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

[Marcus Kaiser]

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
http://dx.doi.org/10.1371/journal.pcbi.0020095
and supporting information and data sets can be found at:
http://www.biological-networks.org/

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, Germany

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

Regards,
Marcus

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