The analysis of EEG microstates offers a valuable approach for investigating large-scale brain networks and dynamics. Beyond the commonly reported "canonical microstates," prior literature has identified another distinct topography: the vertical topography (VT). This VT is characterized by a prominent straight line dividing positive and negative values, extending from the nasion to the inion. Notably, our own simultaneous EEG/fMRI and shielded cabin EEG data, collected from 77 participants, also revealed the presence of this topography. Based on our subsequent analyses of both human and phantom data, we conclude that VT partly represents artifacts arising from unspecified movements of the EEG cap and its metallic components. This conclusion is strongly supported by our evaluation of VT's spatiotemporal characteristics, derived from EEG recorded under diverse conditions. Specifically, we found a significant correlation between framewise displacement (obtained from human EEG/fMRI) and VT's temporal characteristics. Therefore, we advocate for a prudent interpretation of VT when it appears in data. Its mere existence as a resulting topography can impact the spatiotemporal parameters of other microstates and even distort the shapes of the other topographies.

1st Department of Neurology St Anne's University Hospital and Faculty of Medicine Masaryk University Brno Czech Republic

Brain and Mind Research Program CEITEC Masaryk University Brno Czech Republic

Zobrazit více v PubMed

Acharjee, P. P. , Phlypo R., Wu L., Calhoun V. D., and Adalı T.. 2015. “Independent Vector Analysis for Gradient Artifact Removal in Concurrent EEG‐fMRI Data.” IEEE Transactions on Biomedical Engineering 62: 1750–1758. 10.1109/TBME.2015.2403298. PubMed DOI

Agrawal, S. , Chinnadurai V., and Sharma R.. 2022. “Hemodynamic Functional Connectivity Optimization of Frequency EEG Microstates Enables Attention LSTM Framework to Classify Distinct Temporal Cortical Communications of Different Cognitive Tasks.” Brain Informatics 9: 25. 10.1186/s40708-022-00173-5. PubMed DOI PMC

Allen, P. J. , Josephs O., and Turner R.. 2000. “A Method for Removing Imaging Artifact From Continuous EEG Recorded During Functional MRI.” NeuroImage 12: 230–239. 10.1006/nimg.2000.0599. PubMed DOI

Allen, P. J. , Polizzi G., Krakow K., Fish D. R., and Lemieux L.. 1998. “Identification of EEG Events in the MR Scanner: The Problem of Pulse Artifact and a Method for Its Subtraction.” NeuroImage 8: 229–239. 10.1006/nimg.1998.0361. PubMed DOI

Bréchet, L. , Brunet D., Birot G., Gruetter R., Michel C. M., and Jorge J.. 2019. “Capturing the Spatiotemporal Dynamics of Self‐Generated, Task‐Initiated Thoughts With EEG and fMRI.” NeuroImage 194: 82–92. 10.1016/j.neuroimage.2019.03.029. PubMed DOI

Britz, J. , Van De Ville D., and Michel C.. 2010. “BOLD Correlates of EEG Topography Reveal Rapid Resting‐State Network Dynamics.” NeuroImage 52: 1162–1170. 10.1016/j.neuroimage.2010.02.052. PubMed DOI

Brunet, D. , Murray M. M., and Michel C. M.. 2011. “Spatiotemporal Analysis of Multichannel EEG: CARTOOL.” Computational Intelligence and Neuroscience 2011: e813870. 10.1155/2011/813870. PubMed DOI PMC

Bullock, M. , Jackson G. D., and Abbott D. F.. 2021. “Artifact Reduction in Simultaneous EEG‐fMRI: A Systematic Review of Methods and Contemporary Usage.” Frontiers in Neurology 12: 622719. 10.3389/fneur.2021.622719. PubMed DOI PMC

Custo, A. , Van De Ville D., Wells W. M., Tomescu M. I., Brunet D., and Michel C. M.. 2017. “Electroencephalographic Resting‐State Networks: Source Localization of Microstates.” Brain Connectivity 7: 671–682. 10.1089/brain.2016.0476. PubMed DOI PMC

D'Croz‐Baron, D. F. , Bréchet L., Baker M., and Karp T.. 2021. “Auditory and Visual Tasks Influence the Temporal Dynamics of EEG Microstates During Post‐Encoding Rest.” Brain Topography 34: 19–28. 10.1007/s10548-020-00802-4. PubMed DOI

Jabès, A. , Klencklen G., Ruggeri P., Michel C. M., Banta Lavenex P., and Lavenex P.. 2021. “Resting‐State EEG Microstates Parallel Age‐Related Differences in Allocentric Spatial Working Memory Performance.” Brain Topography 34: 442–460. 10.1007/s10548-021-00835-3. PubMed DOI PMC

