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*** Simulator for Models of Neurite Outgrowth ***
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Help Contents:
1. Author Details
2. System Requirements
3. Quick User Guide
4. Model Descriptions
5. References
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1. Author Details:
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Author: Bruce P. Graham, Department of Computing Science and Mathematics,
University of Stirling, Scotland, U.K.
Email: b.graham@cs.stir.ac.uk
Web: www.cs.stir.ac.uk/~bpg/
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2. System Requirements:
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Should run on any system supporting Java 2.
Code provided as executable jar file (e.g. java -jar Neurite.jar).
Example parameter files in "Params" subdirectory.
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3. Quick User Guide:
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Button Function
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Quit quit the simulator
Load load a set of simulation parameters
Save save a set of simulation parameters
Model select required model from drop-down menu and set model parameters
Simulation set simulation parameters e.g. number of trees,
simulation duration and time step
Display set 2D visualisation parameters
Off/On turn 2D visualisation off or on (visualisation only occurs
during creation of a single tree)
Plot turn on model parameter plotting (each selection creates new graph)
Construct start simulator to create required number of trees (neurites)
Stop terminate current simulation
Draw draw 2D visualisation of one tree from currently created
set of trees ("Display" must be on)
Display tree index of tree visualised by "Draw"
Help shows this file
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4. Model Descriptions:
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The simulator currently contains three models of neurite outgrowth.
1. BESTL
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This is an implementation of van Pelt's stochastic model of
dendritic development, based on the description given in
van Pelt and Uylings (1999).
Example parameter files:
BESTL_PC23.par - rat cortical layer 2/3 pyramidal cell basal
dendrites (van Pelt et al, 2001)
BESTL_PC5.par - rat corical layer 5 pyramidal cell basal
dendrites (van Pelt & Uylings, 1999)
BESTL_nonPC.par - rat cortical layer 4 non-pyramidal cell
dendrites (van Pelt et al, 2003)
BESTL_Pur.par - guinea pig Purkinje cell dendrites (van Pelt et al, 2001)
2. AD
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Biophysical model of neurite outgrowth described in Graham and
van Ooyen (2004). In the model, branching depends on the
concentration of a branch-determining substance in each terminal
segment. The substance is produced in the cell body and is
transported by active transport and diffusion to the terminals.
The model reveals that transport-limited effects may give rise
to the same modulation of branching as indicated by the
stochastic BESTL model. Different limitations arise if transport
is dominated by active transport or by diffusion. Example
parameter files for reproducing the same trees as for the BESTL
model are provided (see Figure 4 and Table 2 of Graham &
van Ooyen, 2004).
Example parameter files: AD_PC23.par, AD_PC5.par, AD_nonPC.par, AD_Pur.par
3. ADcm
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Implementation of the AD model in "compartmental" form, allowing
calculation of spatial concentration profiles along the lengths
of unbranched neurite segments. Compartmentalization follows
"growth cone" scheme of Graham and van Ooyen (2001) in which a
compartment immediately preceding a terminal (or "growth cone")
compartment elongates as the neurite grows. All other
compartments have fixed length. Elongating compartments are
split into two when their length reaches twice the length of
other compartments. A branching event results in a growth cone
compartment being replaced by four new compartments, consisting
of a new growth cone and one preceding compartment for the two
new daughter branches.
Concentration gradients are most obvious when transport is by
slow diffusion.
Example parameter file: ADcm_D600.par
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5. References:
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Graham, B.P. & van Ooyen, A., Compartmental models of growing
neurites, Neurocomputing 38-40:31-36, 2001
Graham, B.P. & van Ooyen, A., Transport limited effects in a
model of dendritic branching, Journal of Theoretical
Neurobiology 230:421-432, 2004
van Pelt, J. & Uylings, H.B.M., Natural variability in the
geometry of dendritic branching patterns, Chapt. 4 in "Modeling
in the Neurosciences: From Ionic Channels to Neural Networks",
Poznanski, R.R. (ed.), Harwood Academic, pp79-108, 1999
van Pelt, J., van Ooyen, A. & Uylings, H.B.M.,, Modeling
dendritic geometry and the development of nerve connections,
Chapt. 7 in "Computational Neuroscience: Realistic Modeling for
Experimentalists", De Schutter, E. (ed.), CRC Press, pp179-208,
2001
van Pelt, J., Graham, B.P. and Uylings, H.B.M., Formation of
dendritic branching patterns, Chapt. 4 in "Modeling Neural
Development", van Ooyen, A. (ed.), MIT Press, pp75-94, 2003.
