Abstract
Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we believe has the potential to be effective in examining the resting state activities of the brain in different stages of consciousness by allowing the proper identification of vegetative and minimally conscious patients. As a result, we try to identify clinical evaluation scales and microstate characteristics with resting state EEGs from individuals with disorders of consciousness. Our prospective observational study included 28 individuals with a disorder of consciousness. Control group included 18 healthy subjects with proper EEG data. We made clinical evaluations using patient behavior scales. We also analyzed the EEGs using microstate analysis. In our study, microstate D coverage differed substantially between vegetative and minimally conscious state patients. Also, there was a strong connection between microstate D characteristics and clinical scale scores. Consequently, we have demonstrated that the most accurate parameter for representing consciousness level is microstate D. Microstate analysis appears to be a strong option for future use in the diagnosis, follow-up, and treatment response of patients with Disorders of Consciousness.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data Availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Artoni F, Maillard J, Britz J, Seeber M, Lysakowski C, Bréchet L, Michel CM (2022) EEG microstate dynamics indicate a U-shaped path to propofol-induced loss of consciousness. Neuroimage 256:119156
Aubinet C, Cassol H, Bodart O, Sanz LRD, Wannez S, Martial C, Thibaut A, Martens G, Carrière M, Gosseries O, Laureys S, Chatelle C (2021) Simplified evaluation of CONsciousness disorders (SECONDs) in individuals with severe brain injury: a validation study. Ann Phys Rehabil Med 64(5):101432. https://doi.org/10.1016/J.REHAB.2020.09.001
Beuthien-baumann B, Handrick W, Schmidt T, Burchert W, Oehme L, Kropp J, Schackert G, Pinkert J, Franke WG (2003) Persistent vegetative state: evaluation of brain metabolism and brain perfusion with pet and spect. Nucl Med Commun. https://doi.org/10.1097/00006231-200306000-00005
Bréchet L, Brunet D, Perogamvros L, Tononi G, Michel CM (2020) EEG microstates of dreams. Sci Rep 10(1):1–9
Britz J, van de Ville D, Michel CM (2010) BOLD correlates of EEG topography reveal rapid resting-state network dynamics. Neuroimage 52(4):1162–1170. https://doi.org/10.1016/j.neuroimage.2010.02.052
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):2129–2139. https://doi.org/10.1016/j.neuroimage.2012.05.060
Chang CY, Hsu SH, Pion-Tonachini L, Jung TP (2018) Evaluation of artifact subspace reconstruction for automatic EEG artifact removal. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2018 July, pp 1242–1245. https://doi.org/10.1109/EMBC.2018.8512547
Chu C, Wang X, Cai L, Zhang L, Wang J, Liu C, Zhu X (2020) Spatiotemporal EEG microstate analysis in drug-free patients with Parkinson’s disease. Neuroimage 25:102132. https://doi.org/10.1016/j.nicl.2019.102132
Custo A, Van De Ville D, Wells WM, Tomescu MI, Brunet D, Michel CM (2017) Electroencephalographic resting-state networks: source localization of microstates. Brain Connect 7(10):671–682
Delorme A, Makeig S (2004) EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134(1):9–21. https://doi.org/10.1016/j.jneumeth.2003.10.009
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):349–353. https://doi.org/10.1212/WNL.58.3.349
Giacino JT, Kalmar K, Whyte J (2004) The JFK coma recovery scale-revised: measurement characteristics and diagnostic utility. Arch Phys Med Rehabil. https://doi.org/10.1016/j.apmr.2004.02.033
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’s gold? Progress in brain research, vol 177. Elsevier, Amsterdam, pp 33–48. https://doi.org/10.1016/S0079-6123(09)17704-X
