[en] [en] BACKGROUND: This multi-centric study aimed to explore differences in brain activity patterns in patients with disorders of consciousness (DoC), including unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS).
METHODS: Using high-density electroencephalographic (EEG) recordings from 368 DoC patients, 39 who emerged from MCS (eMCS), and 73 healthy controls, we examined instantaneous functional connectivity-based meta-states acting as attractors in a dynamical system, extracted by means of community detection algorithms and recurrence analysis. We analyzed data from two patient cohorts and included resting-state and auditory processing tasks in four frequency bands (delta, theta, alpha, beta) and from three perspectives, namely: (i) discrete activation of dominant states, (ii) a dynamical system composed of attractor states and (iii) the correlation and anticorrelation patterns of the active states.
RESULTS: Findings revealed that while the overall structure of brain connectivity remained stable after injury, patients with DoC and those who emerged showed notable differences in the speed and consistency of how their brain states activated. Specifically, in higher frequencies, UWS patients exhibited faster, and less stable dynamics, shorter dwell times and decreased meta-state anticorrelation compared to those in MCS and eMCS. Moreover, a four-way combined learning classification analysis showed that the measures were able to distinguish the UWS and MCS subgroups.
SIGNIFICANCE: These brain state dynamics could serve as valuable markers for assessing states of consciousness. Our results highlight the potential of using high-temporal resolution dynamic brain activity patterns to improve the understanding of altered consciousness and their application to clinical settings.
Disciplines :
Neurosciences & behavior
Author, co-author :
Nunez Novo, Pablo ; Coma Science Group, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium, NeuroRehab & Consciousness Clinic, Neurology Department, University Hospital of Liège, Liège, Belgium, Biomedical Engineering Group, University of Valladolid, Valladolid, Spain, Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Madrid, Spain. Electronic address: P.Nunez@uliege.be
Tewarie, Prejaas ; Clinical Neurophysiology Group, University of Twente, Enschede, the Netherlands, Sir Peter Mansfield Imaging Centre, School of Physics, University of Nottingham, United Kingdom, CERVO Brain Research Centre, Laval University, Québec, Canada
Rodríguez-González, Víctor ; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain, Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Madrid, Spain
Alnagger, Naji ; Université de Liège - ULiège > GIGA > GIGA Neurosciences - Coma Science Group
Fundação Bial KBFUS - King Baudouin Foundation United States F.R.S.-FNRS - Fonds de la Recherche Scientifique ERDF - European Regional Development Fund FWO - Research Foundation Flanders MSF - Mind Science Foundation KBS - Koning Boudewijnstichting Fonds Léon Fredericq ISCIII - Instituto de Salud Carlos III NSCF - National Natural Science Foundation of China EC - European Commission Marie Skłodowska-Curie Actions
Funding text :
We thank the patients, their families and the control subjects for participating in our study. The authors extend their gratitude to the entire staff of the ICU, Nuclear Medicine and Radiodiagnostic departments at the University Hospital of Li\u00E8ge. We are especially thankful to the members of the Coma Science Group for their assistance with the clinical evaluations. This work was supported by the University and University Hospital of Li\u00E8ge, the Belgian National Funds for Scientific Research (FRS-FNRS), the FNRS PDR project (T.0134.21), the FNRS MIS project (F.4521.23), the FLAG-ERA JTC2021 project ModelDXConsciousness (Human Brain Project Partnering Project) and FLAG-ERA JTC 2023 - HBP - Basic and Applied Research, project BrainAct, the program Investissements d'avenir ANR-10-IAIHU-06, JTC the fund Generet, the King Baudouin Foundation, the BIAL Foundation, the Funds Chantal Schaeck Yolande, the T\u00E9l\u00E9vie Foundation, the Mind Science Foundation, the European Commission, the Fondation Leon Fredericq, the Mind-Care foundation, the National Natural Science Foundation of China (Joint Research Project 81471100), the European Foundation of Biomedical Research FERB Onlus, the Horizon 2020 MSCA \u2013 Research and Innovation Staff Exchange DoC-Box project (HORIZON-MSCA-2022-SE-01-01; 101131344), by \"MICIU/AEI/10.13039/501100011033\u2033 and \"ERDF A way of making Europe\" through the project PID2022-138286NB-I00, and \"CIBER en Bioingenier\u00EDa, Biomateriales y Nanomedicina (CIBER-BBN)\" through \"Instituto de Salud Carlos III\" co-funded with ERDF funds. NA and MMV are research fellows, OG and AT are research associates, and SL is research director at the F.R.S.-FNRS. JA is postdoctoral fellow at the FWO (1265522N).
