MEG Microstates: An Investigation of Underlying Brain Sources and Potential Neurophysiological Processes.
Magnetoencephalography
Mismatch negativity
Occipital alpha activity
Resting-state microstates
Source-reconstructed brain activation
Journal
Brain topography
ISSN: 1573-6792
Titre abrégé: Brain Topogr
Pays: United States
ID NLM: 8903034
Informations de publication
Date de publication:
08 Aug 2024
08 Aug 2024
Historique:
received:
19
03
2024
accepted:
22
07
2024
medline:
8
8
2024
pubmed:
8
8
2024
entrez:
8
8
2024
Statut:
aheadofprint
Résumé
Microstates are transient scalp configurations of brain activity measured by electroencephalography (EEG). The application of microstate analysis in magnetoencephalography (MEG) data remains challenging. In one MEG dataset (N = 113), we aimed to identify MEG microstates at rest, explore their brain sources, and relate them to changes in brain activity during open-eyes (ROE) or closed-eyes resting state (RCE) and an auditory Mismatch Negativity (MMN) task. In another dataset of simultaneously recorded EEG-MEG data (N = 21), we investigated the association between MEG and EEG microstates. Six MEG microstates (mMS) provided the best clustering of resting-state activity, each linked to different brain sources: mMS 1-2: left/right occipito-parietal; mMS 3: fronto-temporal; mMS 4: centro-medial; mMS 5-6: left/right fronto-parietal. Increases in occipital alpha power in RCE relative to ROE correlated with greater mMS 1-2 time coverage (τ
Identifiants
pubmed: 39115626
doi: 10.1007/s10548-024-01073-z
pii: 10.1007/s10548-024-01073-z
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. The Author(s).
Références
Adrian ED, Mathews BHC (1934) The Berger rhythm: potential changes from the occipital lobe in man. Brain 57:355–385. https://doi.org/10.1093/brain/awp324
doi: 10.1093/brain/awp324
Antonova E, Holding M, Suen HC, Sumich A, Maex R, Nehaniv C (2022) EEG microstates: functional significance and short-term test-retest reliability. Neuroimage: Rep 2(2):100089. https://doi.org/10.1016/j.ynirp.2022.100089
doi: 10.1016/j.ynirp.2022.100089
Berger H (1929) Ueber das Elektroenzephalogramm des Menschen. Archives Psychiatry 87:527–570. https://doi.org/10.1007/BF01797193
doi: 10.1007/BF01797193
Biswal B, Zerrin Yetkin F, Haughton VM, Hyde JS (1995) Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 34(4):537–541. https://doi.org/10.1002/mrm.1910340409
doi: 10.1002/mrm.1910340409
pubmed: 8524021
Bréchet L, Brunet D, Birot G, Gruetter R, Michel CM, Jorge J (2019) Capturing the spatiotemporal dynamics of self-generated, task-initiated thoughts with EEG and fMRI. NeuroImage 194:82–92. https://doi.org/10.1016/j.neuroimage.2019.03.029
doi: 10.1016/j.neuroimage.2019.03.029
pubmed: 30902640
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
doi: 10.1016/j.neuroimage.2010.02.052
pubmed: 20188188
Brunet D, Murray MM, Michel CM (2011) Spatiotemporal analysis of multichannel EEG: CARTOOL. Comput Intell Neurosci 2011:1–15. https://doi.org/10.1155/2011/813870
Coquelet N, De Tiège X, Roshchupkina L, Peigneux P, Goldman S, Woolrich M, Wens V (2022) Microstates and power envelope hidden Markov modeling probe bursting brain activity at different timescales. NeuroImage 247:118850. https://doi.org/10.1016/j.neuroimage.2021.118850
doi: 10.1016/j.neuroimage.2021.118850
pubmed: 34954027
Corsi M-C (2023) Electroencephalography and Magnetoencephalography. In: Colliot O (ed) Machine learning for brain disorders. Humana, Totowa (New Jersey), pp 285–312
doi: 10.1007/978-1-0716-3195-9_9
Croce P, Quercia A, Costa S, Zappasodi F (2020) EEG microstates associated with intra-and inter-subject alpha variability. Sci Rep 10(1):2469. https://doi.org/10.1038/s41598-020-58787-w
doi: 10.1038/s41598-020-58787-w
pubmed: 32051420
pmcid: 7015936
Cui R, Jiang J, Zeng L, Jiang L, Xia Z, Dong L, Yao D (2021) Action video gaming experience related to altered resting-state EEG temporal and spatial complexity. Front Hum Neurosci 15:640329. https://doi.org/10.3389/fnhum.2021.640329
doi: 10.3389/fnhum.2021.640329
pubmed: 34267631
pmcid: 8275975
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. https://doi.org/10.1089/brain.2016.0476
doi: 10.1089/brain.2016.0476
