVEPs for diastole-coupled stimuli, compared to non-coupled stimuli. These results suggest that attentional and representational resources allocated to visual stimuli vary according to fluctuations in cardiac-related signals across the cardiac cycle, reflecting spontaneous and immediate competition between cardiac-related signals and visual events. Furthermore, frequent coupling of visual stimuli with stronger cardiac-related signals not only led to a larger heartbeat evoked potential (HEP) but also resulted in a smaller color change evoked N2 component, with the increase in HEP amplitude associated with a decrease in N2 amplitude. These findings indicate an overall or longer-term increase in brain resources allocated to the internal domain at the expense of reduced resources available for the external domain. Our study highlights the dynamic reallocation of limited processing resources across the internal-external axis and supports the trade-off between interoception and exteroception.

Cardiorespiratory rhythm-contingent trace eyeblink conditioning in elderly adults.

Learning outcome is modified by the degree to which the subject responds and pays attention to specific stimuli. Our recent research suggests that presenting stimuli in contingency with a specific phase of the cardiorespiratory rhythm might expedite learning. Specifically, expiration-diastole (EXP-DIA) is beneficial for learning trace eyeblink conditioning (TEBC) compared with inspiration-systole (INS-SYS) in healthy young adults. The aim of this study was to investigate whether the same holds true in healthy elderly adults (n = 50, aged >70 yr). Participants were instructed to watch a silent nature film while TEBC trials were presented at either INS-SYS or EXP-DIA (separate groups). Learned responses were determined as eyeblinks occurring after the tone conditioned stimulus (CS), immediately preceding the air puff unconditioned stimulus (US). Participants were classified as learners if they made at least five conditioned responses (CRs). Brain responses to the stimuli were measured by electroencephalogram (EEG). Memory for the film and awareness of the CS-US contingency were evaluated with a questionnaire. As a result, participants showed robust brain responses to the CS, acquired CRs, and reported awareness of the CS-US relationship to a variable degree. There was no difference between the INS-SYS and EXP-DIA groups in any of the above. However, when only participants who learned were considered, those trained at EXP-DIA (n = 11) made more CRs than those trained at INS-SYS (n = 13). Thus, learned performance could be facilitated in those elderly who learned. However, training at a specific phase of cardiorespiratory rhythm did not increase the proportion of participants who learned.NEW & NOTEWORTHY We trained healthy elderly individuals in trace eyeblink conditioning, either at inspiration-systole or at expiration-diastole. Those who learned exhibited more conditioned responses when trained at expiration-diastole rather than inspiration-systole. However, there was no difference between the experimental groups in the proportion of individuals who learned or did not learn.

Testing an artificial intelligence algorithm to predict fetal heartbeat of vitrified-warmed blastocysts from a single image: predictive ability in different settings.

