Abstract Purpose of Review Over the last decade, evidence suggests that a combination of
behavioral and neuroimaging findings can help illuminate changes in functional …

Functional neuroimaging emerged with great promise and has provided fundamental
insights into the neurobiology of schizophrenia. However, it has faced challenges and …

Multimodal neuroimaging is an emerging field that leverages multiple sources of information
to diagnose specific brain disorders, especially when deep learning‐based AI algorithms …

The human brain has a complex, intricate functional architecture. While many studies
primarily emphasize pairwise interactions, delving into high-order associations is crucial for …

Brain disorders are often associated with changes in brain structure and function, where
functional changes may be due to underlying structural variations. Gray matter (GM) volume …

The human brain undergoes remarkable development with the first six postnatal months
witnessing the most dramatic structural and functional changes, making this period critical …

Neurodevelopmental disorders (NDDs), including ADHD and ASD, profoundly impact
children and adolescents. Leveraging Machine Learning (ML), Deep Learning (DeepL) on …

Psychotic disorders, such as schizophrenia and bipolar disorder, pose significant diagnostic
challenges with major implications on mental health. The measures of resting-state fMRI …

Converging evidence suggests that understanding the human brain requires more than just
examining pairwise functional brain interactions. The human brain is a complex, nonlinear …

Brain function can be modeled as the dynamic interactions between functional sources at
different spatial scales, and each spatial scale can contain its functional sources with unique …