[en] The neuronal connectivity patterns that differentiate consciousness from unconsciousness remain unclear. Previous studies have demonstrated that effective connectivity, as assessed by transcranial magnetic stimulation combined with electroencephalography (TMS-EEG), breaks down during the loss of consciousness. This study investigated changes in EEG connectivity associated with consciousness during non-rapid eye movement (NREM) sleep following parietal TMS. Compared with unconsciousness, conscious experiences during NREM sleep were associated with reduced phase-locking at low frequencies (<4 Hz). Transitivity and clustering coefficient in the delta and theta bands were also significantly lower during consciousness compared to unconsciousness, with differences in the clustering coefficient observed in scalp electrodes over parietal-occipital regions. There were no significant differences in Granger-causality patterns in frontal-to-parietal or parietal-to-frontal connectivity between reported unconsciousness and reported consciousness. Together these results suggest that alterations in spectral and spatial characteristics of network properties in posterior brain areas, in particular decreased local (segregated) connectivity at low frequencies, is a potential indicator of consciousness during sleep.
Disciplines :
Neurosciences & behavior
Author, co-author :
Lee, Minji
Baird, Benjamin
Gosseries, Olivia ; Université de Liège - ULiège > Consciousness-Coma Science Group
Nieminen, Jaakko O.
Boly, Melanie
Postle, Bradley R.
Tononi, Giulio
Lee, Seong-Whan
Language :
English
Title :
Connectivity differences between consciousness and unconsciousness in non-rapid eye movement sleep: a TMS-EEG study.
Casali, A. G. et al. A theoretically based index of consciousness independent of sensory processing and behavior. Sci. Transl. Med. 5, 198ra105 (2013).
Massimini, M., Ferrarelli, F., Sarasso, S. & Tononi, G. Cortical mechanisms of loss of consciousness: insight from TMS/EEG studies. Arch. Ital. Biol. 150, 44–55 (2012).
Casarotto, S. et al. Stratification of unresponsive patients by an independently validated index of brain complexity. Ann. Neurol. 80, 718–729 (2016).
Massimini, M. et al. Breakdown of cortical effective connectivity during sleep. Science 309, 2228–2232 (2005).
Massimini, M. et al. Triggering sleep slow waves by transcranial magnetic stimulation. Proc. Natl. Acad. Sci. USA 104, 8496–8501 (2007).
Rosanova, M. et al. Sleep-like cortical OFF-periods disrupt causality and complexity in the brain of unresponsive wakefulness syndrome patients. Nat. Commun. 9, 4427 (2018).
Ferrarelli, F. et al. Breakdown in cortical effective connectivity during midazolam-induced loss of consciousness. Proc. Natl. Acad. Sci. USA 107, 2681–2686 (2010).
Sarasso, S. et al. Consciousness and complexity during unresponsiveness induced by propofol, xenon, and ketamine. Curr. Biol. 25, 3099–3105 (2015).
Sanders, R. D. et al. Propofol-induced unresponsiveness is associated with impaired feedforward connectivity in cortical hierarchy. Br. J. Anaesth. 121, 1084–1096 (2018).
Rosanova, M. et al. Recovery of cortical effective connectivity and recovery of consciousness in vegetative patients. Brain 135, 1308–1320 (2012).
Napolitani, M. et al. Transcranial magnetic stimulation combined with high-density EEG in altered states of consciousness. Brain Inj. 28, 1180–1189 (2014).
Ragazzoni, A. et al. Vegetative versus minimally conscious states: a study using TMS-EEG, sensory and event-related potentials. PLoS One 8, e57069 (2013).
Massimini, M. et al. Cortical reactivity and effective connectivity during REM sleep in humans. Cogn. Neurosci. 1, 176–183 (2010).
Lee, M. et al. Network properties in transitions of consciousness during propofol-induced sedation. Sci. Rep. 7, 16791 (2017).