STUDY QUESTION: Could an artificial intelligence (AI) algorithm predict fetal heartbeat from images of vitrified-warmed embryos? SUMMARY ANSWER: Applying AI to vitrified-warmed blastocysts may help predict which ones will result in implantation failure early enough to thaw another. WHAT IS KNOWN ALREADY: The application of AI in the field of embryology has already proven effective in assessing the quality of fresh embryos. Therefore, it could also be useful to predict the outcome of frozen embryo transfers, some of which do not recover their pre-vitrification volume, collapse, or degenerate after warming without prior evidence. STUDY DESIGN, SIZE, DURATION: This retrospective cohort study included 1109 embryos from 792 patients. Of these, 568 were vitrified blastocysts cultured in time-lapse systems in the period between warming and transfer, from February 2022 to July 2023. The other 541 were fresh-transferred blastocysts serving as controls. PARTICIPANTS/MATERIALS, SETTING, METHODS: Four types of time-lapse images were collected: last frame of development of 541 fresh-transferred blastocysts (FTi), last frame of 467 blastocysts to be vitrified (PVi), first frame post-warming of 568 vitrified embryos (PW1i), and last frame post-warming of 568 vitrified embryos (PW2i). After providing the images to the AI algorithm, the returned scores were compared with the conventional morphology and fetal heartbeat outcomes of the transferred embryos (n = 1098). The contribution of the AI score to fetal heartbeat was analyzed by multivariate logistic regression in different patient populations, and the predictive ability of the models was measured by calculating the area under the receiver-operating characteristic curve (ROC-AUC). MAIN RESULTS AND THE ROLE OF CHANCE: Fetal heartbeat rate was related to AI score from FTi (P < 0.001), PW1i (P < 0.05), and PW2i (P < 0.001) images. The contribution of AI score to fetal heartbeat was significant in the oocyte donation program for PW2i (odds ratio (OR)=1.13; 95% CI [1.04-1.23]; P < 0.01), and in cycles with autologous oocytes for PW1i (OR = 1.18; 95% CI [1.01-1.38]; P < 0.05) and PW2i (OR = 1.15; 95% CI [1.02-1.30]; P < 0.05), but was not significantly associated with fetal heartbeat in genetically analyzed embryos. AI scores from the four groups of images varied according to morphological category (P < 0.001). The PW2i score differed in collapsed, non-re-expanded, or non-viable embryos compared to normal/viable embryos (P < 0.001). The predictability of the AI score was optimal at a post-warming incubation time of 3.3-4 h (AUC = 0.673). LIMITATIONS, REASONS FOR CAUTION: The algorithm was designed to assess fresh embryos prior to vitrification, but not thawed ones, so this study should be considered an external trial. WIDER IMPLICATIONS OF THE FINDINGS: The application of predictive software in the management of frozen embryo transfers may be a useful tool for embryologists, reducing the cancellation rates of cycles in which the blastocyst does not recover from vitrification. Specifically, the algorithm tested in this research could be used to evaluate thawed embryos both in clinics with time-lapse systems and in those with conventional incubators only, as just a single photo is required. STUDY FUNDING/COMPETING INTERESTS: This study was supported by the Regional Ministry of Innovation, Universities, Science and Digital Society of the Valencian Community (CIACIF/2021/019) and by Instituto de Salud Carlos III (PI21/00283), and co-funded by European Union (ERDF, 'A way to make Europe'). M.M. received personal fees in the last 5 years as honoraria for lectures from Merck, Vitrolife, MSD, Ferring, AIVF, Theramex, Gedeon Richter, Genea Biomedx, and Life Whisperer. There are no other competing interests. TRIAL REGISTRATION NUMBER: N/A.

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 Contractile Machines of the Heart.

This chapter will describe basic structural and functional features of the contractile apparatus of muscle cells of the heart, namely, cardiomyocytes and smooth muscle cells. Cardiomyocytes form the contractile myocardium of the heart, while smooth muscle cells form the contractile coronary vessels. Both muscle types have distinct properties and will be considered with respect to their cellular appearance (brick-like cross-striated versus spindle-like smooth), arrangement of contractile proteins (sarcomeric versus non-sarcomeric organization), calcium activation mechanisms (thin-filament versus thick-filament regulation), contractile features (fast and phasic versus slow and tonic), energy metabolism (high oxygen versus low oxygen demand), molecular motors (type II myosin isoenzymes with high adenosine diphosphate [ADP]-release rate versus myosin isoenzymes with low ADP-release rates), chemomechanical energy conversion (high adenosine triphosphate [ATP] consumption and short duty ratio versus low ATP consumption and high duty ratio of myosin II cross-bridges [XBs]), and excitation-contraction coupling (calcium-induced calcium release versus pharmacomechanical coupling). Part of the work has been published (Neuroscience - From Molecules to Behavior", Chap. 22, Galizia and Lledo eds 2013, Springer-Verlag; with kind permission from Springer Science + Business Media).

Cardiac organoids do not warrant additional moral scrutiny.

