"Unrest while Resting"? Brain entropy in autism spectrum disorder

Area of Science:

• Neuroscience
• Computational Biology
• Biomedical Engineering

Background:

• Biological systems display complex, nonlinear dynamics.
• Nonlinear signal processing, like sample entropy, offers novel methods to analyze brain connectivity.
• Altered brain connectivity is a hallmark of neurodevelopmental disorders such as autism spectrum disorder (ASD).

Purpose of the Study:

• To investigate differences in brain entropy using sample entropy in children with ASD compared to typically developing (TD) controls.
• To explore the relationship between brain entropy and ASD symptoms.
• To assess the utility of sample entropy as a biomarker for brain dysfunction in ASD.

Main Methods:

• Resting-state functional magnetic resonance imaging (fMRI) data from 45 high-functioning children with ASD and 45 TD children were analyzed.
• Data preprocessing was performed using the CONN toolbox.
• Sample entropy was calculated voxelwise and using region of interest (ROI) methods via the complexity toolbox.

Main Results:

• Children with ASD showed significantly increased sample entropy in the left angular gyrus, superior parietal lobule, and right inferior temporal gyrus.
• Reduced sample entropy was observed in the superior frontal gyrus of ASD participants compared to TD controls.
• Positive correlations were found between entropy in specific brain regions and ASD symptom severity.

Conclusions:

• Sample entropy analysis reveals significant differences in brain entropy patterns between children with ASD and TD controls.
• These findings suggest that sample entropy can serve as a valuable index of brain dysfunction in ASD.
• Optimal brain synchronization, reflected by entropy measures, is crucial for cognitive and behavioral functions in ASD.