Abásolo, D., Hornero, R., Gómez, C., García, M., López, M., 2006. Analysis of EEG background activity in Alzheimer’s disease patients with Lempel-Ziv complexity and central tendency measure. Med. Eng. Phys. 28, 315–322. https://doi.org/10.1016/j.medengphy.2005.07.004
Alnagger, N., Cardone, P., Martial, C., Laureys, S., Annen, J., Gosseries, O., 2023. The current and future contribution of neuroimaging to the understanding of disorders of consciousness. Presse Med.. 52, 104163. https://doi.org/10.1016/j.lpm.2022.104163
American Academy Of Sleep Medicine, 2023. The AASM Manual for the Scoring of Sleep and Associated Events Version 3. American Academy Of Sleep Medicine.
Annen, J., Frasso, G., van der Lande, G.J.M., Bonin, E.A.C., Vitello, M.M., Panda, R., Sala, A., Cavaliere, C., Raimondo, F., Bahri, M.A., Schiff, N.D., Gosseries, O., Thibaut, A., Laureys, S., 2023. Cerebral electrometabolic coupling in disordered and normal states of consciousness. Cell Rep.. 42, 112854. https://doi.org/10.1016/j.celrep.2023.112854
Arbabshirani, M.R., Havlicek, M., Kiehl, K.A., Pearlson, G.D., Calhoun, V.D., 2013. Functional network connectivity during rest and task conditions: a comparative study. Hum. Brain Mapp. 34, 2959–2971. https://doi.org/10.1002/hbm.22118
Bai, Y., He, J., Xia, X., Wang, Y., Yang, Y., Di, H., Li, X., Ziemann, U., 2021. Spontaneous transient brain states in EEG source space in disorders of consciousness. Neuroimage 240, 118407. https://doi.org/10.1016/j.neuroimage.2021.118407
Baker, A.P., Brookes, M.J., Rezek, I.A., Smith, S.M., Behrens, T., Probert Smith, P.J., Woolrich, M., 2014. Fast transient networks in spontaneous human brain activity. Elife 3, 1–18. https://doi.org/10.7554/eLife.01867
Barttfeld, P., Uhrig, L., Sitt, J.D., Sigman, M., Jarraya, B., Dehaene, S., 2015. Signature of consciousness in the dynamics of resting-state brain activity. Proc. Natl. Acad. Sci. 112, 887–892. https://doi.org/10.1073/pnas.1418031112
Bekinschtein, T.A., Dehaene, S., Rohaut, B., Tadel, F., Cohen, L., Naccache, L., 2009. Neural signature of the conscious processing of auditory regularities. Proc. Natl. Acad. Sci. U. S. A. 106, 1672–1677. https://doi.org/10.1073/pnas.0809667106
Benjamini, Y., Hochberg, Y., 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. 57, 289–300. https://doi.org/10.2307/2346101
Blondel, V.D., Guillaume, J.-L., Lambiotte, R., Lefebvre, E., 2008. Fast unfolding of communities in large networks. J. Stat. Mech. Theory Exp. 2008, P10008. https://doi.org/10.1088/1742-5468/2008/10/P10008
Bodien, Y.G., Allanson, J., Cardone, P., Bonhomme, A., Carmona, J., Chatelle, C., Chennu, S., Conte, M., Dehaene, S., Finoia, P., Heinonen, G., Hersh, J.E., Kamau, E., Lawrence, P.K., Lupson, V.C., Meydan, A., Rohaut, B., Sanders, W.R., Sitt, J.D., Soddu, A., Valente, M., Velazquez, A., Voss, H.U., Vrosgou, A., Claassen, J., Edlow, B.L., Fins, J.J., Gosseries, O., Laureys, S., Menon, D., Naccache, L., Owen, A.M., Pickard, J., Stamatakis, E.A., Thibaut, A., Victor, J.D., Giacino, J.T., Bagiella, E., Schiff, N.D., 2024. Cognitive motor dissociation in disorders of consciousness. N. Engl. J. Med. 391, 598–608. https://doi.org/10.1056/NEJMoa2400645
Brookes, M.J., Woolrich, M.W., Barnes, G.R., 2012. Measuring functional connectivity in MEG: a multivariate approach insensitive to linear source leakage. Neuroimage 63, 910–920. https://doi.org/10.1016/j.neuroimage.2012.03.048
Cabral, J., Vidaurre, D., Marques, P., Magalhães, R., Silva Moreira, P., Miguel Soares, J., Deco, G., Sousa, N., Kringelbach, M.L., 2017. Cognitive performance in healthy older adults relates to spontaneous switching between states of functional connectivity during rest. Sci. Rep. 7, 5135. https://doi.org/10.1038/s41598-017-05425-7
Candia-Rivera, D., Annen, J., Gosseries, O., Martial, C., Thibaut, A., Laureys, S., Tallon-Baudry, C., 2021. Neural responses to heartbeats detect residual signs of consciousness during resting state in postcomatose patients. J. Neurosci. 41, 5251–5262. doi:10.1523/JNEUROSCI.1740-20.2021.
