Networks of the Brain

@article{Long2011NetworksOT,
  title={Networks of the Brain},
  author={Donlin M. Long},
  journal={Neurosurgery Quarterly},
  year={2011},
  volume={21},
  pages={144}
}
  • D. Long
  • Published 1 May 2011
  • Art
  • Neurosurgery Quarterly
Models of Network Growth All networks, whether they are social, technological, or biological, are the result of a growth process. Many of these networks continue to grow for prolonged periods of time, continually modifying their connectivity structure throughout their entire existence. For example, the World Wide Web has grown from a small number of cross-linked documents in the early 1 990s to an estimated 30 billion indexed web pages in 2009.3 The extraordinary growth of the Web continues… 

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References

SHOWING 1-10 OF 925 REFERENCES

Graph theoretical analysis of complex networks in the brain

These studies suggest that the human brain can be modelled as a complex network, and may have a small-world structure both at the level of anatomical as well as functional connectivity, and increasing evidence that various types of brain disease may be associated with deviations of the functional network topology from the optimal small- world pattern.

Emergence of scaling in random networks

A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.

The Structure and Function of Complex Networks

Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.

Classes of network connectivity and dynamics

Different classes of network are identified, including networks that are characterized by high complexity, which have distinct structural characteristics such as clustered connectivity and short wiring length similar to those of large-scale networks of the cerebral cortex.

Criticality of spreading dynamics in hierarchical cluster networks without inhibition

Findings indicate that a hierarchical cluster architecture may provide the structural basis for the stable and diverse functional patterns observed in cortical networks.

Self-organized critical neural networks.

A mechanism for self-organization of the degree of connectivity in model neural networks is studied in a two-dimensional neural network with randomly wired asymmetric weights, which is independent of initial conditions, robust against thermal noise, and does not require fine tuning of parameters.

Network structure of cerebral cortex shapes functional connectivity on multiple time scales

Simulating nonlinear neuronal dynamics on a network that captures the large-scale interregional connections of macaque neocortex, and applying information theoretic measures to identify functional networks, this work finds structure–function relations at multiple temporal scales.

The small world of the cerebral cortex

All cortical connection matrices examined in this study exhibit “small-world” attributes, characterized by the presence of abundant clustering of connections combined with short average distances between neuronal elements.
...