Giacino JT, Katz DI, Schiff ND, Whyte J, Ashman EJ, Ashwal S, Barbano R, Hammond FM, Laureys S, Ling GSF, Nakase-Richardson R, Seel RT, Yablon S, Getchius TSD, Gronseth GS, Armstrong MJ (2018) Practice guideline update recommendations summary: disorders of consciousness. Neurology 91(10):450–460
Guo Y, Li R, Zhang R, Liu C, Zhang L, Zhao D, Hu Y (2022) Dynamic changes of brain activity in patients with disorders of consciousness during recovery of consciousness. Front Neurosci. https://doi.org/10.3389/fnins.2022.878203
Ignacio Serrano J, del Castillo MD, Cortés V, Mendes N, Arroyo A, Andreo J, Rocon E, del Valle M, Herreros J, Romero JP (2018) EEG microstates change in response to increase in dopaminergic stimulation in typical Parkinson’s disease patients. Front Neurosci 12(OCT):714. https://doi.org/10.3389/fnins.2018.00714
Juengling FD, Kassubek J, Huppertz HJ, Krause T, Els T (2005) Separating functional and structural damage in persistent vegetative state using combined voxel-based analysis of 3-D MRI and FDG-PET. J Neurol Sci. https://doi.org/10.1016/j.jns.2004.11.052
Khanna A, Pascual-Leone A, Michel CM, Farzan F (2015) Microstates in resting-state EEG: current status and future directions. Neurosci Biobehav Rev 49:105–113. https://doi.org/10.1016/j.neubiorev.2014.12.010
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):41–48. https://doi.org/10.1006/nimg.2002.1070
Koenig T, Kottlow M, Stein M, Melie-García L (2011) Ragu: a free tool for the analysis of EEG and MEG event-related scalp field data using global randomization statistics. Comput Intel Neurosci. https://doi.org/10.1155/2011/938925
Laureys S, Goldman S, Phillips C, van Bogaert P, Aerts J, Luxen A, Franck G, Maquet P (1999a) Impaired effective cortical connectivity in vegetative state: preliminary investigation using PET. Neuroimage. https://doi.org/10.1006/nimg.1998.0414
Laureys S, Lemaire C, Maquet P, Phillips C, Franck G (1999b) Cerebral metabolism during vegetative state and after recovery to consciousness. J Neurol Neurosurg Psychiatr. https://doi.org/10.1136/jnnp.67.1.121
Lehmann D, Ozaki H, Pal I (1987) EEG alpha map series: brain micro-states by space-oriented adaptive segmentation. Electroencephalogr Clin Neurophysiol 67(3):271–288. https://doi.org/10.1016/0013-4694(87)90025-3
Luauté J, Maucort-Boulch D, Tell L, Quelard F, Sarraf T, Iwaz J, Boisson D, Fischer C (2010) Long-term outcomes of chronic minimally conscious and vegetative states. Neurology 75(3):246–252. https://doi.org/10.1212/WNL.0b013e3181e8e8df
Lull N, Noé E, Lull JJ, García-Panach J, Chirivella J, Ferri J, Lpez-Aznar D, Sopena P, Robles M (2010) Voxel-based statistical analysis of thalamic glucose metabolism in traumatic brain injury: relationship with consciousness and cognition. Brain Inj. https://doi.org/10.3109/02699052.2010.494592
Michel CM, Koenig T (2018) EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: a review. Neuroimage 180:577–593. https://doi.org/10.1016/j.neuroimage.2017.11.062
Murphy M, Whitton AE, Deccy S, Ironside ML, Rutherford A, Beltzer M, Pizzagalli DA (2020) Abnormalities in electroencephalographic microstates are state and trait markers of major depressive disorder. Neuropsychopharmacology 45(12):2030–2037
Nakao S, Takata S, Uemura H, Kashihara M, Osawa T, Komatsu K, Masuda Y, Okahisa T, Nishikawa K, Kondo S, Yamada M, Takahara R, Ogata Y, Nakamura Y, Nagahiro S, Kaji R, Yasui N (2010) Relationship between Barthel Index scores during the acute phase of rehabilitation and subsequent ADL in stroke patients. J Med Investig. https://doi.org/10.2152/jmi.57.81