Khanna, A. , Pascual‐Leone A., Michel C. M., and Farzan F.. 2015. “Microstates in Resting‐State EEG: Current Status and Future Directions.” Neuroscience & Biobehavioral Reviews 49: 105–113. 10.1016/j.neubiorev.2014.12.010. PubMed DOI PMC

Kleinert, T. , Koenig T., Nash K., and Wascher E.. 2024. “On the Reliability of the EEG Microstate Approach.” Brain Topography 37: 271–286. 10.1007/s10548-023-00982-9. PubMed DOI PMC

Kleinert, T. , Nash K., Leota J., Koenig T., Heinrichs M., and Schiller B.. 2022. “A Self‐Controlled Mind Is Reflected by Stable Mental Processing.” Psychological Science 33: 2123–2137. 10.1177/09567976221110136. PubMed DOI

Koenig, T. , Diezig S., Kalburgi S. N., et al. 2024. “EEG‐Meta‐Microstates: Towards a More Objective Use of Resting‐State EEG Microstate Findings Across Studies.” Brain Topography 37: 218–231. 10.1007/s10548-023-00993-6. PubMed DOI PMC

Lamoš, M. , Bočková M., Goldemundová S., Baláž M., Chrastina J., and Rektor I.. 2023. “The Effect of Deep Brain Stimulation in Parkinson's Disease Reflected in EEG Microstates.” npj Parkinson's Disease 9: 63. 10.1038/s41531-023-00508-x. PubMed DOI PMC

Lamoš, M. , Morávková I., Ondráček D., Bočková M., and Rektorová I.. 2021. “Altered Spatiotemporal Dynamics of the Resting Brain in Mild Cognitive Impairment With Lewy Bodies.” Movement Disorders 36: 2435–2440. 10.1002/mds.28741. PubMed DOI

Lehmann, D. , Ozaki H., and Pal I.. 1987. “EEG Alpha Map Series: Brain Micro‐States by Space‐Oriented Adaptive Segmentation.” Electroencephalography and Clinical Neurophysiology 67: 271–288. 10.1016/0013-4694(87)90025-3. PubMed DOI

Lehmann, D. , Strik W. K., Henggeler B., Koenig T., and Koukkou M.. 1998. “Brain Electric Microstates and Momentary Conscious Mind States as Building Blocks of Spontaneous Thinking: I. Visual Imagery and Abstract Thoughts.” International Journal of Psychophysiology 29: 1–11. 10.1016/S0167-8760(97)00098-6. PubMed DOI

Liu, J. , Xu J., Zou G., He Y., Zou Q., and Gao J.‐H.. 2020. “Reliability and Individual Specificity of EEG Microstate Characteristics.” Brain Topography 33: 438–449. 10.1007/s10548-020-00777-2. PubMed DOI

Michel, C. M. , and Brunet D.. 2019. “EEG Source Imaging: A Practical Review of the Analysis Steps.” Frontiers in Neurology 10: 325. PubMed PMC

Michel, C. M. , and Koenig T.. 2018. “EEG Microstates as a Tool for Studying the Temporal Dynamics of Whole‐Brain Neuronal Networks: A Review.” NeuroImage 180: 577–593. 10.1016/j.neuroimage.2017.11.062. PubMed DOI

Musso, F. , Brinkmeyer J., Mobascher A., Warbrick T., and Winterer G.. 2010. “Spontaneous Brain Activity and EEG Microstates. A Novel EEG/fMRI Analysis Approach to Explore Resting‐State Networks.” NeuroImage 52: 1149–1161. 10.1016/j.neuroimage.2010.01.093. PubMed DOI

Nierhaus, T. , Gundlach C., Goltz D., Thiel S. D., Pleger B., and Villringer A.. 2013. “Internal Ventilation System of MR Scanners Induces Specific EEG Artifact During Simultaneous EEG‐fMRI.” NeuroImage 74: 70–76. 10.1016/j.neuroimage.2013.02.016. PubMed DOI

Nishida, K. , Morishima Y., Yoshimura M., et al. 2013. “EEG Microstates Associated With Salience and Frontoparietal Networks in Frontotemporal Dementia, Schizophrenia and Alzheimer's Disease.” Clinical Neurophysiology 124: 1106–1114. 10.1016/j.clinph.2013.01.005. PubMed DOI

Pascual‐Marqui, R. D. , Michel C. M., and Lehmann D.. 1995. “Segmentation of Brain Electrical Activity Into Microstates: Model Estimation and Validation.” IEEE Transactions on Biomedical Engineering 42: 658–665. 10.1109/10.391164. PubMed DOI

