EEG Microstates are Not Associated with Psychotic Symptoms, Neurocognitive Domains or Psychosocial Functioning in Adolescents and Young Adults with Clinical High Risk for Psychosis.
Journal:
Brain topography
Published Date:
Oct 10, 2026
(2)
Abstract
EEG microstates are brief and discrete topographic patterns of electrical brain activity. Microstates last for 60-120 milliseconds, are thought to represent transient, quasi-stable neural networks, and traditionally four distinct classes (A-D) are distinguished. One of the core concepts of present neuroscience is that neuroimaging is able to capture meaningful networks of brain activity, which can be translated into specific cognitive functions. Following this idea, each microstate might correspond to specific core brain functions. Importantly, these cognitive functions are impaired in mental disorders. Clinical high-risk (CHR) refers to a state associated with an increased risk of developing psychosis. Previous research has demonstrated consistent microstate alterations in CHR individuals (especially in class D), as well as in psychosis. However, the neurobiological and functional meaning of microstate alterations in CHR populations is still elusive. Since the CHR state is associated with reduced neurocognition (e.g., processing speed, verbal memory, executive functions) in combination with specific clinical symptoms and impairments in psychosocial functioning, relationships between resting-state microstates and these domains were examined in a large cross-sectional cohort of CHR individuals (nā=ā100). Contrary to our expectations, no significant correlations were found for these clinical measures. The finding suggests that while microstate parameters may differ between CHR individuals and controls, these alterations do not seem to directly reflect the neurobiology of clinical symptoms or neurocognitive and psychosocial functions. EEG microstate deviations as candidate trait biomarker therefore require further investigation and validation in longitudinal studies to establish their stability and predictive value.
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