Cavanna, F., Vilas, M.G., Palmucci, M., Tagliazucchi, E., 2018. Dynamic functional connectivity and brain metastability during altered states of consciousness. Neuroimage 180, 383–395. https://doi.org/10.1016/j.neuroimage.2017.09.065
Chennu, S., Annen, J., Wannez, S., Thibaut, A., Chatelle, C., Cassol, H., Martens, G., Schnakers, C., Gosseries, O., Menon, D., Laureys, S., 2017. Brain networks predict metabolism, diagnosis and prognosis at the bedside in disorders of consciousness. Brain 140, 2120–2132. https://doi.org/10.1093/brain/awx163
Claassen, J., Kondziella, D., Alkhachroum, A., Diringer, M., Edlow, B.L., Fins, J.J., Gosseries, O., Hannawi, Y., Rohaut, B., Schnakers, C., Stevens, R.D., Thibaut, A., Monti, M., 2024. Cognitive motor dissociation: gap analysis and future directions. Neurocrit. Care 40, 81–98. https://doi.org/10.1007/s12028-023-01769-3
Cohen, J., 1960. A coefficient of agreement for nominal scales. Educ. Psychol. Meas. 20, 37–46. https://doi.org/10.1177/001316446002000104
Deco, G., Jirsa, V.K., 2012. Ongoing cortical activity at rest: criticality, multistability, and ghost attractors. J. Neurosci. 32, 3366–3375. https://doi.org/10.1523/JNEUROSCI.2523-11.2012
Della Bella, G.A., Zang, D., Gui, P., Mateos, D.M., Sitt, J.D., Bekinschtein, T.A., Manasova, D., Sarton, B., Ferre, F., Silva, S., Lamberti, P.W., Wu, X., Mao, Y., Wang, L., Barttfeld, P., 2022. EEG brain states for real-time detection of covert cognition in disorders of consciousness. PsyArXiv 1–21. https://doi.org/10.31234/osf.io/dbzp6
Demertzi, A., Antonopoulos, G., Heine, L., Voss, H.U., Crone, J.S., De Los Angeles, C., Bahri, M.A., Di Perri, C., Vanhaudenhuyse, A., Charland-Verville, V., Kronbichler, M., Trinka, E., Phillips, C., Gomez, F., Tshibanda, L., Soddu, A., Schiff, N.D., Whitfield-Gabrieli, S., Laureys, S., 2015. Intrinsic functional connectivity differentiates minimally conscious from unresponsive patients. Brain 138, 2619–2631. https://doi.org/10.1093/brain/awv169
Demertzi, A., Soddu, A., Laureys, S., 2013. Consciousness supporting networks. Curr. Opin. Neurobiol. 23, 239–244. https://doi.org/10.1016/j.conb.2012.12.003
Demertzi, A., Tagliazucchi, E., Dehaene, S., Deco, G., Barttfeld, P., Raimondo, F., Martial, C., Fernández-Espejo, D., Rohaut, B., Voss, H.U., Schiff, N.D., Owen, A.M., Laureys, S., Naccache, L., Sitt, J.D., 2019. Human consciousness is supported by dynamic complex patterns of brain signal coordination. Sci. Adv. 5, 1–12. https://doi.org/10.1126/sciadv.aat7603
Di Perri, C., Bahri, M.A., Amico, E., Thibaut, A., Heine, L., Antonopoulos, G., Charland-Verville, V., Wannez, S., Gomez, F., Hustinx, R., Tshibanda, L., Demertzi, A., Soddu, A., Laureys, S., 2016. Neural correlates of consciousness in patients who have emerged from a minimally conscious state: a cross-sectional multimodal imaging study. Lancet Neurol.. 15, 830–842. https://doi.org/10.1016/S1474-4422(16)00111-3
Edlow, B.L., Claassen, J., Schiff, N.D., Greer, D.M., 2021. Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies. Nat. Rev. Neurol. 17, 135–156. https://doi.org/10.1038/s41582-020-00428-x
Engels, M.M.A., van der Flier, W.M., Stam, C.J., Hillebrand, A., Scheltens, P., van Straaten, E.C.W., 2017. Alzheimer’s disease: the state of the art in resting-state magnetoencephalography. Clin. Neurophysiol. 128, 1426–1437. https://doi.org/10.1016/j.clinph.2017.05.012
Engemann, D., Raimondo, F., King, J.-R., Jas, M., Gramfort, A., Dehaene, S., Naccache, L., Sitt, J., 2015. Automated measurement and prediction of consciousness in vegetative and minimally conscious patients. ICML Work. Stat. Mach. Learn. Neurosci. (Stamlins 2015).