Patel, A. X. , Kundu P., Rubinov M., et al. 2014. “A Wavelet Method for Modeling and Despiking Motion Artifacts From Resting‐State fMRI Time Series.” NeuroImage 95: 287–304. 10.1016/j.neuroimage.2014.03.012. PubMed DOI PMC

Power, J. D. , Barnes K. A., Snyder A. Z., Schlaggar B. L., and Petersen S. E.. 2012. “Spurious but Systematic Correlations in Functional Connectivity MRI Networks Arise From Subject Motion.” NeuroImage 59: 2142–2154. 10.1016/j.neuroimage.2011.10.018. PubMed DOI PMC

Rajkumar, R. , Farrher E., Mauler J., et al. 2021. “Comparison of EEG Microstates With Resting State fMRI and FDG‐PET Measures in the Default Mode Network via Simultaneously Recorded Trimodal (PET/MR/EEG) Data.” Human Brain Mapping 42: 4122–4133. 10.1002/hbm.24429. PubMed DOI PMC

Rothlübbers, S. , Relvas V., Leal A., Murta T., Lemieux L., and Figueiredo P.. 2015. “Characterisation and Reduction of the EEG Artefact Caused by the Helium Cooling Pump in the MR Environment: Validation in Epilepsy Patient Data.” Brain Topography 28: 208–220. 10.1007/s10548-014-0408-0. PubMed DOI

Schiller, B. , Sperl M. F. J., Kleinert T., Nash K., and Gianotti L. R. R.. 2024. “EEG Microstates in Social and Affective Neuroscience.” Brain Topography 37: 479–495. 10.1007/s10548-023-00987-4. PubMed DOI PMC

Schwab, S. , Koenig T., Morishima Y., Dierks T., Federspiel A., and Jann K.. 2015. “Discovering Frequency Sensitive Thalamic Nuclei From EEG Microstate Informed Resting State fMRI.” NeuroImage 118: 368–375. 10.1016/j.neuroimage.2015.06.001. PubMed DOI

Steyrl, D. , and Müller‐Putz G.. 2018. “Artifacts in EEG of Simultaneous EEG‐fMRI: Pulse Artifact Remainders in the Gradient Artifact Template Are a Source of Artifact Residuals After Average Artifact Subtraction.” Journal of Neural Engineering 16: 16011. 10.1088/1741-2552/aaec42. PubMed DOI

Sverak, T. , Obdrzalkova M., Mayerova M., Lamos M., and Ustohal L.. 2021. “EEG Microstates Changes in Schizophrenia Patients With Negative Symptoms After Accelerated Repetitive Transcranial Magnetic Stimulation.” Brain Stimulation 14: 1686. 10.1016/j.brs.2021.10.313. DOI

Tarailis, P. , Koenig T., Michel C. M., and Griškova‐Bulanova I.. 2024. “The Functional Aspects of Resting EEG Microstates: A Systematic Review.” Brain Topography 37: 181–217. 10.1007/s10548-023-00958-9. PubMed DOI

Thiele, J. A. , Richter A., and Hilger K.. 2023. “Multimodal Brain Signal Complexity Predicts Human Intelligence.” eNeuro 10: 345–2022. 10.1523/ENEURO.0345-22.2022. PubMed DOI PMC

Warbrick, T. 2022. “Simultaneous EEG‐fMRI: What Have we Learned and What Does the Future Hold?” Sensors (Basel) 22: 2262. 10.3390/s22062262. PubMed DOI PMC

Xu, J. , Pan Y., Zhou S., et al. 2020. “EEG Microstates Are Correlated With Brain Functional Networks During Slow‐Wave Sleep.” NeuroImage 215: 116786. 10.1016/j.neuroimage.2020.116786. PubMed DOI

Yuan, H. , Zotev V., Phillips R., Drevets W. C., and Bodurka J.. 2012. “Spatiotemporal Dynamics of the Brain at Rest — Exploring EEG Microstates as Electrophysiological Signatures of BOLD Resting State Networks.” NeuroImage 60: 2062–2072. 10.1016/j.neuroimage.2012.02.031. PubMed DOI

Zanesco, A. P. 2023. “Normative Temporal Dynamics of Resting EEG Microstates.” Brain Topography 37: 243–264. 10.1007/s10548-023-01004-4. PubMed DOI

Zanesco, A. P. , King B. G., Skwara A. C., and Saron C. D.. 2020. “Within and Between‐Person Correlates of the Temporal Dynamics of Resting EEG Microstates.” NeuroImage 211: 116631. 10.1016/j.neuroimage.2020.116631. PubMed DOI

Zappasodi, F. , Perrucci M. G., Saggino A., et al. 2019. “EEG Microstates Distinguish Between Cognitive Components of Fluid Reasoning.” NeuroImage 189: 560–573. 10.1016/j.neuroimage.2019.01.067. PubMed DOI