Modeling realistic morphologies of genetically labelled layer 5 pyramidal neurons.
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1
Karolinska Institutet, Department of Neuroscience, Sweden
The feasibility of computational construction of realistic morphologies with NETMORPH was studied in case of genetically labeled layer 5 pyramidal neurons from mice cerebral cortex (Groh et al 2010). The NETMORPH-framework for stochastic generation of realistic neuronal morphologies has been recently introduced by Koene et al (2009). Morphological data of layer 5 pyramidal neurons from different neocortical areas was quantitatively analyzed for dendritic and axonal shape patterns and their frequency distributions were used to optimize parameters of the dendrite and axon growth process. The computationally generated morphologies were compared with experimental data and model parameter values were compared between neurons from different neocortical areas. Optimized model parameter values were then used to generate large scale networks of neurons.
Conference:
Neuroinformatics 2010 , Kobe, Japan, 30 Aug - 1 Sep, 2010.
Presentation Type:
Poster Presentation
Topic:
Large scale modeling
Citation:
Krieger
P and
Laakso
R
(2010). Modeling realistic morphologies of genetically labelled layer 5 pyramidal neurons..
Front. Neurosci.
Conference Abstract:
Neuroinformatics 2010 .
doi: 10.3389/conf.fnins.2010.13.00106
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Received:
15 Jun 2010;
Published Online:
15 Jun 2010.
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Correspondence:
Patrik Krieger, Karolinska Institutet, Department of Neuroscience, Stockholm, Sweden, patrik.krieger@rub.de