{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T07:03:38Z","timestamp":1793257418805,"version":"4.5.0"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2025,9,13]],"date-time":"2025-09-13T00:00:00Z","timestamp":1757721600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,9,13]],"date-time":"2025-09-13T00:00:00Z","timestamp":1757721600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["ERA PerMed JTC2019"],"award-info":[{"award-number":["ERA PerMed JTC2019"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["ERA PerMed JTC2019"],"award-info":[{"award-number":["ERA PerMed JTC2019"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["ERA PerMed JTC2019"],"award-info":[{"award-number":["ERA PerMed JTC2019"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["ERA PerMed JTC2019"],"award-info":[{"award-number":["ERA PerMed JTC2019"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["ERA PerMed JTC2019"],"award-info":[{"award-number":["ERA PerMed JTC2019"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["ERA PerMed JTC2019"],"award-info":[{"award-number":["ERA PerMed JTC2019"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001665","name":"Agence Nationale de la Recherche","doi-asserted-by":"publisher","award":["S.1600.ANR.HBPR"],"award-info":[{"award-number":["S.1600.ANR.HBPR"]}],"id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001665","name":"Agence Nationale de la Recherche","doi-asserted-by":"publisher","award":["S.1600.ANR.HBPR"],"award-info":[{"award-number":["S.1600.ANR.HBPR"]}],"id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]},{"name":"ECOS-SUD","award":["A20M02"],"award-info":[{"award-number":["A20M02"]}]},{"name":"ECOS-SUD","award":["A20M02"],"award-info":[{"award-number":["A20M02"]}]},{"name":"Ecole Doctorale Fronti\u00e8res de l\u2019Innovation en Recherche et Education\u2013Programme Bettencourt"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Brain Topogr"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>As a response to the environment and internal signals, brain networks reorganize on a sub-second scale. To capture this reorganization in patients with disorders of consciousness (DoC) and understand their residual brain activity, we investigated the dynamics of electroencephalography (EEG) microstates. EEG microstates are meta-stable topographies that last tens to a few hundreds of milliseconds and are hypothesized to reflect large-scale cortical networks. To obtain EEG\u2011microstate segmentation, EEG topographies per sample were clustered into four groups for the purpose of the present comparison with the existing four\u2011class literature. We then obtained a time series of maps with different frequencies of occurrence and duration. One such occurrence of a map with a given duration is called a microstate. The goal of this work was to study the static and dynamic properties of these topographical patterns in DoC patients. Using the microstate time series, we calculated static and dynamic markers. In contrast to the static, the dynamic metrics depend on the specific temporal sequences of the maps. The static measure map coverage showed differences between healthy controls and patients. In contrast, some dynamic markers captured inter-patient group differences. The dynamic markers we investigated are Mean Microstate Durations (MMD), Microstate Duration Variances (MDV), Microstate Transition Matrices (MTM), and Entropy Production (EP). The MMD and MDV decreased with the state of consciousness, whereas the MTM non-diagonal transitions and EP increased. In other words, DoC patients had slower and closer to equilibrium (time-reversible) brain dynamics. In conclusion, static and dynamic EEG microstate metrics differed across consciousness levels, with the latter having captured the subtler differences between groups of patients with DoC.