On brain-inspired hierarchical network topologies

Valeriu Beiu, Basheer A.M. Madappuram, Peter M. Kelly, Liam J. McDaid

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


In this paper our aim is to identify layered hierarchical generic network topologies which could closely mimic brain's connectivity. Recent analyses have compared the brain's connectivity (based both on a cortical-equivalent Rent's rule and on neurological data) with well-known network topologies used in supercomputers and massively parallel computers (using two different interpretations of Rent's rule). These have revealed that all the well-known computer network topologies fall short of being strong contenders for mimicking the brain's connectivity. That is why in this paper we perform a high-level analysis of two-layer hierarchical generic networks. The range of granularities (i.e., number of gates/cores/neurons) as well as the fan-ins and the particular combinations of the two generic networks which would make such a mimicking achievable are identified and discussed.

Original languageEnglish
Title of host publication2009 9th IEEE Conference on Nanotechnology, IEEE NANO 2009
Number of pages4
Publication statusPublished - 2009
Event2009 9th IEEE Conference on Nanotechnology, IEEE NANO 2009 - Genoa, Italy
Duration: Jul 26 2009Jul 30 2009

Publication series

Name2009 9th IEEE Conference on Nanotechnology, IEEE NANO 2009


Other2009 9th IEEE Conference on Nanotechnology, IEEE NANO 2009


  • Brain
  • Connectivity
  • Nano-architecture
  • Network topology
  • Network-on-chip
  • Neural networks
  • Rent's rule

ASJC Scopus subject areas

  • Process Chemistry and Technology
  • Electrical and Electronic Engineering


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