Certain organoid subtypes are particularly sensitive. We explore whether moral intuitions about the heartbeat warrant unique moral consideration for newly advanced contracting cardiac organoids. Despite the heartbeat's moral significance in organ procurement and abortion discussions, we argue that this significance should not translate into moral implications for cardiac organoids.

Feasibility and validity of using deep learning to reconstruct 12-lead ECG from three­lead signals.

BACKGROUND: In the field of mobile health, portable dynamic electrocardiogram (ECG) monitoring devices often have a limited number of lead electrodes due to considerations, such as portability and battery life. This situation leads to a contradiction between the demand for standard 12­lead ECG information and the limited number of leads collected by portable devices. METHODS: This study introduces a composite ECG vector reconstruction network architecture based on convolutional neural network (CNN) combined with recurrent neural network by using leads I, II, and V2. This network is designed to reconstruct three­lead ECG signals into 12­lead ECG signals. A 1D CNN abstracts and extracts features from the spatial domain of the ECG signals, and a bidirectional long short-term memory network analyzes the temporal trends in the signals. Then, the ECG signals are inputted into the model in a multilead, single-channel manner. RESULTS: Under inter-patient conditions, the mean reconstructed Root mean squared error (RMSE) for precordial leads V1, V3, V4, V5, and V6 were 28.7, 17.3, 24.2, 36.5, and 25.5 µV, respectively. The mean overall RMSE and reconstructed Correlation coefficient (CC) were 26.44 µV and 0.9562, respectively. CONCLUSION: This paper presents a solution and innovative approach for recovering 12­lead ECG information when only three­lead information is available. After supplementing with comprehensive leads, we can analyze the cardiac health status more comprehensively across 12 dimensions.

Enhancing Interoceptive Abilities and Emotional Processing: Effects of HD-tDCS.

BACKGROUND: Interoception, the processing and integration of bodily signals, is crucial for emotional experiences and overall well-being. The interoceptive network, including the somatosensory cortices, has been recognized for its role in interoceptive and emotional processing. High-definition transcranial, direct-current stimulation (HD-tDCS) has been demonstrated to modulate brain activity in the primary somatosensory cortex (S1). Based on those findings, we hypothesized that anodal HD-tDCS over the right S1 would enhance interoceptive abilities and heighten emotional perception. METHODS: Thirty-six healthy adults participated in two sessions separated by at least one week. A 20-min HD-tDCS stimulation (2 mA), and a sham stimulation, were applied in randomized order. Both conditions involved pre-tDCS physical activation by ergometer cycling. Interoceptive abilities were assessed before and after both sessions using a heartbeat-perception and respiratory-load task. Emotional perception was measured using four matched international affective picture system (IAPS) picture sets presented randomly. RESULTS: Active HD-tDCS did not significantly improve interoceptive accuracy, interoceptive emotion evaluation, or interoceptive sensibility. However, a notable increase in cardiac interoceptive awareness was observed after active HD-tDCS. The expected enhancement of emotional processing was not observed. CONCLUSIONS: This study represents the first attempt to modulate interoceptive and emotional processing using HD-tDCS over S1. Although consistent enhancement was not observed, our findings provide insights into the modulation of interoceptive and emotional processes with HD-tDCS, suggesting avenues for further research. Further studies should consider the nuanced effects of stimulation techniques and the complex interplay between interoception and emotion.

Impact of exposure to glyphosate-based herbicide on morphological and physiological parameters in embryonic and larval development of zebrafish.

