Brain Relatively Inert Network: Taking Adult Attention Deficit Hyperactivity Disorder as an Example

Area of Science:

• Neuroscience
• Cognitive Science
• Psychiatric Research

Background:

• Resting-state functional MRI (rs-fMRI) is widely used in cognitive science and psychiatric research.
• Previous studies have primarily focused on brain activation areas, potentially overlooking information in inactivation areas.
• Understanding brain function and mental illness requires exploring both active and inactive brain networks.

Purpose of the Study:

• To introduce and investigate the role of the relatively inert network (RIN) in cognitive mechanisms and mental diseases.
• To use adult attention deficit hyperactivity disorder (ADHD) as a model to explore the RIN's significance.
• To determine if the RIN offers new insights beyond traditional activation networks.

Main Methods:

• Utilized group independent component analysis (GICA) and t-tests to identify the RIN.
• Calculated the time series associated with the RIN.
• Introduced RIN functional connectivity as a feature for machine learning classification.

Main Results:

• Observed alterations in both the RIN and the activation network (AN) in adult ADHD patients compared to healthy controls.
• Found greater activation changes in the right brain hemisphere compared to the left in adult ADHD.
• Achieved a 12% higher classification accuracy for adult ADHD using RIN features versus original functional connectivity features, validated on an independent dataset.

Conclusions:

• The RIN contains significant, previously overlooked information relevant to brain function and mental illness.
• The RIN provides a valuable new approach for studying inter-regional brain communication.
• This research offers a promising new tool for the diagnosis of mental illnesses like ADHD.