Spontaneous fluctuations of ongoing neural activity substantially affect sensory and cognitive performance. Because bodily signals are constantly relayed up to the neocortex, neural responses to bodily signals are likely to shape ongoing activity. Here, using magnetoencephalography, we show that in humans, neural events locked to heartbeats before stimulus onset predict the detection of a faint visual grating in the posterior right inferior parietal lobule and the ventral anterior cingulate cortex, two regions that have multiple functional correlates and that belong to the same resting-state network. Neither fluctuations in measured bodily parameters nor overall cortical excitability could account for this finding. Neural events locked to heartbeats therefore shape visual conscious experience, potentially by contributing to the neural maps of the organism that might underlie subjectivity. Beyond conscious vision, our results show that neural events locked to a basic physiological input such as heartbeats underlie behaviorally relevant differential activation in multifunctional cortical areas.
At a glance
- Dynamics of ongoing activity: explanation of the large variability in evoked cortical responses. Science 273, 1868–1871 (1996). , , &
- Default-mode activity during a passive sensory task: uncoupled from deactivation but impacting activation. J. Cogn. Neurosci. 16, 1484–1492 (2004). &
- An oscillatory hierarchy controlling neuronal excitability and stimulus processing in the auditory cortex. J. Neurophysiol. 94, 1904–1911 (2005). et al.
- Internal brain state regulates membrane potential synchrony in barrel cortex of behaving mice. Nature 454, 881–885 (2008). &
- State-dependent representation of amplitude-modulated noise stimuli in rat auditory cortex. J. Neurosci. 31, 6414–6420 (2011). &
- Spontaneous and task-evoked brain activity negatively interact. J. Neurosci. 33, 4672–4682 (2013).
- Prestimulus oscillations enhance psychophysical performance in humans. J. Neurosci. 24, 10186–10190 (2004). , , , &
- Baseline brain activity fluctuations predict somatosensory perception in humans. Proc. Natl. Acad. Sci. USA 104, 12187–12192 (2007). et al.
- Distributed and antagonistic contributions of ongoing activity fluctuations to auditory stimulus detection. J. Neurosci. 29, 13410–13417 (2009). , &
- Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws. Proc. Natl. Acad. Sci. USA 110, 3585–3590 (2013). et al.
- Beta- and gamma-band EEG power predicts illusory auditory continuity perception. J. Neurophysiol. 108, 2717–2724 (2012). , &
- Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat. Rev. Neurosci. 8, 700–711 (2007). &
- Emerging concepts for the dynamical organization of resting-state activity in the brain. Nat. Rev. Neurosci. 12, 43–56 (2011). , &
- Multisensory brain mechanisms of bodily self-consciousness. Nat. Rev. Neurosci. 13, 556–571 (2012).
- How do you feel? Interoception: the sense of the physiological condition of the body. Nat. Rev. Neurosci. 3, 655–666 (2002).
- Gut feelings: the emerging biology of gut-brain communication. Nat. Rev. Neurosci. 12, 453–466 (2011).
- Visceral influences on brain and behavior. Neuron 77, 624–638 (2013). &
- The nature of feelings: evolutionary and neurobiological origins. Nat. Rev. Neurosci. 14, 143–152 (2013). &
- Specifying the self for cognitive neuroscience. Trends Cogn. Sci. 15, 104–112 (2011). , , &
- Task-independent functional brain activity correlation with skin conductance changes: an fMRI study. Neuroimage 17, 1797–1806 (2002). , &
- Activity in ventromedial prefrontal cortex covaries with sympathetic skin conductance level: a physiological account of a “default mode” of brain function. Neuroimage 22, 243–251 (2004). , , , &
- Spontaneous brain activity relates to autonomic arousal. J. Neurosci. 32, 11176–11186 (2012). et al.
- Ventral medial prefrontal cortex and cardiovagal control in conscious humans. Neuroimage 35, 698–708 (2007). , , , &
- The relation of ventromedial prefrontal cortex activity and heart rate fluctuations at rest. Eur. J. Neurosci. 30, 2205–2210 (2009). , , &
- Event-related brain potentials and the processing of cardiac activity. Biol. Psychol. 42, 75–85 (1996). &
- A cortical potential reflecting cardiac function. Proc. Natl. Acad. Sci. USA 104, 6818–6823 (2007). et al.