Glyphosate-based herbicides (GBH) have been commonly used in agriculture to inhibit weed growth and increase yields. However, due to the high solubility of these herbicides in water, they can reach aquatic environments, by infiltration, erosion, and/or lixiviation, affecting non target organisms. Thus, this study aimed to characterize the toxicity of GBH Roundup WG® (RWG®) during the embryonic and larval development of Danio rerio. Embryos (3 hours post fertilization, hpf-until hatching) and larvae (3 days post fertilization, dpf to 6 dpf) were exposed to concentrations of 0.065 and 6.5 mg L-1 . They were evaluated for survival, hatching, spontaneous movements, heartbeat, morphology, and morphometry by in vivo photographs in microscope, cell proliferation and apoptosis by immunohistochemistry, and exploratory behavior and phototropism by video recording. Our results showed an increase in embryo and larvae mortality in those exposed to 0.065 mg L-1 , as well as a reduction in spontaneous embryo movements. The larval heartbeats showed a decrease at 4 dpf in the group exposed to 0.065 mg L-1 and an increase at 5 and 6 dpf in both exposed groups. Cell proliferation was reduced in both groups exposed in embryos and only in the 0.065 mg L-1 group in larvae, while cell death increased in embryos exposed to 6.5 mg L-1 . These results demonstrated the toxic effect of low concentrations of the herbicide RWG® during embryonic and larval development of non target organisms, as well as the importance of constantly reviewing acceptable limits for exposure in natural environments.

Chest Wall Motion Model of Cardiac Activity for Radar-Based Vital-Sign-Detection System.

An increasing number of studies on non-contact vital sign detection using radar are now beginning to turn to data-driven neural network approaches rather than traditional signal-processing methods. However, there are few radar datasets available for deep learning due to the difficulty of acquiring and labeling the data, which require specialized equipment and physician collaboration. This paper presents a new model of heartbeat-induced chest wall motion (CWM) with the goal of generating a large amount of simulation data to support deep learning methods. An in-depth analysis of published CWM data collected by the VICON Infrared (IR) motion capture system and continuous wave (CW) radar system during respiratory hold was used to summarize the motion characteristics of each stage within a cardiac cycle. In combination with the physiological properties of the heartbeat, appropriate mathematical functions were selected to describe these movement properties. The model produced simulation data that closely matched the measured data as evaluated by dynamic time warping (DTW) and the root-mean-squared error (RMSE). By adjusting the model parameters, the heartbeat signals of different individuals were simulated. This will accelerate the application of data-driven deep learning methods in radar-based non-contact vital sign detection research and further advance the field.

Comparison of Machine Learning Algorithms for Heartbeat Detection Based on Accelerometric Signals Produced by a Smart Bed.

This work aims to compare the performance of Machine Learning (ML) and Deep Learning (DL) algorithms in detecting users' heartbeats on a smart bed. Targeting non-intrusive, continuous heart monitoring during sleep time, the smart bed is equipped with a 3D solid-state accelerometer. Acceleration signals are processed through an STM 32-bit microcontroller board and transmitted to a PC for recording. A photoplethysmographic sensor is simultaneously checked for ground truth reference. A dataset has been built, by acquiring measures in a real-world set-up: 10 participants were involved, resulting in 120 min of acceleration traces which were utilized to train and evaluate various Artificial Intelligence (AI) algorithms. The experimental analysis utilizes K-fold cross-validation to ensure robust model testing across different subsets of the dataset. Various ML and DL algorithms are compared, each being trained and tested using the collected data. The Random Forest algorithm exhibited the highest accuracy among all compared models. While it requires longer training time compared to some ML models such as Naïve Bayes, Linear Discrimination Analysis, and K-Nearest Neighbour Classification, it keeps substantially faster than Support Vector Machine and Deep Learning models. The Random Forest model demonstrated robust performance metrics, including recall, precision, F1-scores, macro average, weighted average, and overall accuracy well above 90%. The study highlights the better performance of the Random Forest algorithm for the specific use case, achieving superior accuracy and performance metrics in detecting user heartbeats in comparison to other ML and DL models tested. The drawback of longer training times is not too relevant in the long-term monitoring target scenario, so the Random Forest model stands out as a viable solution for real-time ballistocardiographic heartbeat detection, showcasing potential for healthcare and wellness monitoring applications.

Cardiac interoception in Anorexia Nervosa: A resting-state heartbeat-evoked potential study.

