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Contribution of Branching Order of Dendrites to Morphology of Neural Cells


Affiliations
1 Department of Engineering Mathematics and Physics, Faculty of Engineering, Cairo University, Giza, 12613, Egypt
 

It is currently believed that the morphology of dendrites depends on two main factors, namely the material of the cytoplasm and the path length of the signal before reaching the soma. In the present work the branching order is introduced as a third factor; it represents the variation of electrical resistivity of different dendritic segments. A mathematical modification of the optimum cost function is applied. The software package TREES toolbox is employed to reconstruct several types of cells, specifically LPTC, HSS, HSN and starburst amacrine. The effectiveness of the present analysis is assessed by both the electrotonic and Sholl footprints. The results indicate a higher degree of matching between the synthesized reconstructions of these cells and their original morphology. Moreover, a reduction in the storage memory of their in silico morphologies is achieved.

Keywords

Branching Order, Dendrites Morphology, Electrotonic Footprint, Nerve Cells.
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  • Contribution of Branching Order of Dendrites to Morphology of Neural Cells

Abstract Views: 274  |  PDF Views: 104

Authors

Mina Elias
Department of Engineering Mathematics and Physics, Faculty of Engineering, Cairo University, Giza, 12613, Egypt
Noha M. Salem
Department of Engineering Mathematics and Physics, Faculty of Engineering, Cairo University, Giza, 12613, Egypt
Manal M. Awad
Department of Engineering Mathematics and Physics, Faculty of Engineering, Cairo University, Giza, 12613, Egypt
Medhat A. ElMessiery
Department of Engineering Mathematics and Physics, Faculty of Engineering, Cairo University, Giza, 12613, Egypt

Abstract


It is currently believed that the morphology of dendrites depends on two main factors, namely the material of the cytoplasm and the path length of the signal before reaching the soma. In the present work the branching order is introduced as a third factor; it represents the variation of electrical resistivity of different dendritic segments. A mathematical modification of the optimum cost function is applied. The software package TREES toolbox is employed to reconstruct several types of cells, specifically LPTC, HSS, HSN and starburst amacrine. The effectiveness of the present analysis is assessed by both the electrotonic and Sholl footprints. The results indicate a higher degree of matching between the synthesized reconstructions of these cells and their original morphology. Moreover, a reduction in the storage memory of their in silico morphologies is achieved.

Keywords


Branching Order, Dendrites Morphology, Electrotonic Footprint, Nerve Cells.

References





DOI: https://doi.org/10.18520/cs%2Fv116%2Fi3%2F457-462