Engemann, D.A., Raimondo, F., King, J.-R., Rohaut, B., Louppe, G., Faugeras, F., Annen, J., Cassol, H., Gosseries, O., Fernandez-Slezak, D., Laureys, S., Naccache, L., Dehaene, S., Sitt, J.D., 2018. Robust EEG-based cross-site and cross-protocol classification of states of consciousness. Brain 141, 3179–3192. https://doi.org/10.1093/brain/awy251
Forgacs, P.B., Frey, H.P., Velazquez, A., Thompson, S., Brodie, D., Moitra, V., Rabani, L., Park, S., Agarwal, S., Falo, M.C., Schiff, N.D., Claassen, J., 2017. Dynamic regimes of neocortical activity linked to corticothalamic integrity correlate with outcomes in acute anoxic brain injury after cardiac arrest. Ann. Clin. Transl. Neurol. 4, 119–129. https://doi.org/10.1002/acn3.385
Garrett, D.D., Samanez-Larkin, G.R., MacDonald, S.W.S., Lindenberger, U., McIntosh, A.R., Grady, C.L., 2013. Moment-to-moment brain signal variability: a next frontier in human brain mapping? Neurosci. Biobehav. Rev. 37, 610–624. https://doi.org/10.1016/j.neubiorev.2013.02.015
Gaser, C., Dahnke, R., Thompson, P.M., Kurth, F., Gaser, C., Ph, D., 2023. CAT – a computational anatomy toolbox for the analysis of structural MRI. bioRxiv. https://doi.org/10.1101/2022.06.11.495736
Gates, K.M., Henry, T., Steinley, D., Fair, D.A., 2016. A Monte Carlo evaluation of weighted community detection algorithms. Front. Neuroinform. 10. https://doi.org/10.3389/fninf.2016.00045
Gohil, C., Roberts, E., Timms, R., Skates, A., Higgins, C., Quinn, A., Pervaiz, U., van Amersfoort, J., Notin, P., Gal, Y., Adaszewski, S., Woolrich, M., 2022. Mixtures of large-scale dynamic functional brain network modes. Neuroimage 263, 119595. https://doi.org/10.1016/j.neuroimage.2022.119595
Gosseries, O., Zasler, N.D., Laureys, S., 2014. Recent advances in disorders of consciousness: focus on the diagnosis. Brain Inj.. 28, 1141–1150. https://doi.org/10.3109/02699052.2014.920522
Gramfort, A., Papadopoulo, T., Olivi, E., Clerc, M., 2010. OpenMEEG: opensource software for quasistatic bioelectromagnetics. Biomed. Eng. Online 9, 45. https://doi.org/10.1186/1475-925X-9-45
Haenschel, C., Baldeweg, T., Croft, R.J., Whittington, M., Gruzelier, J., 2000. Gamma and beta frequency oscillations in response to novel auditory stimuli: a comparison of human electroencephalogram (EEG) data with in vitro models. Proc. Natl. Acad. Sci. U. S. A. 97, 7645–7650. https://doi.org/10.1073/pnas.120162397
Hansen, E.C.A., Battaglia, D., Spiegler, A., Deco, G., Jirsa, V.K., 2015. Functional connectivity dynamics: modeling the switching behavior of the resting state. Neuroimage 105, 525–535. https://doi.org/10.1016/j.neuroimage.2014.11.001
Hao, Z., Xia, X., Pan, Y., Bai, Y., Wang, Y., Peng, B., Dou, W., 2024. Uncovering brain network insights for prognosis in disorders of consciousness: EEG source space analysis and brain dynamics. IEEE Trans. Neural Syst. Rehabil. Eng. 32, 144–153. https://doi.org/10.1109/TNSRE.2023.3346947
Hermann, B., Stender, J., Habert, M.O., Kas, A., Denis-Valente, M., Raimondo, F., Pérez, P., Rohaut, B., Sitt, J.D., Naccache, L., 2021. Multimodal FDG-PET and EEG assessment improves diagnosis and prognostication of disorders of consciousness. NeuroImage Clin.. 30. https://doi.org/10.1016/j.nicl.2021.102601
