Literature DB >> 17587166

Classes of multichannel EEG microstates in light and deep hypnotic conditions.

Hitoshi Katayama1, Lorena R R Gianotti, Toshiaki Isotani, Pascal L Faber, Kyohei Sasada, Toshihiko Kinoshita, Dietrich Lehmann.   

Abstract

The study assessed the brain electric mechanisms of light and deep hypnotic conditions in the framework of EEG temporal microstates. Multichannel EEG of healthy volunteers during initial resting, light hypnosis, deep hypnosis, and eventual recovery was analyzed into temporal EEG microstates of four classes. Microstates are defined by the spatial configuration of their potential distribution maps ([Symbol: see text]potential landscapes') on the head surface. Because different potential landscapes must have been generated by different active neural assemblies, it is reasonable to assume that they also incorporate different brain functions. The observed four microstate classes were very similar to the four standard microstate classes A, B, C, D [Koenig, T. et al. Neuroimage, 2002;16: 41-8] and were labeled correspondingly. We expected a progression of microstate characteristics from initial resting to light to deep hypnosis. But, all three microstate parameters (duration, occurrence/second and %time coverage) yielded values for initial resting and final recovery that were between those of the two hypnotic conditions of light and deep hypnosis. Microstates of the classes B and D showed decreased duration, occurrence/second and %time coverage in deep hypnosis compared to light hypnosis; this was contrary to microstates of classes A and C which showed increased values of all three parameters. Reviewing the available information about microstates in other conditions, the changes from resting to light hypnosis in certain respects are reminiscent of changes to meditation states, and changes to deep hypnosis of those in schizophrenic states.

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Year:  2007        PMID: 17587166     DOI: 10.1007/s10548-007-0024-3

Source DB:  PubMed          Journal:  Brain Topogr        ISSN: 0896-0267            Impact factor:   3.020


  21 in total

1.  EEG microstate sequences in healthy humans at rest reveal scale-free dynamics.

Authors:  Dimitri Van de Ville; Juliane Britz; Christoph M Michel
Journal:  Proc Natl Acad Sci U S A       Date:  2010-10-04       Impact factor: 11.205

2.  EEG microstates during different phases of Transcendental Meditation practice.

Authors:  Pascal L Faber; Frederick Travis; Patricia Milz; Niyazi Parim
Journal:  Cogn Process       Date:  2017-04-27

3.  Electroencephalographic Resting-State Networks: Source Localization of Microstates.

Authors:  Anna Custo; Dimitri Van De Ville; William M Wells; Miralena I Tomescu; Denis Brunet; Christoph M Michel
Journal:  Brain Connect       Date:  2017-11-17

Review 4.  Microstates in resting-state EEG: current status and future directions.

Authors:  Arjun Khanna; Alvaro Pascual-Leone; Christoph M Michel; Faranak Farzan
Journal:  Neurosci Biobehav Rev       Date:  2014-12-17       Impact factor: 8.989

5.  Reconfiguration of Electroencephalography Microstate Networks after Breath-Focused, Digital Meditation Training.

Authors:  Lucie Bréchet; David A Ziegler; Alexander J Simon; Denis Brunet; Adam Gazzaley; Christoph M Michel
Journal:  Brain Connect       Date:  2021-02-09

6.  Microstates in complex and dynamical environments: Unraveling situational awareness in critical helicopter landing maneuvers.

Authors:  Camila S Deolindo; Mauricio W Ribeiro; Maria A A de Aratanha; José R S Scarpari; Carlos H Q Forster; Roberto G A da Silva; Birajara S Machado; Edson Amaro Junior; Thomas König; Elisa H Kozasa
Journal:  Hum Brain Mapp       Date:  2021-05-04       Impact factor: 5.038

7.  Altered Brain Microstate Dynamics in Adolescents with Narcolepsy.

Authors:  Natasha M Drissi; Attila Szakács; Suzanne T Witt; Anna Wretman; Martin Ulander; Henriettae Ståhlbrandt; Niklas Darin; Tove Hallböök; Anne-Marie Landtblom; Maria Engström
Journal:  Front Hum Neurosci       Date:  2016-08-03       Impact factor: 3.169

8.  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.

Authors:  Ravichandran Rajkumar; Ezequiel Farrher; Jörg Mauler; Praveen Sripad; Cláudia Régio Brambilla; Elena Rota Kops; Jürgen Scheins; Jürgen Dammers; Christoph Lerche; Karl-Josef Langen; Hans Herzog; Bharat Biswal; N Jon Shah; Irene Neuner
Journal:  Hum Brain Mapp       Date:  2018-10-27       Impact factor: 5.038

9.  15 Years of Microstate Research in Schizophrenia - Where Are We? A Meta-Analysis.

Authors:  Kathryn Rieger; Laura Diaz Hernandez; Anja Baenninger; Thomas Koenig
Journal:  Front Psychiatry       Date:  2016-02-26       Impact factor: 4.157

10.  Fluctuations of spontaneous EEG topographies predict disease state in relapsing-remitting multiple sclerosis.

Authors:  Markus Gschwind; Martin Hardmeier; Dimitri Van De Ville; Miralena I Tomescu; Iris-Katharina Penner; Yvonne Naegelin; Peter Fuhr; Christoph M Michel; Margitta Seeck
Journal:  Neuroimage Clin       Date:  2016-08-09       Impact factor: 4.881

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