Neuropsychiatric disorders, such as Alzheimer's disease, Huntington's disease, Parkinson’s disease, Major Depressive Disorder, Schizophrenia, Bipolar Disorder, and Autism Spectrum Disorder, are characterized by complex alterations in brain structure and function. These disorders often involve disruptions in the connectivity and communication between brain regions/networks, leading to cognitive, emotional, and behavioral impairments. Over the past two decades, advances in neuroimaging and network neuroscience have provided new tools to map, analyze, and model the brain as a complex network, offering insights into the neural mechanisms underlying these disorders.

Network neuroscience leverages the principles of graph theory and network science to study the brain as a multiscale, interconnected system. By modeling the brain as a network of nodes (e.g., brain regions) and edges (e.g., structural or functional connections), researchers can investigate how disruptions in network topology and dynamics contribute to the pathophysiology of neuropsychiatric disorders. This approach has led to the identification of key network properties, such as small-world architecture, modularity, and hub connectivity, which are often altered in these conditions.

Despite significant progress, our understanding of how network disruptions contribute to neuropsychiatric disorders remains incomplete. This Research Topic aims to address this gap by focusing on the development, validation, and application of novel network modeling methods to study neuropsychiatric disorders. We welcome contributions that explore, but are not limited to, the following areas:

a) Development of Novel Network Modeling Methods

b) Validation of Network Models

c) Applications of Network Models in Neuropsychiatric Disorders

d) Cross-Disorder Comparisons

e) Multiscale Network Modeling

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Network neuroscience in neuropsychiatric disorders