[Comp-neuro] New paper: Spatial organisation of cortical and neuronal networks and the role of long-distance connections

Marcus Kaiser M.Kaiser at newcastle.ac.uk
Fri Aug 4 18:25:15 CEST 2006

Dear colleagues,

I want to advertise our paper on the spatial organisation of neural
systems. We find that an abundance of long-distance connections in
primates and C. elegans leads to nonoptimal component placement but
ensures a low number of processing steps in these systems. Indeed, a
lack of long-distance connections is linked with functional deficits as
occuring in Alzheimer and Autism patients. The optimisation for a low
number of processing steps also verifies a prediction of John von
Neumann who compared the architecture of the Computer and the Brain
about 50 years ago.

The paper is available at
and supporting information and data sets can be found at:

The complete abstract is:

Nonoptimal Component Placement, but Short Processing Paths, due to
Long-Distance Projections in Neural Systems

Marcus Kaiser and Claus C. Hilgetag

It has been suggested that neural systems across several scales of
organization show optimal component placement, in which any spatial
rearrangement of the components would lead to an increase of total
wiring. Using extensive connectivity datasets for diverse neural
networks combined with spatial coordinates for network nodes, we applied
an optimization algorithm to the network layouts, in order to search for
wire-saving component rearrangements. We found that optimized component
rearrangements could substantially reduce total wiring length in all
tested neural networks. Specifically, total wiring among 95 primate
(Macaque) cortical areas could be decreased by 32%, and wiring of
neuronal networks in the nematode Caenorhabditis elegans could be
reduced by 48% on the global level, and by 49% for neurons within
frontal ganglia. Wiring length reductions were possible due to the
existence of long-distance projections in neural networks. We explored
the role of these projections by comparing the original networks with
minimally rewired networks of the same size, which possessed only the
shortest possible connections. In the minimally rewired networks, the
number of processing steps along the shortest paths between components
was significantly increased compared to the original networks.
Additional benchmark comparisons also indicated that neural networks are
more similar to network layouts that minimize the length of processing
paths, rather than wiring length. These findings suggest that neural
systems are not exclusively optimized for minimal global wiring, but for
a variety of factors including the minimization of processing steps.

Newcastle University, School of Computing Science, U.K.
International University Bremen, School of Engineering and Science,

PLoS Computational Biology 21 July 2006. Vol. 2, No. 7, e95



Marcus Kaiser, Ph.D.
School of Computing Science
Newcastle University
Claremont Tower
Newcastle upon Tyne NE1 7RU, U.K.
Phone: +44 191 222 8161
Fax:   +44 191 222 8232

More information about the Comp-neuro mailing list