A Complex Systems Perspective on Neuroimaging Studies of Behavior and Its Disorders

Area of Science:

• Neuroscience and Complexity Science
• Interdisciplinary applications of nonlinear dynamics and statistical mechanics to biological systems.

Background:

• Complex systems exhibit emergent behavior from nonlinear interactions.
• Neural systems and their disorders can be analyzed using complexity science principles.

Purpose of the Study:

• To illustrate complex system properties and their relevance to neuroimaging findings.
• To advocate for a complexity science-based methodology in neuroimaging research.

Main Methods:

• Review of fundamental mathematical concepts in complexity science.
• Evaluation of neuroimaging literature through the lens of complex systems theory.
• Integration of theoretical and experimental procedures from complexity science.

Main Results:

• Demonstration of how complex systems properties relate to brain structure and function.
• Identification of parallels between neuroimaging data and complex systems characteristics.
• Compilation of existing literature supporting a complexity-based approach.

Conclusions:

• A complex systems approach offers a robust framework for neuroimaging.
• Adopting this methodology alongside traditional approaches can enhance understanding of neural systems.
• Further integration of complexity science is recommended for future neuroimaging studies.