<\/jats:p>","DOI":"10.1007\/s10548-025-01142-x","type":"journal-article","created":{"date-parts":[[2025,9,13]],"date-time":"2025-09-13T02:51:13Z","timestamp":1757731873000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Dynamics of EEG Microstates Change Across the Spectrum of Disorders of Consciousness"],"prefix":"10.1007","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2756-3263","authenticated-orcid":false,"given":"Dragana","family":"Manasova","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yonatan Sanz","family":"Perl","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas Marcelo","family":"Bruno","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melanie","family":"Valente","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin","family":"Rohaut","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enzo","family":"Tagliazucchi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lionel","family":"Naccache","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Federico","family":"Raimondo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacobo D.","family":"Sitt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,9,13]]},"reference":[{"issue":"24","key":"1142_CR1","doi-asserted-by":"publisher","first-page":"6583","DOI":"10.1523\/JNEUROSCI.0902-16.2016","volume":"36","author":"T Andrillon","year":"2016","unstructured":"Andrillon T, Poulsen AT, Hansen LK, Ger L\u00c9, D., Kouider S (2016) Neural markers of responsiveness to the environment in human sleep. J Neurosci 36(24):6583\u20136596. https:\/\/doi.org\/10.1523\/JNEUROSCI.0902-16.2016","journal-title":"J Neurosci"},{"issue":"5","key":"1142_CR2","doi-asserted-by":"publisher","first-page":"1672","DOI":"10.1073\/pnas.0809667106","volume":"106","author":"TA Bekinschtein","year":"2009","unstructured":"Bekinschtein TA, Dehaene S, Rohaut B, Tadel F, Cohen L, Naccache L (2009) Neural signature of the conscious processing of auditory regularities. Proc Natl Acad Sci 106(5):1672\u20131677. https:\/\/doi.org\/10.1073\/pnas.0809667106","journal-title":"Proc Natl Acad Sci"},{"issue":"5","key":"1142_CR3","doi-asserted-by":"publisher","first-page":"485","DOI":"10.1055\/S-0037-1607310","volume":"37","author":"YG Bodien","year":"2017","unstructured":"Bodien YG, Chatelle C, Edlow BL (2017) Functional networks in disorders of consciousness. Semin Neurol 37(5):485\u2013502. https:\/\/doi.org\/10.1055\/S-0037-1607310","journal-title":"Semin Neurol"},{"issue":"4","key":"1142_CR4","doi-asserted-by":"publisher","first-page":"1162","DOI":"10.1016\/j.neuroimage.2010.02.052","volume":"52","author":"J Britz","year":"2010","unstructured":"Britz J, Van De Ville D, Michel CM (2010) BOLD correlates of EEG topography reveal rapid resting-state network dynamics. Neuroimage 52(4):1162\u20131170. https:\/\/doi.org\/10.1016\/j.neuroimage.2010.02.052","journal-title":"Neuroimage"},{"issue":"3","key":"1142_CR5","doi-asserted-by":"publisher","first-page":"2129","DOI":"10.1016\/j.neuroimage.2012.05.060","volume":"62","author":"V Brodbeck","year":"2012","unstructured":"Brodbeck V, Kuhn A, von Wegner F, Morzelewski A, Tagliazucchi E, Borisov S, Michel CM, Laufs H (2012) EEG microstates of wakefulness and NREM sleep. Neuroimage 62(3):2129\u20132139. https:\/\/doi.org\/10.1016\/j.neuroimage.2012.05.060","journal-title":"Neuroimage"},{"issue":"2","key":"1142_CR6","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1007\/s10548-018-0689-9","volume":"32","author":"IM Comsa","year":"2019","unstructured":"Comsa IM, Bekinschtein TA, Chennu S (2019) Transient topographical dynamics of the electroencephalogram predict brain connectivity and behavioural responsiveness during drowsiness. Brain Topogr 32(2):315\u2013331. https:\/\/doi.org\/10.1007\/s10548-018-0689-9","journal-title":"Brain Topogr"},{"issue":"1","key":"1142_CR7","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1038\/nrn2961","volume":"12","author":"G Deco","year":"2011","unstructured":"Deco G, Jirsa VK, McIntosh AR (2011) Emerging concepts for the dynamical organization of resting-state activity in the brain. Nat Rev Neurosci 12(1):43\u201356. https:\/\/doi.org\/10.1038\/nrn2961","journal-title":"Nat Rev Neurosci"},{"issue":"2","key":"1142_CR8","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.aat7603","volume":"5","author":"A Demertzi","year":"2019","unstructured":"Demertzi A, Tagliazucchi E, Dehaene S, Deco G, Barttfeld P, Raimondo F, Martial C, Fern\u00e1ndez-Espejo D, Rohaut B, Voss HU, Schiff ND, Owen AM, Laureys S, Naccache L, Sitt JD (2019) Human consciousness is supported by dynamic complex patterns of brain signal coordination. Sci Adv 5(2):eaat7603. https:\/\/doi.org\/10.1126\/sciadv.aat7603","journal-title":"Sci