Shaping Realistic Neuronal Morphologies: An Evolutionary Computation Method

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Torben-Nielsen:2006:CEC,
  author =       "Ben Torben-Nielsen and Karl Tuyls and Eric O. Postma",
  title =        "Shaping Realistic Neuronal Morphologies: An
                 Evolutionary Computation Method",
  booktitle =    "Proceedings of IJCNN '06 the 2006 International Joint
                 Conference on Neural Networks",
  year =         "2006",
  editor =       "Gary G. Yen and Lipo Wang and Piero Bonissone and 
                 Simon M. Lucas",
  pages =        "1300--1307",
  address =      "Vancouver",
  month =        "6-21 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming,
                 Lindenmayer-System",
  ISBN =         "0-7803-9487-9",
  URL =          "http://www.cs.unimaas.nl/b.torben-nielsen/ijcnn_draft.pdf",
  URL =          "http://ieeexplore.ieee.org/xpl/RecentCon.jsp?punumber=11216",
  DOI =          "doi:10.1109/IJCNN.2006.246733",
  size =         "8 pages",
  abstract =     "Neuronal morphology plays a crucial role in the
                 information processing capabilities of neurons. Despite
                 the importance of morphology for neural functionality,
                 biological data is scarce and hard to obtain.
                 Therefore, virtual neurons are devised to allow
                 extensive modelling and experimenting. The main problem
                 with current virtual-neuron generation methods is that
                 they impose severe a priori constraints on the virtual
                 morphologies. These constraints are based on widespread
                 assumptions and beliefs about the morphology of real
                 neurons. To overcome this problem, we present
                 EvOL-Neuron, a new method based on L-Systems and
                 Evolutionary Computation that imposes a posteriori
                 constraints on candidate virtual neuron morphologies.
                 As a proof of principle, our experiments show the power
                 of the new method. Moreover, our method revealed a
                 limitation in the description of neural morphology in
                 the literature. We empirically show that Hillman's
                 fundamental parameters of neuron morphology are
                 satisfactory but not sufficient to describe neuronal
                 morphology. The results are discussed and an outline
                 for future research is given. We conclude that we
                 succeeded in devising a new method for virtual-neuron
                 generation that does not impose a priori limitations on
                 the virtual-neuron morphology.",
  notes =        "

                 IEEExplore says pages 573--580 but pages are 1300-1307
                 in proceedings CDROM

                 WCCI 2006 - A joint meeting of the IEEE, the EPS, and
                 the IEE.

                 IEEE Catalog Number: 06TH8846D",
}

Genetic Programming entries for Ben Torben-Nielsen Karl Tuyls Eric O Postma

Citations