Hsiao, F.J., Wu, Z.A., Ho, L.T., Lin, Y.Y., 2009. Theta oscillation during auditory change detection: an MEG study. Biol. Psychol. 81, 58–66. https://doi.org/10.1016/j.biopsycho.2009.01.007
Hutchison, R.M., Womelsdorf, T., Gati, J.S., Everling, S., Menon, R.S., 2013. Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques. Hum. Brain Mapp. 34, 2154–2177. https://doi.org/10.1002/hbm.22058
Kondziella, D., Bender, A., Diserens, K., van Erp, W., Estraneo, A., Formisano, R., Laureys, S., Naccache, L., Ozturk, S., Rohaut, B., Sitt, J.D., Stender, J., Tiainen, M., Rossetti, A.O., Gosseries, O., Chatelle, C., 2020. European Academy of Neurology guideline on the diagnosis of coma and other disorders of consciousness. Eur. J. Neurol. 27, 741–756. https://doi.org/10.1111/ene.14151
Laureys, S., Celesia, G.G., Cohadon, F., Lavrijsen, J., León-Carrión, J., Sannita, W.G., Sazbon, L., Schmutzhard, E., von Wild, K.R., Zeman, A., Dolce, G., 2010. Unresponsive wakefulness syndrome: a new name for the vegetative state or apallic syndrome. BMC Med.. 8, 68. https://doi.org/10.1186/1741-7015-8-68
Li, Y., Gao, J., Yang, Y., Zhuang, Y., Kang, Q., Li, X., Tian, M., Lv, H., He, J., 2024. Temporal and spatial variability of dynamic microstate brain network in disorders of consciousness. CNS Neurosci. Ther. 30, 1–15. https://doi.org/10.1111/cns.14641
Lin, F.-H., Witzel, T., Hämäläinen, M.S., Dale, A.M., Belliveau, J.W., Stufflebeam, S.M., 2004. Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain. Neuroimage 23, 582–595. https://doi.org/10.1016/j.neuroimage.2004.04.027
López-González, A., Panda, R., Ponce-Alvarez, A., Zamora-López, G., Escrichs, A., Martial, C., Thibaut, A., Gosseries, O., Kringelbach, M.L., Annen, J., Laureys, S., Deco, G., 2021. Loss of consciousness reduces the stability of brain hubs and the heterogeneity of brain dynamics. Commun. Biol. 4, 1037. https://doi.org/10.1038/s42003-021-02537-9
Manasova, D., Perl, Y.S., Bruno, N.M., Valente, M., Rohaut, B., Tagliazucchi, E., Naccache, L., Raimondo, F., Sitt, J.D., 2024. Dynamics of EEG microstates change across the spectrum of disorders of consciousness. bioRxiv 2024.05.30.596582. https://doi.org/10.1101/2024.05.30.596582
Marwan, N., Carmen Romano, M., Thiel, M., Kurths, J., 2007. Recurrence plots for the analysis of complex systems. Phys. Rep. 438, 237–329. https://doi.org/10.1016/j.physrep.2006.11.001
Núñez, P., Gómez, C., Rodríguez-González, V., Hillebrand, A., Tewarie, P., Gomez-Pilar, J., Molina, V., Hornero, R., Poza, J., 2022. Schizophrenia induces abnormal frequency-dependent patterns of dynamic brain network reconfiguration during an auditory oddball task. J. Neural Eng. 19, 016033. https://doi.org/10.1088/1741-2552/ac514e
Núñez, P., Poza, J., Gómez, C., Rodríguez-González, V., Hillebrand, A., Tewarie, P., Tola-Arribas, M.Á., Cano, M., Hornero, R., 2021a. Abnormal meta-state activation of dynamic brain networks across the Alzheimer spectrum. Neuroimage 232, 117898. https://doi.org/10.1016/j.neuroimage.2021.117898
Núñez, P., Rodríguez-González, V., Gutiérrez-de Pablo, V., Gómez, C., Shigihara, Y., Hoshi, H., 2021b Effect of segment length, sampling frequency, and imaging modality on the estimation of measures of brain meta-state activation: an MEG/EEG study, in: Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society Conference.