Adv"},{"issue":"11","key":"1142_CR9","doi-asserted-by":"publisher","first-page":"3179","DOI":"10.1093\/brain\/awy251","volume":"141","author":"DA Engemann","year":"2018","unstructured":"Engemann DA, 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 JD (2018) Robust EEG-based cross-site and cross-protocol classification of states of consciousness. Brain 141(11):3179\u20133192. https:\/\/doi.org\/10.1093\/brain\/awy251","journal-title":"Brain"},{"issue":"3","key":"1142_CR10","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1212\/WNL.58.3.349","volume":"58","author":"JT Giacino","year":"2002","unstructured":"Giacino JT, Ashwal S, Childs N, Cranford R, Jennett B, Katz DI, Kelly JP, Rosenberg JH, Whyte J, Zafonte RD, Zasler ND (2002) The minimally conscious state: definition and diagnostic criteria. Neurology 58(3):349\u2013353. https:\/\/doi.org\/10.1212\/WNL.58.3.349","journal-title":"Neurology"},{"key":"1142_CR11","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/S0079-6123(09)17704-X","volume":"177","author":"JT Giacino","year":"2009","unstructured":"Giacino JT, Schnakers C, Rodriguez-Moreno D, Kalmar K, Schiff N, Hirsch J (2009) Behavioral assessment in patients with disorders of consciousness: gold standard or fool\u2019s gold? Prog Brain Res 177:33\u201348. https:\/\/doi.org\/10.1016\/S0079-6123(09)17704-X","journal-title":"Prog Brain Res"},{"key":"1142_CR12","doi-asserted-by":"publisher","first-page":"446","DOI":"10.1016\/j.neuroimage.2013.10.027","volume":"86","author":"A Gramfort","year":"2014","unstructured":"Gramfort A, Luessi M, Larson E, Engemann DA, Strohmeier D, Brodbeck C, Parkkonen L, H\u00e4m\u00e4l\u00e4inen MS (2014) MNE software for processing MEG and EEG data. Neuroimage 86:446\u2013460. https:\/\/doi.org\/10.1016\/j.neuroimage.2013.10.027","journal-title":"Neuroimage"},{"issue":"6","key":"1142_CR13","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1038\/s41593-020-0639-1","volume":"23","author":"P Gui","year":"2020","unstructured":"Gui P, Jiang Y, Zang D, Qi Z, Tan J, Tanigawa H, Jiang J, Wen Y, Xu L, Zhao J, Mao Y, Poo M, ming, Ding N, Dehaene S, Wu X, Wang L (2020) Assessing the depth of Language processing in patients with disorders of consciousness. Nat Neurosci 23(6):761\u2013770. https:\/\/doi.org\/10.1038\/s41593-020-0639-1","journal-title":"Nat Neurosci"},{"key":"1142_CR14","doi-asserted-by":"publisher","unstructured":"Guzm\u00e1n EG, Perl YS, Vohryzek J, Escrichs A, Manasova D, T\u00fcrker B, Tagliazucchi E, Kringelbach M, Sitt JD, Deco G (2023) The lack of Temporal brain dynamics asymmetry as a signature of impaired consciousness States. Interface Focus 13(3). https:\/\/doi.org\/10.1098\/RSFS.2022.0086","DOI":"10.1098\/RSFS.2022.0086"},{"issue":"7753","key":"1142_CR15","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1016\/S0140-6736(72)90242-5","volume":"299","author":"B Jennett","year":"1972","unstructured":"Jennett B, Plum F (1972) Persistent vegetative state after brain damage: a syndrome in search of a name. Lancet 299(7753):734\u2013737. https:\/\/doi.org\/10.1016\/S0140-6736(72)90242-5","journal-title":"Lancet"},{"issue":"1","key":"1142_CR16","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1006\/nimg.2002.1070","volume":"16","author":"T Koenig","year":"2002","unstructured":"Koenig T, Prichep L, Lehmann D, Sosa PV, Braeker E, Kleinlogel H, Isenhart R, John ER (2002) Millisecond by millisecond, year by year: normative EEG microstates and developmental stages. Neuroimage 16(1):41\u201348. https:\/\/doi.org\/10.1006\/nimg.2002.1070","journal-title":"Neuroimage"},{"issue":"4","key":"1142_CR17","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1007\/s10548-014-0387-1","volume":"28","author":"A Kuhn","year":"2015","unstructured":"Kuhn A, Brodbeck V, Tagliazucchi E, Morzelewski A, von Wegner F, Laufs H (2015) Narcoleptic patients show fragmented EEG-microstructure during early NREM sleep. Brain Topogr 28(4):619\u2013635. https:\/\/doi.org\/10.1007\/s10548-014-0387-1","journal-title":"Brain Topogr"},{"key":"1142_CR18","first-page":"309","volume":"1","author":"D Lehmann","year":"1987","unstructured":"Lehmann D (1987) Principles of spatial analysis. Handb Electroencephalogr Clin Neurophysiology: Methods Anal Brain Electr Magn Signals 1:309\u2013354","journal-title":"Handb Electroencephalogr Clin Neurophysiology: Methods Anal