OBJECTIVE: A deficit in interoception - the ability to perceive, interpret and integrate afferent signals about the physiological state of the body - has been shown in Anorexia Nervosa (AN), and linked to altered hunger sensations, body dysmorphia, and abnormal emotional awareness. The present high-density electroencephalography (hdEEG) study aims to assess cardiac interoception in AN and to investigate its neural correlates, using an objective neurophysiological measure. METHOD: Heartbeat-evoked potentials (HEPs) were computed from 5 min of resting-state EEG and electrocardiogram (ECG) data and compared between individuals with AN (N = 22) and healthy controls (HC) (N = 19) with waveform, topographic, and source imaging analyses. RESULTS: Differences in the cortical representation of heartbeats were present between AN and HC at a time window of 332-348 ms after the ECG R-peak. Source imaging analyses revealed a right-sided hypoactivation in AN of brain regions linked to interoceptive processing, such as the anterior cingulate and orbitofrontal areas. CONCLUSIONS: To the best of our knowledge, this is the first study using hdEEG to localise the underlying sources of HEPs in AN. Results point to altered interoceptive processing during resting-state in AN. As our participants had a short duration of illness, this might not be the consequence of prolonged starvation. Interventions targeted at interoception could provide an additional tool to facilitate recovery.

Whose emotion is it? Perspective matters to understand brain-body interactions in emotions.

Feeling happy, or judging whether someone else is feeling happy are two distinct facets of emotions that nevertheless rely on similar physiological and neural activity. Differentiating between these two states, also called Self/Other distinction, is an essential aspect of empathy, but how exactly is it implemented? In non-emotional cognition, the transient neural response evoked at each heartbeat, or heartbeat evoked response (HER), indexes the self and signals Self/Other distinction. Here, using electroencephalography (n = 32), we probe whether HERs' role in Self/Other distinction extends also to emotion - a domain where brain-body interactions are particularly relevant. We asked participants to rate independently validated affective scenes, reporting either their own emotion (Self) or the emotion expressed by people in the scene (Other). During the visual cue indicating to adopt the Self or Other perspective, before the affective scene, HERs distinguished between the two conditions, in visual cortices as well as in the right frontal operculum. Physiological reactivity (facial electromyogram, skin conductance, heart rate) during affective scene co-varied as expected with valence and arousal ratings, but also with the Self- or Other- perspective adopted. Finally, HERs contributed to the subjective experience of valence in the Self condition, in addition to and independently from physiological reactivity. We thus show that HERs represent a trans-domain marker of Self/Other distinction, here specifically contributing to experienced valence. We propose that HERs represent a form of evidence related to the 'I' part of the judgement 'To which extent do I feel happy'. The 'I' related evidence would be combined with the affective evidence collected during affective scene presentation, accounting at least partly for the difference between feeling an emotion and identifying it in someone else.

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.

CA3-CA1 long-term potentiation occurs regardless of respiration and cardiac cycle phases in urethane-anesthetized rats.

Breathing and heartbeat synchronize to each other and to brain function and affect cognition in humans. However, it is not clear how cardiorespiratory rhythms modulate such basic processes as synaptic plasticity thought to underlie learning. Thus, we studied if respiration and cardiac cycle phases at burst stimulation onset affect hippocampal long-term potentiation (LTP) in the CA3-CA1 synapse in urethane-anesthetized adult male Sprague-Dawley rats. In a between-subjects design, we timed burst stimulation of the ventral hippocampal commissure (vHC) to systole or diastole either during expiration or inspiration and recorded responses throughout the hippocampus with a linear probe. As classical conditioning in humans seems to be most efficient at expiration-diastole, we also expected LTP to be most efficient if burst stimulation was targeted to expiration-diastole. However, LTP was induced equally in all four groups and respiration and cardiac cycle phase did not modulate CA1 responses to vHC stimulation overall. This could be perhaps because we bypassed all natural routes of external influences on the CA1 by directly stimulating the vHC. In the future, the effect of cardiorespiratory rhythms on synaptic plasticity could also be studied in awake state and in other parts of the hippocampal tri-synaptic loop.

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.