L-Neuron Download

L-Neuron (v1.08b) is now available for the Windows and Linux platform (thanks to the help of Guido Cervone).For Linux you can dowload it, here . After downloading L-Neuron, please use the command 'chmod +x LM.exe' to change its file access permission.

For Windows please use this link .

For help and example files click here

For further questions drop me an email: Ruggero Scorcioni

L-Neuron: Generation and Description of Dendritic Morphology

The primary goal of the L-Neuron project is to create virtual neurons that are anatomically indistinguishable from their real counterparts. L-Neuron uses the formalism of the Lyndenmayer systems in the version known as Turtle Graphics. Particularly, the L-Neuron program is based on a modification of Laurens Lapre's "L-Parser". Instead of working with the standard L-systems algorithms, however, L-Neuron implements sets of neuroanatomical rules discovered by several research groups (and in particular, Hillman's, Tamori', and Burke's). These rules are local and recursive.

The
fact that the rules are *local*
means that they establish correlations
among geometrical parameters (e.g. a dendritic branch's diameter and
taper)
independent of their overall position in the tree. The term *recursive*
refers to the fact that, as a branch grows, it stems other branches
that
follow the same rules. Therefore the same simple algorithm can be
reiterated
many times as the dendritic tree develops more and more bifurcations
(as
shown in this figure, representing the Hillman rules). The L-Neuron
algorithms
read in experimental data to generate virtual structures. The
experimental
data are in the form of statistical distributions (for example,
bifurcation
angles in Purkinje cells can be represented with a Gaussian
distribution,
with a certain average and standard deviation). L-Neuron samples the
values
of the parameters within these statistical distributions in a
stochastic
(random) fashion during dendritic growth. Therefore, with the same set
of parameter distributions, the program can generate an unlimited
number
of virtual neurons.

Because L-Neuron implements a stochastic and statistical algorithm, it achieves a form of morphological data compression and amplification. Compression because hundreds of experimental neuronal tracings within a certain morphological class can be described with a handful of statistical distributions, instead of with the classical compartmental description (thousands of lines per neuron). Amplification because, from those hundred real neurons, one can then generate thousands of virtual counterparts.

Note that different sets of statistical distributions correspond to different morphological families. By varying these values, the same algorithm can describe neurons as diverse as pyramidal, granule, Purkinje, or stellate cells. In this screen shot of the L-Neuron viewer, a pyramidal cell was generated with experimental values reported by Hillman. Green segments are basal dendrites, blue segments are apical dendrites, and the soma is drawn in red.

L-Neuron can output its virtual structures in a variety of
formats,
including virtual reality, graphical files, and the standard
neuroanatomical
coordinates compatible with neurophysiological simulators such as GENESIS
and Neuron.

The L-Neuron Project is supported by the Krasnow Institute for Advanced Study and by Human Brain Project grant R01-NS39600-01 awarded to Giorgio Ascoli by the National Institute of Neurological Disorders and Stroke (NIH).

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