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Related Concept Videos

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Bipolar disorder is a chronic mental health condition marked by significant mood fluctuations, including episodes of mania and depression. Elevated energy levels, heightened mood or irritability, impulsive behavior, reduced sleep needs, rapid speech, racing thoughts, inflated self-esteem, and distractibility characterize mania. Individuals with bipolar disorder often alternate between depressive and manic states, with periods of emotional stability lasting an average of six months to a year.
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Related Experiment Video

Updated: Apr 5, 2026

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
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Directed EEG microstate transitions during affective processing complement static microstate metrics in bipolar

Ronen Sosnik1, Arnaud Pouchon2, Antoine Bertrand2

  • 1Faculty of Electrical and Electronics Engineering, Holon Institute of Technology (HIT), Holon, Israel.

Neuroimage
|April 4, 2026
PubMed
Summary
This summary is machine-generated.

Task-evoked electroencephalographic (EEG) microstate syntax, focusing on brain state transitions, offers a dynamic view of affective processing. This approach reveals clearer group differences in brain activity compared to static microstate measures.

Keywords:
Affective processingBipolar disorderDirected transitionsEEG microstatesERPMicrostate syntaxNetwork dynamics

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Area of Science:

  • Neuroscience
  • Cognitive Neuroscience
  • Psychophysiology

Background:

  • Electroencephalography (EEG) microstates represent rapid, large-scale brain activity patterns.
  • Existing research often focuses on static microstate properties (duration, coverage).
  • The dynamic organization of microstate transitions ('microstate syntax') during cognitive tasks, especially affective processing, is less understood.

Purpose of the Study:

  • To operationalize and investigate task-evoked microstate syntax during affective processing.
  • To compare dynamic microstate syntax with static microstate metrics in healthy controls, individuals with bipolar disorder, and their unaffected siblings.
  • To identify group-specific deviations in microstate transition patterns within canonical event-related potential (ERP) windows.

Main Methods:

  • Analysis of stimulus-locked EEG data from three groups: healthy controls (n=15), bipolar disorder patients (n=44), and unaffected siblings (n=14).
  • Quantification of directed microstate transition deviations from independence within N200, P300, and Late Positive Potential (LPP) ERP windows.
  • Application of age-adjusted models and false-discovery-rate control for statistical analysis.

Main Results:

  • Static microstate metrics showed limited and pipeline-sensitive group effects.
  • Directed microstate transition structure revealed clearer, window-specific group deviations, particularly within the LPP window.
  • A modest association was found in the N200 window where increased early 'anchor' outflow correlated with faster responses on valenced trials, though this effect was small and sensitivity-dependent.

Conclusions:

  • Task-evoked microstate syntax provides a valuable dynamic descriptor of brain state switching during affective processing.
  • Dynamic microstate syntax captures information beyond static microstate measures, showing clearer group differences in this dataset.
  • Transition-based analyses demonstrated robustness to temporal smoothing and modest shifts in ERP windows, suggesting stability.