Temporal and spatial variability of large-scale dynamic brain networks in ASD

Area of Science:

• Neuroscience
• Developmental Neuroscience
• Biomarkers

Background:

• Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by social-cognitive deficits.
• Altered brain functional connectivity (FC) is documented in ASD, suggesting potential diagnostic biomarkers.
• The dynamic, spatiotemporal variability of functional connectivity networks in ASD is not well understood.

Purpose of the Study:

• To investigate temporal and spatial variability in dynamic functional connectivity networks (dFCNs) in individuals with ASD.
• To identify distinct dFCN patterns associated with ASD core symptoms.
• To explore the utility of dFCN spatiotemporal features as biomarkers for ASD diagnosis.

Main Methods:

• Employed fuzzy entropy to quantify temporal and spatial variability of dFCNs.
• Conducted comparative analysis between individuals with ASD and healthy controls (HCs).
• Correlated dFCN variability patterns with ASD clinical symptom severity.

Main Results:

• Individuals with ASD exhibited increased temporal variability in sensorimotor, subcortical, and cerebellar networks compared to HCs.
• Increased spatial variability was observed in visual, limbic, subcortical, and cerebellar networks in ASD.
• Spatiotemporal dFCN variability correlated significantly with ASD symptom severity.

Conclusions:

• Dynamic functional connectivity networks display unique spatiotemporal variability patterns in ASD.
• These variability features are associated with clinical symptoms and hold potential as diagnostic biomarkers.
• Integrated spatiotemporal dFCN analysis offers a promising avenue for enhancing ASD diagnostic accuracy.