Robust dynamic brain coactivation states estimated in individuals.

Area of Science:

• Neuroscience
• Cognitive Science
• Network Science

Background:

• Brain functional connectivity is increasingly recognized as dynamic, not static.
• Reliable methods are needed to capture transient, individual brain network interactions.
• Understanding dynamic brain states is crucial for both basic and clinical research.

Purpose of the Study:

• To introduce and validate an individualized, network-based dynamic analysis technique for brain states.
• To assess the reliability of detecting subject-specific brain states during rest and cognitive tasks.
• To investigate hemispheric asymmetries and phenotypic influences (handedness, gender) on brain network dynamics.

Main Methods:

• Development of an individualized network-based dynamic analysis technique.
• Assessment of within-subject reliability during resting-state and a language task.
• Analysis of brain state asymmetries and influence of handedness and gender.
• Longitudinal assessment in patients with subcortical stroke.

Main Results:

• The developed technique reliably detects subject-specific brain states.
• A right-lateralized brain state was identified, more prevalent in men and right-handed individuals.
• Longitudinal changes in brain states were observed in stroke patients over 6 months.

Conclusions:

• The individualized dynamic analysis technique reliably quantifies subject-specific brain states.
• Phenotypic factors like gender and handedness influence brain network dynamics.
• This approach holds promise for advancing basic neuroscience and clinical applications, including monitoring stroke recovery.