- Heart cycle-related effects on event-related potentials, spectral power changes, and connectivity patterns in the human ECoG. Neuroimage 81, 178–190 (2013). , , &
- Heartbeat evoked potentials (HEP): topography and influence of cardiac awareness and focus of attention. Electroencephalogr. Clin. Neurophysiol. 88, 163–172 (1993). , &
- Association between interoception and empathy: evidence from heart-beat evoked brain potential. Int. J. Psychophysiol. 79, 259–265 (2011). , &
- Basic and Clinical Neurocardiology (Oxford University Press, Oxford, 2004). &
- Visceral circuits and cingulate-mediated autonomic functions. in Cingulate Neurobiology and Disease (ed. Vogt, B.A.) 220–235 (Oxford University Press, Oxford, 2009). &
- Studies of heart rate and other bodily processes in sensorimotor behavior. in Cardiovascular Psychophysiology (ed. Obrist, P.A., Black, A.H., Brener, J. & DiCara, L.) 538–564 (Aldine Press, Chicago, 1974). &
- Topography and morphology of heart action-related EEG potentials. Electroencephalogr. Clin. Neurophysiol. 108, 299–305 (1998). , , &
- Contributions of anterior cingulate cortex to behaviour. Brain 118, 279–306 (1995). , &
- The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. USA 102, 9673–9678 (2005). et al.
- Neural systems supporting interoceptive awareness. Nat. Neurosci. 7, 189–195 (2004). , , , &
- Lapses in alertness: coherence of fluctuations in performance and EEG spectrum. Electroencephalogr. Clin. Neurophysiol. 86, 23–35 (1993). &
- Intrinsic connectivity networks, alpha oscillations, and tonic alertness: a simultaneous electroencephalography/functional magnetic resonance imaging study. J. Neurosci. 30, 10243–10250 (2010). et al.
- The neural subjective frame: from bodily signals to perceptual consciousness. Phil. Trans. R. Soc. B (in the press). &
- Towards a neurobiological theory of consciousness. Semin. Neurosci. 2, 263–275 (1990). &
- Neural correlates of the first-person-perspective. Trends Cogn. Sci. 7, 38–42 (2003). &
- Effect of subjective perspective taking during simulation of action: a PET investigation of agency. Nat. Neurosci. 4, 546–550 (2001). &
- Movement intention after parietal cortex stimulation in humans. Science 324, 811–813 (2009). et al.
- Parietal cortex and representation of the mental Self. Proc. Natl. Acad. Sci. USA 101, 6827–6832 (2004). et al.
- Social comparison affects reward-related brain activity in the human ventral striatum. Science 318, 1305–1308 (2007). et al.
- The brain basis of emotion: a meta-analytic review. Behav. Brain Sci. 35, 121–143 (2012). , , , &
- How is our self related to midline regions and the default-mode network? Neuroimage 57, 1221–1233 (2011). &
- The neural correlates of subjective value during intertemporal choice. Nat. Neurosci. 10, 1625–1633 (2007). &
- Investigating the functional heterogeneity of the default mode network using coordinate-based meta-analytic modeling. J. Neurosci. 29, 14496–14505 (2009). et al.
- Functional-anatomic fractionation of the brain's default network. Neuron 65, 550–562 (2010). , , , &
- Detection Theory: a User's Guide (Lawrence Erlbaum Associates, 2005). &
- Brainstorm: a user-friendly application for MEG/EEG analysis. Comput. Intell. Neurosci. 2011, 879716 (2011). , , , &
- Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15, 273–289 (2002). et al.
- FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput. Intell. Neurosci. 2011, 156869 (2011). , , &
- Automatic detection of respiration rate from ambulatory single-lead ECG. IEEE Trans. Inf. Technol. Biomed. 13, 890–896 (2009). , , &
- The phase of ongoing EEG oscillations predicts visual perception. J. Neurosci. 29, 7869–7876 (2009). , &
- Nonparametric statistical testing of EEG- and MEG-data. J. Neurosci. Methods 164, 177–190 (2007). &
- Supplementary Figure 1: Mean interbeat interval variability. (73 KB)
Data are presented from the interbeat interval during which the warning signal appeared on the screen until interbeat intervals after response delivery. Interbeat interval variability decreased after stimulus onset (* p<0.05), but did not differ between hits and misses (Greenhouse-Geisser corrected 2-way ANOVA with factors Consciousness and Time, main effect of Time F2.0,32.0=11.7, p=2.10—4; main effect of Consciousness F1,16=0.9, p=0.36; interaction F2.39,38.24=2.0, p=0.13). Error bars represent s.e.m.
