Aberrant dynamic functional network connectivity in type 2 diabetes mellitus individuals

Area of Science:

• Neuroscience
• Medical Imaging
• Systems Biology

Background:

• Type 2 Diabetes Mellitus (T2DM) is increasingly linked to cognitive impairment.
• Previous research focused on static functional connectivity, limiting understanding of dynamic brain alterations.
• Understanding the neurobiological mechanisms of cognitive deficits in T2DM is crucial.

Purpose of the Study:

• To investigate dynamic alterations in brain functional networks in individuals with T2DM.
• To characterize time-varying connectivity properties and recurring brain states.
• To explore the relationship between these dynamic changes and cognitive performance.

Main Methods:

• Utilized group independent component analysis (GICA) and sliding-window analysis.
• Applied k-means clustering to identify recurring brain states.
• Analyzed fraction time (FT) and mean dwell time (MDT) of brain states.
• Correlated network connectivity metrics with Montreal Cognitive Assessment (MoCA) scores.

Main Results:

• Identified significant differences in FT and MDT between T2DM and control groups.
• Observed a negative correlation between MoCA scores and FT/MDT, indicating poorer cognition with altered state dynamics.
• Found decreased inter-network and increased intra-network connectivity for Default Mode Network (DMN) and Task-Positive Network (TPN) in T2DM.
• Detected alterations in the Precuneus Network (PCUN) and enhanced connectivity between the Salience Network (SN) and TPN.

Conclusions:

• T2DM is associated with significant alterations in the dynamic properties of large-scale brain networks.
• These dynamic changes in brain states and network connectivity are linked to cognitive impairment in T2DM.
• The findings provide insights into the neurobiological underpinnings of cognitive deficits in T2DM, highlighting the importance of dynamic connectivity analysis.