Spectral feature modeling with graph signal processing for brain connectivity in autism spectrum disorder

• Published in: Scientific reports Vol. 15; no. 1; pp. 22933 - 34
• Main Authors: Jabbar, Ayesha, Jianjun, Huang, Jabbar, Muhammad Kashif, ur Rehman, Khalil, Bilal, Anas
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 02.07.2025; Nature Portfolio
• Subjects: 631/61; 639/4077; Autism spectrum disorder; Autism Spectrum Disorder - diagnostic imaging; Autism Spectrum Disorder - physiopathology; Brain - diagnostic imaging; Brain - physiopathology; Brain connectivity analysis; Child; Connectome - methods; Electroencephalography; Female; Graph Fourier transform; Graph signal processing; Humanities and Social Sciences; Humans; Magnetic Resonance Imaging; Male; multidisciplinary; Principal Component Analysis; Science; Science (multidisciplinary); Signal Processing, Computer-Assisted; Spectral clustering; Support Vector Machine; Graph Fourier transform; Spectral clustering; Graph signal processing; Autism spectrum disorder; Brain connectivity analysis

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition associated with disrupted brain connectivity. Traditional graph-theoretical approaches have been widely employed to study ASD biomarkers; however, these methods are often limited to static topological measures and lack the capa...