Massimini, M., Tononi, G. & Huber, R. Slow waves, synaptic plasticity and information processing: insights from transcranial magnetic stimulation and high-density EEG experiments. Eur. J. Neurosci. 29, 1761–1770 (2009).
Valderrama, M. et al. Human gamma oscillations during slow wave sleep. PLoS One 7, e33477 (2012).
Sarasso, S. et al. Quantifying cortical EEG responses to TMS in (un)consciousness. Clin. EEG Neurosci. 45, 40–49 (2014).
Boly, M. et al. Hierarchical clustering of brain activity during human nonrapid eye movement sleep. Proc. Natl. Acad. Sci. USA 109, 5856–5861 (2012).
Murphy, M. et al. Propofol anesthesia and sleep: a high-density EEG study. Sleep 34, 283–291A (2011).
Chokroverty, S. Syntax of referencing in Sleep Disorders Medicine (ed. Chokroverty, S.) 153-194 (Springer 2017).
Nieminen, J. O. et al. Consciousness and cortical responsiveness: a within-state study during non-rapid eye movement sleep. Sci. Rep. 6, 30932 (2016).
Siclari, F., LaRocque, J. J., Postle, B. R. & Tononi, G. Assessing sleep consciousness within subjects using a serial awakening paradigm. Front. Psychol. 4, 542 (2013).
Siclari, F. et al. The neural correlates of dreaming. Nat. Neurosci. 20, 872–878 (2017).
Bortoletto, M., Veniero, D., Thut, G. & Miniussi, C. The contribution of TMS–EEG coregistration in the exploration of the human cortical connectome. Neurosci. Biobehav. Rev. 49, 114–124 (2015).
Drakesmith, M. et al. Overcoming the effects of false positives and threshold bias in graph theoretical analyses of neuroimaging data. NeuroImage 118, 313–333 (2015).
Pigorini, A. et al. Bistability breaks-off deterministic responses to intracortical stimulation during non-REM sleep. NeuroImage 112, 105–113 (2015).
Esser, S. K., Hill, S. & Tononi, G. Breakdown of effective connectivity during slow wave sleep: investigating the mechanism underlying a cortical gate using large-scale modeling. J. Neurophysiol. 102, 2096–2111 (2009).
Höller, Y. et al. Connectivity biomarkers can differentiate patients with different levels of consciousness. Clin. Neurophysiol. 125, 1545–1555 (2014).
Lee, H., Mashour, G. A., Noh, G.-J., Kim, S. & Lee, U. Reconfiguration of network hub structure after propofol-induced unconsciousness. Anesthesiology 119, 1347–1359 (2013).
Lee, M. et al. Change in functional networks for transitions between states of consciousness during midazolam-induced sedation. Conf. Proc. IEEE Eng. Med. Biol. Soc. 958–961 (IEEE) (2017).
Shafi, M. M., Westover, M. B., Oberman, L., Cash, S. S. & Pascual-Leone, A. Modulation of EEG functional connectivity networks in subjects undergoing repetitive transcranial magnetic stimulation. Brain Topogr. 27, 172–191 (2014).
Siclari, F. & Tononi, G. Local aspects of sleep and wakefulness. Curr. Opin. Neurobiol. 44, 222–227 (2017).
Koch, C., Massimini, M., Boly, M. & Tononi, G. Posterior and anterior cortex – where is the difference that makes the difference? Nat. Rev. Neurosci. 17, 666 (2016).
Boly, M. et al. Are the neural correlates of consciousness in the front or in the back of the cerebral cortex? Clinical and neuroimaging evidence. J. Neurosci. 37, 9603–9613 (2017).
Storm, J. F. et al. Consciousness regained: disentangling mechanisms, brain systems, and behavioral responses. J. Neurosci. 37, 10882–10893 (2017).
Sanders, R. D., Mostert, N., Lindroth, H., Tononi, G. & Sleigh, J. Is consciousness frontal? Two perioperative case reports that challenge that concept. Br. J. Anaesth. 121, 330–332 (2018).