O’Neill, G.C., Tewarie, P., Vidaurre, D., Liuzzi, L., Woolrich, M.W., Brookes, M.J., 2018. Dynamics of large-scale electrophysiological networks: a technical review. Neuroimage 180, 559–576. https://doi.org/10.1016/j.neuroimage.2017.10.003
Panda, R., Thibaut, A., Lopez-Gonzalez, A., Escrichs, A., Bahri, M.A., Hillebrand, A., Deco, G., Laureys, S., Gosseries, O., Annen, J., Tewarie, P., 2022. Disruption in structural–functional network repertoire and time-resolved subcortical fronto-temporoparietal connectivity in disorders of consciousness. Elife 11, 1–19. https://doi.org/10.7554/eLife.77462
Piarulli, A., Bergamasco, M., Thibaut, A., Cologan, V., Gosseries, O., Laureys, S., 2016. EEG ultradian rhythmicity differences in disorders of consciousness during wakefulness. J. Neurol. 263, 1746–1760. https://doi.org/10.1007/s00415-016-8196-y
Posner, J.B., Saper, C.B., Schiff, N., Plum, F., 2008. Plum and Posner’s Diagnosis of Stupor and Coma. Oxford University Press. https://doi.org/10.1093/med/9780195321319.001.0001
Raimondo, F., Rohaut, B., Demertzi, A., Valente, M., Engemann, D.A., Salti, M., Fernandez Slezak, D., Naccache, L., Sitt, J.D., 2017. Brain–heart interactions reveal consciousness in noncommunicating patients. Ann. Neurol. 82, 578–591. https://doi.org/10.1002/ana.25045
Sarasso, S., Casali, A.G., Casarotto, S., Rosanova, M., Sinigaglia, C., Massimini, M., 2021. Consciousness and complexity: a consilience of evidence. Neurosci. Conscious. 2021, 1–24. https://doi.org/10.1093/nc/niab023
Schiff, N.D., Nauvel, T., Victor, J.D., 2014. Large-scale brain dynamics in disorders of consciousness. Curr. Opin. Neurobiol. 25, 7–14. https://doi.org/10.1016/j.conb.2013.10.007
Schnakers, C., Giacino, J.T., Løvstad, M., Habbal, D., Boly, M., Di, H., Majerus, S., Laureys, S., 2015. Preserved covert cognition in noncommunicative patients with severe brain injury? Neurorehabil. Neural Repair 29, 308–317. https://doi.org/10.1177/1545968314547767
Schnakers, C., Hirsch, M., Noé, E., Llorens, R., Lejeune, N., Veeramuthu, V., De Marco, S., Demertzi, A., Duclos, C., Morrissey, A.-M., Chatelle, C., Estraneo, A., 2020. Covert cognition in disorders of consciousness: a meta-analysis. Brain Sci.. 10, 930. https://doi.org/10.3390/brainsci10120930
Seel, R.T., Sherer, M., Whyte, J., Katz, D.I., Giacino, J.T., Rosenbaum, A.M., Hammond, F.M., Kalmar, K., Pape, T.L.-B., Zafonte, R., Biester, R.C., Kaelin, D., Kean, J., Zasler, N., 2010. Assessment scales for disorders of consciousness: evidence-based recommendations for clinical practice and research. Arch. Phys. Med. Rehabil. 91, 1795–1813. https://doi.org/10.1016/j.apmr.2010.07.218
Sitt, J.D., King, J.R., El Karoui, I., Rohaut, B., Faugeras, F., Gramfort, A., Cohen, L., Sigman, M., Dehaene, S., Naccache, L., 2014. Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state. Brain 137, 2258–2270. https://doi.org/10.1093/brain/awu141
Stender, J., Gosseries, O., Bruno, M.A., Charland-Verville, V., Vanhaudenhuyse, A., Demertzi, A., Chatelle, C., Thonnard, M., Thibaut, A., Heine, L., Soddu, A., Boly, M., Schnakers, C., Gjedde, A., Laureys, S., 2014. Diagnostic precision of PET imaging and functional MRI in disorders of consciousness: a clinical validation study. Lancet 384, 514–522. https://doi.org/10.1016/S0140-6736(14)60042-8