Nishida K, Morishima Y, Yoshimura M, Isotani T, Irisawa S, Jann K, Dierks T, Strik W, Kinoshita T, Koenig T (2013) EEG microstates associated with salience and frontoparietal networks in frontotemporal dementia, schizophrenia and Alzheimer’s disease. Clin Neurophysiol 124(6):1106–1114. https://doi.org/10.1016/j.clinph.2013.01.005
Nuwer M (1997) Assessment of digital EEG, quantitative EEG, and EEG brain mapping: report of the American Academy of Neurology and the American Clinical Neurophysiology Society. Neurology 49(1):277–292. https://doi.org/10.1212/WNL.49.1.277
Pal A, Behari M, Goyal V, Sharma R (2021) Study of EEG microstates in Parkinson’s disease: a potential biomarker? Cogn Neurodyn 15(3):463–471. https://doi.org/10.1007/s11571-020-09643-0
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):658–665. https://doi.org/10.1109/10.391164
Plechawska-Wojcik M, Kaczorowska M, Zapala D (2018) The artifact subspace reconstruction (ASR) for EEG signal correction. A comparative study. International conference on information systems architecture and technology. Springer, Cham, pp 125–135
Schumacher J, Peraza LR, Firbank M, Thomas AJ, Kaiser M, Gallagher P, O’Brien JT, Blamire AM, Taylor JP (2019) Dysfunctional brain dynamics and their origin in Lewy body dementia. Brain 142(6):1767–1782. https://doi.org/10.1093/brain/awz069
Silva S, Alacoque X, Fourcade O, Samii K, Marque P, Woods R, Mazziotta J, Chollet F, Loubinoux I (2010) Wakefulness and loss of awareness: brain and brainstem interaction in the vegetative state. Neurology. https://doi.org/10.1212/WNL.0b013e3181cbcd96
Stefan S, Schorr B, Lopez-Rolon A, Kolassa IT, 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):848–862. https://doi.org/10.1007/s10548-018-0643-x
Strik WK, Fallgatter AJ, Brandeis D, Pascual-Marqui RD (1998) Three-dimensional tomography of event-related potentials during response inhibition: evidence for phasic frontal lobe activation. Electroencephalogr Clin Neurophysiology/evoked Potentials Section 108(4):406–413
Tait L, Tamagnini F, Stothart G, Barvas E, Monaldini C, Frusciante R, Volpini M, Guttmann S, Coulthard E, Brown JT, Kazanina N, Goodfellow M (2020) EEG microstate complexity for aiding early diagnosis of Alzheimer’s disease. Sci Rep 10(1):1–10. https://doi.org/10.1038/s41598-020-74790-7
Vanhaudenhuyse A, Noirhomme Q, Tshibanda LJF, Bruno MA, Boveroux P, Schnakers C, Soddu A, Perlbarg V, Ledoux D, Brichant JF, Moonen G, Maquet P, Greicius MD, Laureys S, Boly M (2010) Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients. Brain. https://doi.org/10.1093/brain/awp313
Wutzl B, Golaszewski SM, Leibnitz K, Langthaler PB, Kunz AB, Leis S, Schwenker K, Thomschewski A, Bergmann J, Trinka E (2021) Narrative review: quantitative EEG in disorders of consciousness. Brain Sci 11(6):697. https://doi.org/10.3390/brainsci11060697
Xie Q, Ni X, Yu R, Li Y, Huang R (2017) Chronic disorders of consciousness (Review). Exp Ther Med 14(2):1277–1283. https://doi.org/10.3892/etm.2017.4639
Acknowledgements
We would like to thank Tuba Aktürk for her support, Eray Sarıoğlu for arranging the figures and Zeynep Karakaya for improving the English language.
Author information
Authors and Affiliations
Contributions
ET, LH, contributed to conception and design of the study. ET and FA organized the database. ET performed the statistical analysis. ET wrote the first draft of the manuscript. ET and LH wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Handling Editor: Christoph Michel.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Toplutaş, E., Aydın, F. & Hanoğlu, L. EEG Microstate Analysis in Patients with Disorders of Consciousness and Its Clinical Significance. Brain Topogr 37, 377–387 (2024). https://doi.org/10.1007/s10548-023-00939-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10548-023-00939-y