pubmed: 28938855
pmcid: 5736178
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):43–56. https://doi.org/10.1038/nrn2961
doi: 10.1038/nrn2961
pubmed: 21170073
Destrieux C, Fischl B, Dale A, Halgren E (2010) Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. NeuroImage 53(1):1–15. https://doi.org/10.1016/j.neuroimage.2010.06.010
doi: 10.1016/j.neuroimage.2010.06.010
pubmed: 20547229
Diaz BA, Van Der Sluis S, Moens S, Benjamins JS, Migliorati F, Stoffers D, Linkenkaer-Hansen K (2013) The amsterdam resting-state questionnaire reveals multiple phenotypes of resting-state cognition. Front Hum Neurosci 7:446. https://doi.org/10.3389/fnhum.2013.00446
doi: 10.3389/fnhum.2013.00446
pubmed: 23964225
pmcid: 3737475
Diaz BA, Van Der Sluis S, Benjamins JS, Stoffers D, Hardstone R, Mansvelder HD, Linkenkaer-Hansen K (2014) The ARSQ 2.0 reveals age and personality effects on mind-wandering experiences. Front Psychol 5:271. https://doi.org/10.3389/fpsyg.2014.00271
doi: 10.3389/fpsyg.2014.00271
pubmed: 24772097
pmcid: 3982068
First MB, Skodol AE, Bender DS, Oldham JM (2017) User’s guide for the Structured Clinical Interview for the DSM-5
Garcés P, López-Sanz D, Maestú F, Pereda E (2017) Choice of magnetometers and gradiometers after signal space separation. Sensors 17(12):2926. https://doi.org/10.3390/s17122926
doi: 10.3390/s17122926
pubmed: 29258189
pmcid: 5751446
Hedrich T, Pellegrino G, Kobayashi E, Lina JM, Grova C (2017) Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG. NeuroImage 157:531–544. https://doi.org/10.1016/j.neuroimage.2017.06.022
doi: 10.1016/j.neuroimage.2017.06.022
pubmed: 28619655
Hohaia W, Saurels BW, Johnston A, Yarrow K, Arnold DH (2022) Occipital alpha-band brain waves when the eyes are closed are shaped by ongoing visual processes. Sci Rep 12(1):1194. https://doi.org/10.1038/s41598-022-05289-6
doi: 10.1038/s41598-022-05289-6
pubmed: 35075196
pmcid: 8786963
Jabès A, Klencklen G, Ruggeri P, Michel CM, Lavenex B, P., Lavenex P (2021) Resting-state EEG microstates parallel age‐related differences in allocentric spatial working memory performance. Brain Topogr 34:442–460. https://doi.org/10.1007/s10548-021-00835-3
doi: 10.1007/s10548-021-00835-3
pubmed: 33871737
pmcid: 8195770
Jawinski P, Markett S, Sander C, Huang J, Ulke C, Hegerl U, Hensch T (2021) The big five personality traits and brain arousal in the resting state. Brain Sci 11(10):1272. https://doi.org/10.3390/brainsci11101272
doi: 10.3390/brainsci11101272
pubmed: 34679337
pmcid: 8533901
Ke M, Li J, Wang L (2021) Alteration in resting-state EEG microstates following 24 hours of total sleep deprivation in healthy young male subjects. Front Hum Neurosci 15:636252. https://doi.org/10.3389/fnhum.2021.636252
doi: 10.3389/fnhum.2021.636252
pubmed: 33912019
pmcid: 8075097
Khanna A, Pascual-Leone A, Michel CM, Farzan F (2015) Microstates in resting-state EEG: current status and future directions. Neurosci Biobehavioral Reviews 49:105–113. https://doi.org/10.1016/j.neubiorev.2014.12.010
doi: 10.1016/j.neubiorev.2014.12.010
Korn U, Krylova M, Heck KL, Häußinger FB, Stark RS, Alizadeh S, Munk MH (2021) EEG-Microstates reflect auditory distraction after attentive audiovisual perception recruitment of cognitive control networks. Front Syst Neurosci 15:751226. https://doi.org/10.3389/fnsys.2021.751226
doi: 10.3389/fnsys.2021.751226
pubmed: 34955767
pmcid: 8696261
Mazziotta J, Toga A, Evans A, Fox P, Lancaster J, Zilles K, Mazoyer B (2001) A probabilistic atlas and reference system for the human brain: international consortium for brain mapping (ICBM). Philosophical Trans Royal Soc Lond Ser B: Biol Sci 356(1412):1293–1322. https://doi.org/10.1098/rstb.2001.0915
doi: 10.1098/rstb.2001.0915
Michel CM, Brunet D (2019) EEG source imaging: a practical review of the analysis steps. Front Neurol 10:325. https://doi.org/10.3389/fneur.2019.00325
doi: 10.3389/fneur.2019.00325
pubmed: 31019487
pmcid: 6458265
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
doi: 10.1016/j.neuroimage.2017.11.062
pubmed: 29196270
Milz P, Faber PL, Lehmann D, Koenig T, Kochi K, Pascual-Marqui RD (2016) The functional significance of EEG microstates—associations with modalities of thinking. NeuroImage 125:643–656. https://doi.org/10.1016/j.neuroimage.2015.08.023
