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Brain architecture: a design for natural computation.

Marcus Kaiser1

  • 1School of Computing Science, University of Newcastle, Claremont Tower, Newcastle upon Tyne NE1 7RU, UK. m.kaiser@ncl.uk

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|September 15, 2007
PubMed
Summary
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Brain and computer architecture share historical links. Current neural system organization reveals robust, efficient networks that could inspire future computer designs.

Area of Science:

  • Neuroscience
  • Computer Science
  • Network Architecture

Background:

  • Historical parallels between brain and computer architecture, dating back to John von Neumann's work.
  • Early computer designs were influenced by biological brain organization principles.

Purpose of the Study:

  • To provide an update on current findings regarding the global organization of neural systems.
  • To explore how the architecture of neuronal and cortical networks impacts system functionality.
  • To discuss self-organization mechanisms in neural architectures.

Main Methods:

  • Review of current research on neural system organization.
  • Analysis of spatial and topological network properties.
  • Discussion of self-organization principles.

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Main Results:

  • Neural systems exhibit spatial and topological architectures that enhance robustness against failures.
  • These architectures facilitate rapid information processing within neural networks.
  • Network structures promote balanced activation, crucial for efficient neural function.

Conclusions:

  • The global organization of neural systems demonstrates sophisticated architectural principles.
  • Understanding these principles can inform the development of more resilient and efficient computer architectures.
  • Future computer designs may again draw inspiration from brain organization.