REMOD: a computational tool for remodeling neuronal dendrites
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1
Democritus University of Thrace, Department of Molecular Biology & Genetics, Greece
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2
University of Crete, Computer Science Department, Greece
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3
University of Crete, Department of Biology, Greece
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4
IMBB, Foundation for Research and Technology-Hellas, Greece
In recent years, several modeling studies have indicated that 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 not only in various neuropathological conditions, but in physiological, too. Yet, despite the profound effect that these alterations can have on neuronal function, the causal relationship between structure and function remains largely elusive. The lack of a systematic approach for remodeling neuronal cells and their dendritic trees is a key limitation that contributes to this problem.
In this context, we developed a computational tool that allows the remodeling of any type of neurons, given a set of exemplar morphologies. The tool is written in Python and provides a simple GUI that guides the user through various options to manipulate selected neuronal morphologies. It provides the ability to load one or more morphology files (.swc or .hoc) and choose specific dendrites to operate one of the following actions: shrink, remove, extend or branch (as shown in Figure 1). The user retains complete control over the extent of each alteration and if a chosen action is not possible due to pre-existing structural constraints, appropriate warnings are produced. Importantly, the tool can also be used to extract morphology statistics for one or multiple morphologies, including features such as the total dendritic length, path length to the root, branch order, diameter tapering, etc. Finally, an experimental utility enables the user to remodel entire dendritic trees based on preloaded statistics from a database of cell-type specific neuronal morphologies.
To our knowledge, this is the first tool that allows (a) the remodeling of existing –as opposed to the de novo generation of- neuronal morphologies both ad hoc and based on predefined statistics and (b) the extraction of morphological feature statistics. Thus, REMOD allows the implementation of a systematic approach for altering neuronal morphologies that will promote further research into understanding the hidden associations between critical morphology parameters and the distinct electrophysiological patterns that individual neurons exhibit.
Acknowledgements
This work is funded by the ERC Starting Grant dEMORY (ERC-2012-StG-311435) and the BIOSYS research project, Action KRIPIS, project No MIS-448301 (2013SE01380036).
Keywords:
dendritic morphology,
Dendrites,
neuronal function,
dendritic computations,
neural computations
Conference:
4th NAMASEN Training Workshop - Dendrites 2014, Heraklion, Greece, 1 Jul - 4 Jul, 2014.
Presentation Type:
Poster presentation
Topic:
the role of dendrites in complex processes, including learning/memory and neural computations
Citation:
Bozelos
P,
Bouloukakis
G,
Stefanou
SS and
Poirazi
P
(2014). REMOD: a computational tool for remodeling neuronal dendrites.
Front. Syst. Neurosci.
Conference Abstract:
4th NAMASEN Training Workshop - Dendrites 2014.
doi: 10.3389/conf.fnsys.2014.05.00047
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Received:
11 Apr 2014;
Published Online:
12 Jun 2014.
*
Correspondence:
Mr. Panagiotis Bozelos, Democritus University of Thrace, Department of Molecular Biology & Genetics, Heraklion, Greece, bozelosp@gmail.com
Dr. Panayiota Poirazi, IMBB, Foundation for Research and Technology-Hellas, Heraklion, Greece, poirazi@imbb.forth.gr