Neural networks in psychiatry

Area of Science:

• Neuroscience
• Psychiatry
• Network Science

Background:

• Numerous brain imaging studies over 30 years show structural and functional abnormalities in neuropsychiatric diseases.
• These changes often occur in multiple, discrete brain regions (cortical and subcortical).
• These regions are interconnected via long-distance fibers, forming complex brain networks.

Purpose of the Study:

• To introduce recent developments in neural network studies relevant to psychiatry.
• To highlight the application of complex network analysis, based on graph theory, to brain structure and function.
• To emphasize the shift from viewing localized brain changes as separate entities to understanding them as parts of an altered brain network.

Main Methods:

• Review of recent developments in neural network studies in psychiatry.
• Application of quantitative analysis of complex networks (graph theory) to brain imaging data.
• Reference to the 2013 special issue on Neural Networks in Psychiatry in European Neuropsychopharmacology.

Main Results:

• Brain structure and function exhibit characteristics of complex networks.
• Localized brain abnormalities in psychiatric disorders may represent components of a larger, altered brain network.
• Neural network approaches provide a new framework for understanding brain alterations in psychiatric conditions.

Conclusions:

• Viewing psychiatric disorders through the lens of brain networks offers a more integrated understanding.
• Neural network approaches in brain imaging hold significant potential for uncovering the causes of psychiatric disorders.
• This approach may lead to the development of novel preventive and therapeutic strategies for psychiatric conditions.