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Summary

Brain network models require better biological detail and refined structures to understand function. Integrating neurophysiology and network properties is key for accurate brain activity representation.

Keywords:
brain dynamicsbrain topologyfunctional networkshypergraphsintrinsical propertiesmultilayer networksmultiplex networksrenormalisation group

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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.