Network neuroscience

Network neuroscience is an approach to understanding the structure and function of the human brain through an approach of network science, through the paradigm of graph theory.[1]

Multiple scales of analysis for the brain

Nanoscale

Mircoscale

Mesoscale
  • Mesoscale - micrometer to millimeter scale.[2]

Macroscale

Modelling brain networks as graphs

Any network can be modelled as a graph of nodes connected by edges.[2]

  • Nodes represent fundamental processing units. Nodes are recommended to be:[2]
    • Spatially constrained.
    • Intrinsically homogenous.
    • Extrinically distinct.
  • Edges represent the interaction between nodes
gollark: I've said it repeatedly and it continues to be annoying: measuring neglected experiments' ToD. The low-precision timer makes them harder, via tediousness, not any actual fun mechanics.
gollark: Bad Idea #3783: genetic diseases from inbreeding.
gollark: Bad idea #1959: a breed with dimorphic eggs but monomorphic anything else.
gollark: Especially the AP times.
gollark: The AP works in mysterious ways.

See also

References
  1. Bassett, Danielle S; Sporns, Olaf (2017-02-23). "Network neuroscience". Nature Neuroscience. 20 (3): 353–364. doi:10.1038/nn.4502. ISSN 1097-6256. PMC 5485642. PMID 28230844.
  2. Alex Fornito. "An Introduction to Network Neuroscience: How to build, model, and analyse connectomes - 0800-10:00 | OHBM". pathlms.com. Retrieved 2020-03-11.


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