- Supplementary Figure 2: Neural responses to hearbeats in subjects with fast or slow heart rate. (75 KB)
Mean time course across the cluster in hits and misses, in subjects with (a) short (n=9, mean IBI 730 ms) or (b) long (n=8, mean IBI 886 ms) interbeat intervals (IBI). Neural responses to heartbeats within the cluster significantly differed between hits and misses in both groups (short IBI group, t8=3.76, p=0.006; long IBI group, t7=3.19, p=0.015). Longer IBIs did not delay the effect, indicating that the effect corresponds to a differential response to the preceding heartbeat rather than a preparation of the next heartbeat. Error bars represent s.e.m.
- Supplementary Figure 3: T-locked electrocardiogram, grand-average across subjects. (54 KB)
Top, vertical derivation. Bottom, horizontal derivation. We did not find any significant difference between hits and misses.
- Supplementary Figure 4: Influence of cardiac artefact correction using independent component analysis (ICA) on prestimulus heartbeat-evoked responses. (74 KB)
(a) Topographical map of the difference between prestimulus heartbeat-evoked responses in hits and misses, grand-averaged across 17 subjects, in the 135—171 ms time window, after ICA correction, on magnetometer signals. The topography of the difference was not affected by ICA correction. (b) T-locked magnetic fields at the sensor indicated in white in A, before (top) and after (bottom) ICA correction. The R and T waves could barely be observed on ICA corrected data, but the significant difference between hits and misses in the 135—171 ms time window (shaded area) was preserved. The overall shift toward more negative values in ICA-corrected data is due to data mean-centering by ICA. (c) Amplitude of the prestimulus heartbeat-evoked response, averaged across the cluster separately in hits and misses, and during a separate resting session with eyes open, after ICA correction. The heart-evoked response in the 135—171 ms cluster significantly differed between hits and misses (paired t-test, t16= 4.81, p=2.10—4). It was larger in hits than during rest (paired t-test, t16=3.46, p=0.003) and smaller in misses than during rest (paired t-test, t16=2.39, p=0.03). Because ICA extracts from MEG data the shape of each participant's heartbeat, this analysis further shows that the effect is not dependent on subject-specific heartbeat morphology. Error bars represent s.e.m.
- Supplementary Figure 5: Distribution of respiration phase in hits and misses at stimulus onset. (31 KB)
Each point represents a subject and a condition. No preferential phase emerged (Raighley test for non-uniformity of circular data), neither in hits (p=0.81) nor in misses (p=0.67).
- Supplementary Figure 6: Prestimulus peripheral blood pressure in hits and misses. (62 KB)
Blood pressure (arbitrary units) was computed over those heartbeats used to compute the heartbeat-evoked neural activity. (a) Time course of pressure, separately in hits and misses. (b) Difference between systolic and diastolic pressure, separately in hits and misses. No significant difference between hits and misses could be found in systolic, diastolic, nor difference between systolic and diastolic pressure. Error bars represent s.e.m.
- Supplementary Figure 7: Peripheral blood pressure throughout a trial. (56 KB)
The difference between systolic and diastolic pressure in arbitrary units was measured on the heartbeat preceding warning onset, preceding stimulus onset, preceding response, as well as the first (R+1) and second (R+2) heartbeats following response. Blood pressure evolved in the course of a trial, but did not differ between hits and misses (Greenhouse-Geisser corrected 2-way ANOVA with factors Consciousness and Time, main effect of Time F2.27,22.71=4,15, p=0.025; main effect of Consciousness F1,10=2.14, p=0.17; interaction F1.85,18.54=1.52, p=0.25; paired t-test between hits and misses before stimulus onset: t10=1.50, p=0.16). Error bars represent standard errors of the mean.
- Supplementary Text and Figures (749 KB)
Supplementary Figures 1–7 and Supplementary Tables 1–3