Identification of high-functioning autism spectrum disorders based on gray-white matter functional network...

Area of Science:

• Neuroscience
• Medical Imaging
• Autism Spectrum Disorder Research

Background:

• Functional connectivity research in autism spectrum disorder (ASD) has historically focused less on gray-white matter interactions.
• Understanding the interplay between gray and white matter is crucial for a comprehensive view of brain function in ASD.

Purpose of the Study:

• To investigate gray-white matter functional connectivity in individuals with high-functioning ASD.
• To develop and apply an innovative nested cross-validation method integrating gray-white matter connectivity with an F-Score algorithm for ASD classification.
• To identify specific abnormal connectivity patterns and their correlation with clinical symptoms in ASD.

Main Methods:

• A novel nested cross-validation approach was employed, integrating gray-white matter functional connectivity analysis.
• Functional magnetic resonance imaging (fMRI) data from individuals with high-functioning ASD and healthy controls were analyzed.
• An F-Score algorithm was utilized to calculate correlations based on signals from gray and white matter brain region templates.

Main Results:

• The developed method achieved a classification accuracy of 72.94% for distinguishing individuals with ASD from healthy controls.
• Abnormal functional connectivity was identified, notably involving regions such as the left anterior prefrontal cortex, right superior corona radiata, left retrosplenial cortex, and left ventral anterior cingulate cortex.
• These identified abnormal connections were found to be significantly associated with social impairments and restrictive, repetitive behaviors characteristic of ASD.

Conclusions:

• This study introduces a novel perspective on gray-white matter functional connectivity for understanding and potentially diagnosing ASD.
• The findings highlight specific neural pathways implicated in ASD, offering targets for future research and clinical applications.
• The integrated approach provides a more nuanced understanding of the neural underpinnings of ASD symptoms.