Brain Electr Magn Signals"},{"key":"1142_CR19","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2109889118","author":"CW Lynn","year":"2021","unstructured":"Lynn CW, Cornblath EJ, Papadopoulos L, Bertolero MA, Bassett DS (2021) Broken detailed balance and entropy production in the human brain. PNAS. https:\/\/doi.org\/10.1073\/pnas.2109889118","journal-title":"PNAS"},{"key":"1142_CR20","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1016\/j.neuroimage.2017.11.062","volume":"180","author":"CM Michel","year":"2018","unstructured":"Michel CM, Koenig T (2018) EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: a review. Neuroimage 180:577\u2013593. https:\/\/doi.org\/10.1016\/j.neuroimage.2017.11.062","journal-title":"Neuroimage"},{"key":"1142_CR21","doi-asserted-by":"crossref","unstructured":"Michel CM, Koenig T, Brandeis D, Gianotti LRR, Wackermann J (2009) Electrical Neuroimaging. Cambridge Medicine","DOI":"10.1017\/CBO9780511596889"},{"key":"1142_CR22","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1016\/j.neuroimage.2015.08.023","volume":"125","author":"P Milz","year":"2016","unstructured":"Milz P, Faber PL, Lehmann D, Koenig T, Kochi K, Pascual-Marqui RD (2016) The functional significance of EEG microstates\u2014associations with modalities of thinking. Neuroimage 125:643\u2013656. https:\/\/doi.org\/10.1016\/j.neuroimage.2015.08.023","journal-title":"Neuroimage"},{"key":"1142_CR23","doi-asserted-by":"publisher","first-page":"116454","DOI":"10.1016\/j.neuroimage.2019.116454","volume":"208","author":"A Mishra","year":"2020","unstructured":"Mishra A, Englitz B, Cohen MX (2020) EEG microstates as a continuous phenomenon. Neuroimage 208:116454. https:\/\/doi.org\/10.1016\/j.neuroimage.2019.116454","journal-title":"Neuroimage"},{"issue":"4","key":"1142_CR24","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1007\/s10548-008-0054-5","volume":"20","author":"MM Murray","year":"2008","unstructured":"Murray MM, Brunet D, Michel CM (2008) Topographic ERP analyses: a step-by-step tutorial review. Brain Topogr 20(4):249\u2013264. https:\/\/doi.org\/10.1007\/s10548-008-0054-5","journal-title":"Brain Topogr"},{"issue":"7","key":"1142_CR25","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1109\/10.391164","volume":"42","author":"RD Pascual-Marqui","year":"1995","unstructured":"Pascual-Marqui RD, Michel CM, Lehmann D (1995) Segmentation of brain electrical activity into microstates: model estimation and validation. IEEE Trans Biomed Eng 42(7):658\u2013665. https:\/\/doi.org\/10.1109\/10.391164","journal-title":"IEEE Trans Biomed Eng"},{"key":"1142_CR26","doi-asserted-by":"publisher","unstructured":"Poulsen AT, Pedroni A, Langer N, Hansen LK (2018) Microstate EEGlab toolbox: An introductory guide. bioRxiv, 1\u201330. https:\/\/doi.org\/10.1101\/289850","DOI":"10.1101\/289850"},{"key":"1142_CR27","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.104.014411","author":"Y Sanz Perl","year":"2021","unstructured":"Sanz Perl Y, Bocaccio H, Pallavicini C, P\u00e9rez-Ipi\u00f1a I, Laureys S, Laufs H, Kringelbach M, Deco G, Tagliazucchi E (2021) Nonequilibrium brain dynamics as a signature of consciousness. Phys Rev E. https:\/\/doi.org\/10.1103\/PhysRevE.104.014411","journal-title":"Phys Rev E"},{"issue":"7","key":"1142_CR28","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1038\/s41583-022-00587-4","volume":"23","author":"AK Seth","year":"2022","unstructured":"Seth AK, Bayne T (2022) Theories of consciousness. Nat Rev Neurosci 23(7):439\u2013452. https:\/\/doi.org\/10.1038\/s41583-022-00587-4","journal-title":"Nat Rev Neurosci"},{"issue":"11","key":"1142_CR29","doi-asserted-by":"publisher","first-page":"2177","DOI":"10.1162\/neco_a_01229","volume":"31","author":"SB Shaw","year":"2019","unstructured":"Shaw SB, Dhindsa K, Reilly JP, Becker S (2019) Capturing the forest but missing the trees: microstates inadequate for characterizing shorter-scale EEG dynamics. Neural Comput 31(11):2177\u20132211. https:\/\/doi.org\/10.1162\/neco_a_01229","journal-title":"Neural Comput"},{"issue":"9","key":"1142_CR30","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.24949","volume":"41","author":"A Sikka","year":"2020","unstructured":"Sikka A, Jamalabadi H, Krylova M, Alizadeh S, Meer JN, Danyeli L, Deliano M, Vicheva P, Hahn T, Koenig