Constructed Tessellated Neuronal Geometries (CTNG) (McDougal et al. 2013)

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Accession:146950
We present an algorithm to form watertight 3D surfaces consistent with the point-and-diameter based neuronal morphology descriptions widely used with spatial electrophysiology simulators. ... This (point-and-diameter) representation is well-suited for electrophysiology simulations, where the space constants are larger than geometric ambiguities. However, the simple interpretations used for pure electrophysiological simulation produce geometries unsuitable for multi-scale models that also involve three-dimensional reaction–diffusion, as such models have smaller space constants. ... Although one cannot exactly reproduce an original neuron's full shape from point-and-diameter data, our new constructive tessellated neuronal geometry (CTNG) algorithm uses constructive solid geometry to define a plausible reconstruction without gaps or cul-de-sacs. CTNG then uses “constructive cubes” to produce a watertight triangular mesh of the neuron surface, suitable for use in reaction–diffusion simulations. ..."
Reference:
1 . McDougal RA, Hines ML, Lytton WW (2013) Water-tight membranes from neuronal morphology files Journal of Neuroscience Methods 220(2):167-78 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; C or C++ program; Python; Cython;
Model Concept(s): Methods;
Implementer(s): McDougal, Robert [robert.mcdougal at yale.edu];
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ctng
geometry3d
readme.txt
ctng.py
                            
CTNG (Constructive Tessellated Neuronal Geometry) is a tool for
constructing a 3d tesselation of a neuron's surface from
point-diameter data.

Before use: compile the C and Cython routines:

    cd geometry3d
    python setup.py build_ext --inplace

To use (for now displays the neuron, but could easily write data to a file):

    python ctng.py FILENAME_IN [FILENAME_OUT] [dx]
    
where neuron_file is the name of the source morphology.

e.g.

    python ctng.py Vn03082006-0-D.ASC out.tri 0.25

The first line of an output file lists the number of triangles and the area.

Each triangle is listed on its own line in the following format:

    x1, y1, z1,    x2, y2, z2,    x3, y3, z3

Requires:
    g++
    cython
    python
        numpy
        mayavi
    NEURON


Most of the figures for the CTNG paper were made using the morphology from

http://neuromorpho.org/neuroMorpho/neuron_info.jsp?neuron_name=Vn03082006-0-D

Changelog:

2012-12-10    sphere tests for contains_surface is primary
              bugfix for case where no output file specified
              lowered minimum chunk width from 100 to 20 voxels

2013-01-21    refactoring, bugfixes
              surfaces now provably watertight (last change introduced holes)

2013-10-05    fix to extreme points of soma (was using axis, not the soma data)

2016-05-31    commented out some printfs and changed a tuple to a list to make
              it compile with current cython and python code

              now checking filenames and using the SWC loader if a .swc file
              is loaded


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