Nicolaou, N., Hourris, S., Alexandrou, P. & Georgiou, J. EEG-based automatic classification of ‘awake’ versus ‘anesthetized’ state in general anesthesia using Granger causality. PLoS One 7, e33869 (2012).
Ryu, J.-H., Kim, P.-J., Kim, H.-G., Koo, Y.-S. & Shin, T. J. Investigating the effects of nitrous oxide sedation on frontal-parietal interactions. Neurosci. Lett. 651, 9–15 (2017).
Maksimow, A. et al. Directional connectivity between frontal and posterior brain regions is altered with increasing concentrations of propofol. PLoS One 9, e113616 (2014).
Koskinen, M., Seppänen, T., Tuukkanen, J., Yli-Hankala, A. & Jäntti, V. Propofol anesthesia induces phase synchronization changes in EEG. Clin. Neurophysiol. 112, 386–392 (2001).
Liang, Z. et al. A comparison of different synchronization measures in electroencephalogram during propofol anesthesia. J. Clin. Monit. Comput. 30, 451–466 (2016).
Funk, C. M. et al. Local slow waves in superficial layers of primary cortical areas during REM Sleep. Curr. Biol. 26, 396–403 (2016).
Blain-Moraes, S. et al. Neurophysiological correlates of sevoflurane-induced unconsciousness. Anesthesiol. 122, 307–316 (2015).
Vinck, M., Oostenveld, R., van Wingerden, M., Battaglia, F. & Pennartz, C. M. A. An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias. NeuroImage 55, 1548–1565 (2011).
Van de Steen, F. et al. Critical comments on EEG sensor space dynamical connectivity analysis. Brain Topogr. 1–12 (2016).
Omidvarnia, A. et al. Measuring time-varying information flow in scalp EEG signals: orthogonalized partial directed coherence. IEEE Trans. Biomed. Eng. 61, 680–693 (2014).
Berry, R. B. et al. Rules for scoring respiratory events in sleep: update of the 2007 AASM manual for the scoring of sleep and associated events. J. Clin. Sleep Med. 8, 597–619 (2012).
Casarotto, S. et al. EEG responses to TMS are sensitive to changes in the perturbation parameters and repeatable over time. PLoS One 5, e10281 (2010).
Delorme, A. & Makeig, S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134, 9–21 (2004).
Lachaux, J.-P., Rodriguez, E., Martinerie, J. & Varela, F. J. Measuring phase synchrony in brain signals. Hum. Brain Mapp. 8, 194–208 (1999).
Sakkalis, V. Review of advanced techniques for the estimation of brain connectivity measured with EEG/MEG. Comput. Biol. Med. 41, 1110–1117 (2011).
Glerean, E., Salmi, J., Lahnakoski, J. M., Jääskeläinen, I. P. & Sams, M. Functional magnetic resonance imaging phase synchronization as a measure of dynamic functional connectivity. Brain Connect. 2, 91–101 (2012).
Gupta, R., Laghari, K. R. & Falk, T. H. Relevance vector classifier decision fusion and EEG graph-theoretic features for automatic affective state characterization. Neurocomputing 174, 875–884 (2016).
Rubinov, M. & Sporns, O. Complex network measures of brain connectivity: Uses and interpretations. NeuroImage 52, 1059–1069 (2010).
Watts, D. J. & Strogatz, S. H. Collective dynamics of ‘small-world’ networks. Nature 393, 440–442 (1998).
Newman, M. E. J. The structure and function of complex networks. SIAM Rev. 45, 167–256 (2003).
Barnett, L. & Seth, A. K. The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference. J. Neurosci. Methods 223, 50–68 (2014).
Akaike, H. A new look at the statistical model identification. IEEE Trans. Automat. Contr. 19, 716–723 (1974).
Nichols, T. E. & Holmes, A. P. Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum. Brain Mapp. 15, 1–25 (2002).