Tadel, F., Baillet, S., Mosher, J.C., Pantazis, D., Leahy, R.M., 2011. Brainstorm: a user-friendly application for MEG/EEG analysis. Comput. Intell. Neurosci. 2011, 1–13. https://doi.org/10.1155/2011/879716
Tewarie, P., Liuzzi, L., O’Neill, G.C., Quinn, A.J., Griffa, A., Woolrich, M.W., Stam, C.J., Hillebrand, A., Brookes, M.J., 2019. Tracking dynamic brain networks using high temporal resolution MEG measures of functional connectivity. Neuroimage 200, 38–50. https://doi.org/10.1016/j.neuroimage.2019.06.006
Thibaut, A., Panda, R., Annen, J., Sanz, L.R.D., Naccache, L., Martial, C., Chatelle, C., Aubinet, C., Bonin, E.A.C., Barra, A., Briand, M., Cecconi, B., Wannez, S., Stender, J., Laureys, S., Gosseries, O., 2021. Preservation of brain activity in unresponsive patients identifies MCS star. Ann. Neurol. 90, 89–100. https://doi.org/10.1002/ana.26095
Todorovic, A., Schoffelen, J.-M., van Ede, F., Maris, E., de Lange, F.P., 2015. Temporal expectation and attention jointly modulate auditory oscillatory activity in the beta band. PLoS ONE 10, e0120288. https://doi.org/10.1371/journal.pone.0120288
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., Joliot, M., 2002. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15, 273–289. https://doi.org/10.1006/nimg.2001.0978
van der Lande, G.J.M., Casas-Torremocha, D., Manasanch, A., Dalla Porta, L., Gosseries, O., Alnagger, N., Barra, A., Mejías, J.F., Panda, R., Riefolo, F., Thibaut, A., Bonhomme, V., Thirion, B., Clasca, F., Gorostiza, P., Sanchez-Vives, M.V., Deco, G., Laureys, S., Zamora-López, G., Annen, J., 2024. Brain state identification and neuromodulation to promote recovery of consciousness. Brain Commun.. https://doi.org/10.1093/braincomms/fcae362
Vidaurre, D., Hunt, L.T., Quinn, A.J., Hunt, B.A.E., Brookes, M.J., Nobre, A.C., Woolrich, M.W., 2018. Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks. Nat. Commun. 9, 2987. https://doi.org/10.1038/s41467-018-05316-z
Vohryzek, J., Deco, G., Cessac, B., Kringelbach, M.L., Cabral, J., 2020. Ghost attractors in spontaneous brain activity: recurrent excursions into functionally-relevant BOLD phase-locking states. Front. Syst. Neurosci. 14, 1–15. https://doi.org/10.3389/fnsys.2020.00020
von Wegner, F., Wiemers, M., Hermann, G., Tödt, I., Tagliazucchi, E., Laufs, H., 2024. Complexity measures for EEG microstate sequences: concepts and algorithms. Brain Topogr.. 37, 296–311. https://doi.org/10.1007/s10548-023-01006-2
Webber, C., Zbilut, J., 2005. Recurrence quantification analysis of nonlinear dynamical systems. Tutorials in Contemporary Nonlinear Methods for the Behavioral Sciences 26–94.
Xia, M., Wang, J., He, Y., 2013. BrainNet Viewer: a network visualization tool for Human Brain connectomics. PLoS ONE 8. https://doi.org/10.1371/journal.pone.0068910
Zalesky, A., Fornito, A., Cocchi, L., Gollo, L.L., Breakspear, M., 2014. Time-resolved resting-state brain networks. Proc. Natl. Acad. Sci. 111, 10341–10346. https://doi.org/10.1073/pnas.1400181111
Zasler, N.D., Aloisi, M., Contrada, M., Formisano, R., 2019. Disorders of consciousness terminology: history, evolution and future directions. Brain Inj.. 33, 1684–1689. https://doi.org/10.1080/02699052.2019.1656821