Respiration and heartbeat continuously interact within the living organism at many different levels, representing two of the main oscillatory rhythms of the body and providing major sources of interoceptive information to the brain. Despite the modulatory effect of respiration on exteroception and cognition has been recently established in humans, its role in shaping interoceptive perception has been scarcely investigated so far. In two independent studies, we investigated the effect of spontaneous breathing on cardiac interoception by assessing the Heartbeat Evoked Potential (HEP) in healthy humans. In Study 1, we compared HEP activity for heartbeats occurred during inhalation and exhalation in 40 volunteers at rest. We found higher HEP amplitude during exhalation, compared to inhalation, over fronto-centro-parietal areas. This suggests increased brain-heart interactions and improved cortical processing of the heartbeats during exhalation. Further analyses revealed that this effect was moderated by heart rate changes. In Study 2, we tested the respiratory phase-dependent modulation of HEP activity in 20 volunteers during Exteroceptive and Interoceptive conditions of the Heartbeat Detection (HBD) task. In these conditions, participants were requested to tap at each heartbeat, either listened to or felt, respectively. Results showed higher HEP activity and higher detection accuracy at exhalation than inhalation in the Interoceptive condition only. Direct comparisons of Interoceptive and Exteroceptive conditions confirmed stronger respiratory phase-dependent modulation of HEP and accuracy when attention was directed towards the interoceptive stimuli. Moreover, HEP changes during the Interoceptive condition were independent of heart physiology, but were positively correlated with higher detection accuracy at exhalation than inhalation. This suggests a link between optimization of cortical processing of cardiac signals and detection of heartbeats across the respiratory cycle. Overall, we provide data showing that respiration shapes cardiac interoception at the neurophysiological and behavioural levels. Specifically, exhalation may allow attentional shift towards the internal bodily states.

Respiration and cardiac activity intricately interact through complex physiological mechanisms. The heartbeat-evoked potential (HEP) is an EEG fluctuation reflecting the cortical processing of cardiac signals. We recently found higher HEP amplitude during exhalation than inhalation during a task involving attention to cardiac sensations. This may have been due to reduced cardiac perception during inhalation and heightened perception during exhalation through attentional mechanisms. To investigate relationships between HEP, attention, and respiration, we introduced an experimental setup that included tasks related to cardiac and respiratory interoceptive and exteroceptive attention. Results revealed HEP amplitude increases during the interoceptive tasks over fronto-central electrodes. When respiratory phases were taken into account, HEP increases were primarily driven by heartbeats recorded during exhalation, specifically during the cardiac interoceptive task, while inhalation had minimal impact. These findings emphasize the role of respiration in cardiac interoceptive attention and could have implications for respiratory interventions to fine-tune cardiac interoception.

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.

Nidrâ yoga is an ancient yogic practice capable of inducing altered states of consciousness characterized by deep relaxation, strong concentration, acute self-awareness, and joy. In modern contemplative neuroscience language, it is known by the name yoga nidra, and few studies have investigated its phenomenological and psychophysiological effects. Six healthy volunteers (four females aged 31–74) performed 12 yoga nidra sessions guided by an expert during a 6-day retreat. Each session consisted of 10 minutes in a resting state (baseline) followed by 2 hours of yoga nidra. Psychometric data regarding dissociative experiences (Clinician Administered Dissociative States Scale) and the state of consciousness (Phenomenology of Consciousness Inventory) were collected after baseline and yoga nidra, while high-density EEG was recorded during the entire session. During nidra sessions, no sleep hallmarks (i.e., K-complexes and sleep spindles) were detected by the EEG in any subject. Psychometric data we re analyzed using a Wilcoxon signed-rank test corrected with the false discovery rate approach for multiple comparisons. Compared to baseline, yoga nidra practice was related to: (1) increased dissociative effects (p = 0.022); (2) perception of being in an altered state of consciousness (p = 0.026); (3) alterations in perceived body image (p = 0.022); (4) increased “meaningfulness” attributed to the experience (p = 0.026); (5) reduced rational thinking (p = 0.029); and (6) reduced volitional thought control (p = 0.026). First-person experience is discussed in relation to descriptive EEG power spectral density analysis, which was performed in one subject because of severe EEG artifacts in the other recordings; that subject showed, compared to baseline: (1) early increase of alpha and beta power, followed by a progressive widespread reduction; (2) widespread early increase of theta power, followed by a progressive reduction; and (3) widespread increase of gamma power in the latest stages. The present preliminary results enrich the knowledge of yoga nidra, elucidating its phenomenology and suggesting some psychophysiological correlates that future studies may address.

Sleep and plasticity are highly interrelated, as sleep slow oscillations and sleep spindles are associated with consolidation of Hebbian-based processes. However, in adult humans, visual cortical plasticity is mainly sustained by homeostatic mechanisms, for which the role of sleep is still largely unknown. Here, we demonstrate that non-REM sleep stabilizes homeostatic plasticity of ocular dominance induced in adult humans by short-term monocular deprivation: the counterintuitive and otherwise transient boost of the deprived eye was preserved at the morning awakening (>6 hr after deprivation). Subjects exhibiting a stronger boost of the deprived eye after sleep had increased sleep spindle density in frontopolar electrodes, suggesting the involvement of distributed processes. Crucially, the individual susceptibility to visual homeostatic plasticity soon after deprivation correlated with the changes in sleep slow oscillations and spindle power in occipital sites, consistent with a modulation in early occipital visual cortex.

The cardiovascular and respiratory systems are anatomically and functionally integrated, suggesting that breathing continuously influences cardiac interoception. Previously, we demonstrated that the heartbeat-evoked potential (HEP), a neural marker of cardiac signal processing, is modulated by respiration, with enhanced late HEP positivity and increased interoceptive accuracy during exhalation. Here, we reanalysed our previous dataset in the time-frequency domain to investigate heartbeat-modulated cortical oscillations across respiratory phases during rest, cardiac interoception (heartbeat counting), and an exteroceptive control task. During heartbeat counting, exhalation was associated with increased late heartbeat-modulated alpha- and theta-band power and inter-trial coherence over fronto-parietal electrodes, compared with inhalation. Heartbeat-modulated alpha activity was related to HEP amplitude and predicted interoceptive accuracy. Exploratory analyses also indicated enhanced heartbeat-modulated functional connectivity during exhalation. These effects could not be accounted for by cardiac physiology alone and were absent during exteroception. We propose a mechanistic account of cardio-respiratory interactions grounded in interoceptive predictive coding, suggesting that exhalation enhances precision-weighting of cardiac signals by facilitating attentional allocation to interoceptive signals and suppressing task-irrelevant distractions.