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Mathematical modeling of the neuron morphology using two dimensional images

Rajković, Katarina et al.

Journal of theoretical biology. Volume 390 (2016); pp 80-85 -- Elsevier Science Ltd

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  • Title:
    Mathematical modeling of the neuron morphology using two dimensional images
  • Author: Rajković, Katarina;
    Marić, Dušica L.;
    Milošević, Nebojša T.;
    Jeremic, Sanja;
    Arsenijević, Valentina Arsić;
    Rajković, Nemanja
  • Found In: Journal of theoretical biology. Volume 390 (2016); pp 80-85
  • Journal Title: Journal of theoretical biology
  • Subjects: Biologie--Périodiques; Biological Science Disciplines--Periodicals; Biology--Periodicals; Theoretische biologie; Biology; Periodicals; Dentate nucleus--Fractal analysis--Modified Sholl analysis--Neuronal image--Response surface methodology; Dewey: 571.05
  • Rights: legaldeposit
  • Publication Details: Elsevier Science Ltd
  • Abstract: Abstract:

    In this study mathematical analyses such as the analysis of area and length, fractal analysis and modified Sholl analysis were applied on two dimensional (2D) images of neurons from adult human dentate nucleus (DN). Using mathematical analyses main morphological properties were obtained including the size of neuron and soma, the length of all dendrites, the density of dendritic arborization, the position of the maximum density and the irregularity of dendrites. Response surface methodology (RSM) was used for modeling the size of neurons and the length of all dendrites. However, the RSM model based on the second-order polynomial equation was only possible to apply to correlate changes in the size of the neuron with other properties of its morphology. Modeling data provided evidence that the size of DN neurons statistically depended on the size of the soma, the density of dendritic arborization and the irregularity of dendrites. The low value of mean relative percent deviation ( MRPD ) between the experimental data and the predicted neuron size obtained by RSM model showed that model was suitable for modeling the size of DN neurons. Therefore, RSM can be generally used for modeling neuron size from 2D images.

    Highlights:

    The response surface methodology (RSM) was used for modeling the size of neurons.

    The RSM model using second-order polynomial for predicted the size of neurons.

    Evaluating was influence the morphology properties on the size of neurons.


  • Identifier: System Number: LDEAvdc_100051377418.0x000001; Journal ISSN: 0022-5193; 10.1016/j.jtbi.2015.11.019
  • Publication Date: 2016
  • Physical Description: Electronic
  • Shelfmark(s): ELD Digital store

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