T, Bathula DR, Walter M (2020) Investigating the temporal dynamics of electroencephalogram (EEG) microstates using recurrent neural networks. Hum Brain Mapp hbm24949. https:\/\/doi.org\/10.1002\/hbm.24949","journal-title":"Hum Brain Mapp"},{"issue":"8","key":"1142_CR31","doi-asserted-by":"publisher","first-page":"2258","DOI":"10.1093\/brain\/awu141","volume":"137","author":"JD Sitt","year":"2014","unstructured":"Sitt JD, King J-R, Karoui E, Rohaut I, Faugeras B, Gramfort F, Cohen A, Sigman L, Dehaene M, S., Naccache L (2014) Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state. Brain 137(8):2258\u20132270. https:\/\/doi.org\/10.1093\/brain\/awu141","journal-title":"Brain"},{"issue":"5","key":"1142_CR32","doi-asserted-by":"publisher","first-page":"848","DOI":"10.1007\/s10548-018-0643-x","volume":"31","author":"S Stefan","year":"2018","unstructured":"Stefan S, Schorr B, Lopez-Rolon A, Kolassa I-T, Shock JP, Rosenfelder M, Heck S, Bender A (2018) Consciousness indexing and outcome prediction with resting-state EEG in severe disorders of consciousness. Brain Topogr 31(5):848\u2013862. https:\/\/doi.org\/10.1007\/s10548-018-0643-x","journal-title":"Brain Topogr"},{"key":"1142_CR33","unstructured":"Titterington DM, Titterington P of, Smith SDM, A. F. M., Makov UE (1985) Statistical Analysis of Finite Mixture Distributions. Wiley"},{"issue":"3","key":"1142_CR34","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1007\/S10548-023-00939-Y","volume":"37","author":"E Topluta\u015f","year":"2024","unstructured":"Topluta\u015f E, Ayd\u0131n F, Hano\u011flu L (2024) EEG microstate analysis in patients with disorders of consciousness and its clinical significance. Brain Topogr 37(3):377\u2013387. https:\/\/doi.org\/10.1007\/S10548-023-00939-Y","journal-title":"Brain Topogr"},{"key":"1142_CR35","doi-asserted-by":"publisher","first-page":"30","DOI":"10.3389\/fninf.2018.00030","volume":"12","author":"F von Wegner","year":"2018","unstructured":"von Wegner F, Laufs H (2018) Information-Theoretical analysis of EEG microstate sequences in python. Front Neuroinformatics 12:30. https:\/\/doi.org\/10.3389\/fninf.2018.00030","journal-title":"Front Neuroinformatics"},{"key":"1142_CR36","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.neuroimage.2017.06.062","volume":"158","author":"F von Wegner","year":"2017","unstructured":"von Wegner F, Tagliazucchi E, Laufs H (2017) Information-theoretical analysis of resting state EEG microstate sequences\u2014non-Markovianity, non-stationarity and periodicities. Neuroimage 158:99\u2013111. https:\/\/doi.org\/10.1016\/j.neuroimage.2017.06.062","journal-title":"Neuroimage"},{"key":"1142_CR37","doi-asserted-by":"publisher","first-page":"116631","DOI":"10.1016\/j.neuroimage.2020.116631","volume":"211","author":"AP Zanesco","year":"2020","unstructured":"Zanesco AP, King BG, Skwara AC, Saron CD (2020) Within and between-person correlates of the temporal dynamics of resting EEG microstates. Neuroimage 211:116631. https:\/\/doi.org\/10.1016\/j.neuroimage.2020.116631","journal-title":"Neuroimage"}],"container-title":["Brain Topography"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10548-025-01142-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10548-025-01142-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10548-025-01142-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T11:47:52Z","timestamp":1763552872000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10548-025-01142-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,13]]},"references-count":37,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,11]]}},"alternative-id":["1142"],"URL":"https:\/\/doi.org\/10.1007\/s10548-025-01142-x","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2024.05.30.596582","asserted-by":"object"}]},"ISSN":["0896-0267","1573-6792"],"issn-type":[{"value":"0896-0267","type":"print"},{"value":"1573-6792","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,13]]},"assertion":[{"value":"6 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 September 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Jacobo D. Sitt and Lionel Naccache are scientific co-founders of NeuroMeters (have scientific advisory activity but no executive or management activity).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"65"}}