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@ARTICLE{Manasova:1034747,
      author       = {Manasova, Dragana and Sanz Perl, Yonatan and Bruno, Nicolas
                      Marcelo and Valente, Melanie and Rohaut, Benjamin and
                      Tagliazucchi, Enzo and Naccache, Lionel and Raimondo,
                      Federico and Sitt, Jacobo D.},
      title        = {{D}ynamics of {EEG} {M}icrostates {C}hange {A}cross the
                      {S}pectrum of {D}isorders of {C}onsciousness},
      reportid     = {FZJ-2024-07504},
      year         = {2024},
      abstract     = {As a response to the environment and internal signals,
                      brain networks reorganize on asub-second scale. To capture
                      this reorganization in patients with disorders
                      ofconsciousness and understand their residual brain
                      activity, we investigated thedynamics of
                      electroencephalography (EEG) microstates. We analyze EEG
                      microstatemarkers to quantify the periods of semi-stable
                      topographies and the large-scalecortical networks they may
                      reflect. To achieve this, EEG samples are clustered intofour
                      groups and then fit back into each time sample. We then
                      obtain a time series ofmaps with different frequencies of
                      occurrence and duration. One such occurrence of amap with a
                      given duration is called a microstate. The goal of this work
                      is to study thedynamics of these topographical patterns
                      across patients with disorders ofconsciousness. Using the
                      microstate time series, we calculate static and
                      dynamicmarkers. In contrast to the static, the dynamic
                      metrics depend on the specific temporalsequences of the
                      maps. The static measure Ratio of Total Time covered (RTT)
                      showsdifferences between healthy controls and patients,
                      however, no differences wereobserved between the groups of
                      patients. In contrast, some dynamic markers
                      captureinter-patient group differences. The dynamic markers
                      we investigated are MeanMicrostate Durations (MMD),
                      Microstate Duration Variances (MDV), MicrostateTransition
                      Matrices (MTM), and Entropy Production (EP). The MMD and
                      MDVdecrease with the state of consciousness, whereas the MTM
                      non-diagonal transitionsand EP increase. In other words, DoC
                      patients have slower and closer to
                      equilibrium(time-reversible) brain dynamics. In conclusion,
                      static and dynamic EEG microstatemetrics differ across
                      consciousness levels, with the latter capturing the
                      subtitlerdifferences between groups of patients with
                      disorders of consciousness.},
      cin          = {INM-7},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5252 - Brain Dysfunction and Plasticity (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5252},
      typ          = {PUB:(DE-HGF)25},
      doi          = {10.1101/2024.05.30.596582},
      url          = {https://juser.fz-juelich.de/record/1034747},
}