Biological detail and graph structure in network neuroscience.

Area of Science:

• Neuroscience
• Computational Neuroscience
• Network Science

Background:

• Brain activity is often modeled using complex networks, but these models involve approximations of biological detail and network structure.
• Current models face challenges in intrinsicality, universality, and functional meaningfulness.

Purpose of the Study:

• To discuss biological details that can improve network models of brain activity.
• To explore refining network structures to better represent neural properties.
• To understand the structure-dynamics-function relationship in the brain.

Main Methods:

• Conceptual analysis of existing brain network models.
• Discussion on incorporating biological detail into network structures.
• Examination of neurophysiological stylized facts.

Main Results:

• Generalised network structures share fundamental issues with standard models.
• Improved models require understanding how network structure performs specific functions.
• Better characterization of neurophysiological facts and the structure-dynamics-function relationship is needed.

Conclusions:

• Appropriate levels of biological and network detail are crucial for accurate brain modeling.
• Future research should focus on bridging network structure, neural dynamics, and function.
• Refining network models necessitates a deeper understanding of brain complexity.