REMOD: a tool for analyzing and remodeling the dendritic architecture of neural cells
Dendritic morphology is a key determinant of how individual neurons acquire a unique signal processing profile. The highly branched dendritic structure that originates from the cell body, explores the surrounding 3D space in a fractal-like manner, until it reaches a certain amount of complexity. Its...
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doaj-1462c610bdcc409d9aa73a31df3fff1c2020-11-24T23:45:07ZengFrontiers Media S.A.Frontiers in Neuroanatomy1662-51292016-01-01910.3389/fnana.2015.00156166642REMOD: a tool for analyzing and remodeling the dendritic architecture of neural cellsPanagiotis eBozelos0Panagiotis eBozelos1Stefanos eStefanou - Stamatiadis2Stefanos eStefanou - Stamatiadis3George eBouloukakis4George eBouloukakis5Constantinos eMelachrinos6Panayiota ePoirazi7Foundation for Research and Technology-Hellas (FORTH)Democritus University of ThraceFoundation for Research and Technology-Hellas (FORTH)University of CreteFoundation for Research and Technology-Hellas (FORTH)University of CreteFoundation for Research and Technology-Hellas (FORTH)Foundation for Research and Technology-Hellas (FORTH)Dendritic morphology is a key determinant of how individual neurons acquire a unique signal processing profile. The highly branched dendritic structure that originates from the cell body, explores the surrounding 3D space in a fractal-like manner, until it reaches a certain amount of complexity. Its shape undergoes significant alterations under various physiological or neuropathological conditions. Yet, despite the profound effect that these alterations can have on neuronal function, the causal relationship between the two remains largely elusive. The lack of a systematic approach for remodeling neural cells and their dendritic trees is a key limitation that contributes to this problem. Such causal relationships can be inferred via the use of large-scale neuronal models whereby the anatomical plasticity of neurons is accounted for, in order to enhance their biological relevance and hence their predictive performance. To facilitate this effort, we developed a computational tool named REMOD that allows the structural remodeling of any type of virtual neuron. REMOD is written in Python and can be accessed through a dedicated web interface that guides the user through various options to manipulate selected neuronal morphologies. REMOD can also be used to extract meaningful morphology statistics for one or multiple reconstructions, including features such as sholl analysis, total dendritic length and area, path length to the soma, centrifugal branch order, diameter tapering and more. As such, the tool can be used both for the analysis and/or the remodeling of neuronal morphologies of any type.http://journal.frontiersin.org/Journal/10.3389/fnana.2015.00156/fullDendritesNeuronscomputational neurosciencedendritic morphologystatistical analysisdendritic remodeling |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Panagiotis eBozelos Panagiotis eBozelos Stefanos eStefanou - Stamatiadis Stefanos eStefanou - Stamatiadis George eBouloukakis George eBouloukakis Constantinos eMelachrinos Panayiota ePoirazi |
spellingShingle |
Panagiotis eBozelos Panagiotis eBozelos Stefanos eStefanou - Stamatiadis Stefanos eStefanou - Stamatiadis George eBouloukakis George eBouloukakis Constantinos eMelachrinos Panayiota ePoirazi REMOD: a tool for analyzing and remodeling the dendritic architecture of neural cells Frontiers in Neuroanatomy Dendrites Neurons computational neuroscience dendritic morphology statistical analysis dendritic remodeling |
author_facet |
Panagiotis eBozelos Panagiotis eBozelos Stefanos eStefanou - Stamatiadis Stefanos eStefanou - Stamatiadis George eBouloukakis George eBouloukakis Constantinos eMelachrinos Panayiota ePoirazi |
author_sort |
Panagiotis eBozelos |
title |
REMOD: a tool for analyzing and remodeling the dendritic architecture of neural cells |
title_short |
REMOD: a tool for analyzing and remodeling the dendritic architecture of neural cells |
title_full |
REMOD: a tool for analyzing and remodeling the dendritic architecture of neural cells |
title_fullStr |
REMOD: a tool for analyzing and remodeling the dendritic architecture of neural cells |
title_full_unstemmed |
REMOD: a tool for analyzing and remodeling the dendritic architecture of neural cells |
title_sort |
remod: a tool for analyzing and remodeling the dendritic architecture of neural cells |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neuroanatomy |
issn |
1662-5129 |
publishDate |
2016-01-01 |
description |
Dendritic morphology is a key determinant of how individual neurons acquire a unique signal processing profile. The highly branched dendritic structure that originates from the cell body, explores the surrounding 3D space in a fractal-like manner, until it reaches a certain amount of complexity. Its shape undergoes significant alterations under various physiological or neuropathological conditions. Yet, despite the profound effect that these alterations can have on neuronal function, the causal relationship between the two remains largely elusive. The lack of a systematic approach for remodeling neural cells and their dendritic trees is a key limitation that contributes to this problem. Such causal relationships can be inferred via the use of large-scale neuronal models whereby the anatomical plasticity of neurons is accounted for, in order to enhance their biological relevance and hence their predictive performance. To facilitate this effort, we developed a computational tool named REMOD that allows the structural remodeling of any type of virtual neuron. REMOD is written in Python and can be accessed through a dedicated web interface that guides the user through various options to manipulate selected neuronal morphologies. REMOD can also be used to extract meaningful morphology statistics for one or multiple reconstructions, including features such as sholl analysis, total dendritic length and area, path length to the soma, centrifugal branch order, diameter tapering and more. As such, the tool can be used both for the analysis and/or the remodeling of neuronal morphologies of any type. |
topic |
Dendrites Neurons computational neuroscience dendritic morphology statistical analysis dendritic remodeling |
url |
http://journal.frontiersin.org/Journal/10.3389/fnana.2015.00156/full |
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