doi: 10.1016/j.neuroimage.2015.08.023
pubmed: 26285079
Näätänen R, Paavilainen P, Rinne T, Alho K (2007) The mismatch negativity (MMN) in basic research of central auditory processing: a review. Clin Neurophysiol 118(12):2544–2590. https://doi.org/10.1016/j.clinph.2007.04.026
doi: 10.1016/j.clinph.2007.04.026
pubmed: 17931964
Oostenveld R, Fries P, Maris E, Schoffelen JM (2011) FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput Intell Neurosci 2011:1–9. https://doi.org/10.1155/2011/156869
Pascual-Marqui RD (2002) Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods Find Exp Clin Pharmacol 24(Suppl D):5–12
pubmed: 12575463
Pascual-Marqui RD, Lehmann D, Faber P, Milz P, Kochi K, Yoshimura M, Kinoshita T (2014) The resting microstate networks (RMN): cortical distributions, dynamics, and frequency specific information flow. arXiv preprint arXiv:1411.1949
Schaefer A, Kong R, Gordon EM, Laumann TO, Zuo XN, Holmes AJ, Yeo BT (2018) Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI. Cereb Cortex 28(9):3095–3114. https://doi.org/10.1093/cercor/bhx179
doi: 10.1093/cercor/bhx179
pubmed: 28981612
Seitzman BA, Abell M, Bartley SC, Erickson MA, Bolbecker AR, Hetrick WP (2017) Cognitive manipulation of brain electric microstates. NeuroImage 146:533–543. https://doi.org/10.1016/j.neuroimage.2016.10.002
doi: 10.1016/j.neuroimage.2016.10.002
pubmed: 27742598
Seitzman BA, Snyder AZ, Leuthardt EC, Shimony JS (2019) The state of resting state networks. Top Magn Reson Imaging: TMRI 28(4):189. https://doi.org/10.1097/rmr.0000000000000214
doi: 10.1097/rmr.0000000000000214
pubmed: 31385898
Singh SP (2014) Magnetoencephalography: basic principles. Ann Indian Acad Neurol 17(Suppl 1):S107–S112. https://doi.org/10.4103/0972-2327.128676
doi: 10.4103/0972-2327.128676
pubmed: 24791076
pmcid: 4001219
Tadel F, Baillet S, Mosher JC, Pantazis D, Leahy RM (2011) Brainstorm: a user-friendly application for MEG/EEG analysis. Comput Intell Neurosci 2011:1–13. https://doi.org/10.1155/2011/879716
Tait L, Zhang J (2022) MEG cortical microstates: spatiotemporal characteristics, dynamic functional connectivity and stimulus-evoked responses. NeuroImage 251:119006. https://doi.org/10.1016/j.neuroimage.2022.119006
doi: 10.1016/j.neuroimage.2022.119006
pubmed: 35181551
Tarailis P, Šimkutė D, Koenig T, Griškova-Bulanova I (2021) Relationship between spatiotemporal dynamics of the brain at rest and self-reported spontaneous thoughts: an EEG microstate approach. J Personalized Med 11(11):1216. https://doi.org/10.3390/jpm11111216
doi: 10.3390/jpm11111216
Tarailis P, Koenig T, Michel CM, Griškova-Bulanova I (2024) The functional aspects of resting EEG microstates: a systematic review. Brain Topogr 37(2):181–217. https://doi.org/10.1007/s10548-023-00958-9
Taulu S, Simola J (2006) Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements. Phys Med Biol 51(7):1759. https://doi.org/10.1088/0031-9155/51/7/008
doi: 10.1088/0031-9155/51/7/008
pubmed: 16552102
Tomescu MI, Rihs TA, Rochas V, Hardmeier M, Britz J, Allali G, Michel CM (2018) From swing to cane: sex differences of EEG resting-state temporal patterns during maturation and aging. Dev Cogn Neurosci 31:58–66. https://doi.org/10.1016/j.dcn.2018.04.011
doi: 10.1016/j.dcn.2018.04.011
pubmed: 29742488
pmcid: 6969216
Valt C, Quarto T, Tavella A, Romanelli F, Fazio L, Arcara G, Bertolino A (2023) Reduced magnetic mismatch negativity: a shared deficit in psychosis and related risk. Psychol Med 53(13):6037–6045. https://doi.org/10.1017/s003329172200321x
doi: 10.1017/s003329172200321x
pubmed: 36321391
Vrba J, Robinson SE (2001) Signal Processing in Magnetoencephalography. Methods 25(2):249–271. https://doi.org/10.1006/METH.2001.1238
doi: 10.1006/METH.2001.1238
pubmed: 11812209
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
doi: 10.1016/j.neuroimage.2020.116631
pubmed: 32062082
Zappasodi F, Perrucci MG, Saggino A, Croce P, Mercuri P, Romanelli R, Ebisch SJ (2019) EEG microstates distinguish between cognitive components of fluid reasoning. NeuroImage 189:560–573. https://doi.org/10.1016/j.neuroimage.2019.01.067
doi: 10.1016/j.neuroimage.2019.01.067
pubmed: 30710677