Lab 03

PSYC480

Harriet Grace

University of Canterbury

2024-04-23

EEG Microstates

  • Definition
  • Use
  • Re-processing

Microstates Definition

“EEG microstates are brief, recurring periods of stable brain activity that reflect the activation of large-scale neural networks. The temporal characteristics of these microstates, including their average duration, number of occurrences, and percentage contribution have been shown to serve as biomarkers of mental and neurological disorders” (Kleinert, Nash, et al. 2024).

Two major types

  • Resting EEG Microstates
  • ERP Microstates

The use of Microstates

“Recent publications demonstrate the potential of microstate research to contribute to a more sophisticated diagnosis, monitoring, prognosis, and prevention of mental disorders in clinical psychology and psychiatry. Microstate characteristics may serve as biomarkers of schizophrenia (da Cruz et al. 2020; de Bock et al. 2020), affective disorders (Al Zoubi et al. 2019; Damborská et al. 2019b; Murphy et al. 2020), anxiety disorders (Al Zoubi et al. 2019), ADHD (Férat et al. 2022a), and autism (D’Croz-Baron et al. 2019; Bochet et al. 2021). as mentioned in (Kleinert, Koenig, et al. 2024)”

Processing for Microstates analysis

EEG data processing (as described in the previous labs) has historically been recommended by many experts. However, recent research shows that the EEG data processing (or over-processing) could be counterproductive. Therefore, it is sensible to process the data to only the extent that is needed to obtain microstates that resemble the prototypical four to seven network types.

Processing continued….

To the best of my knowledge, it is important to use only the following processing steps:

  1. Add channel locations
  2. Filter 2-20 Hz
  3. Remove artefacts with ASR, but make sure to un-check the option Remove channel if it is flat for more than (seconds), see Figure 1.
  4. Reference to average and interpolate removed channels.

Processing continued….

Figure 1: Automatic artefact removal

Processing continued….

  1. From Tools -> Microstates -> Obtain Microstate Maps, use k-means method with a min of 4 and max of 5 maps, and set restarts to 20, see Figure 2.
  2. From Plots -> …
  3. Examine whether or not your obtained microstates resemble the prototypical four (or seven) network types (see Figure 3) (Nash et al. 2022).

Microstates menu

Figure 2

Typical MS Maps

Figure 3: Four prototypical microstates (Nash et al. 2022)

Obtaining microstates

  • Use Lab 3 demo dataset on Learn.
  • Conduct the necessary processing.

To submit

  • Use the the Lab 3 exercise dataset on Learn.
  • Conduct necessary processing.
  • Identify microstate maps

The END

Kleinert, Tobias, Thomas Koenig, Kyle Nash, and Edmund Wascher. 2024. “On the Reliability of the EEG Microstate Approach.” Brain Topography 37 (2): 271–86. https://doi.org/10.1007/s10548-023-00982-9.
Kleinert, Tobias, Kyle Nash, Thomas Koenig, and Edmund Wascher. 2024. “Normative Intercorrelations Between EEG Microstate Characteristics.” Brain Topography 37 (2): 265–69. https://doi.org/10.1007/s10548-023-00988-3.
Nash, Kyle, Tobias Kleinert, Josh Leota, Andy Scott, and Jeff Schimel. 2022. “Resting-State Networks of Believers and Non-Believers: An EEG Microstate Study.” Biological Psychology 169 (March): 108283. https://doi.org/10.1016/j.biopsycho.2022.108283.