Compartmental models of growing neurites (Graham and van Ooyen 2004)

 Download zip file 
Help downloading and running models
Accession:59582
Simulator for models of neurite outgrowth. The principle model is a 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.
Reference:
1 . Graham BP, van Ooyen A (2004) Transport limited effects in a model of dendritic branching. J Theor Biol 230:421-32 [PubMed]
2 . Graham BP, van Ooyen A (2006) Mathematical modelling and numerical simulation of the morphological development of neurons. BMC Neurosci 7 Suppl 1:S9 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Axon; Dendrite;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: Java;
Model Concept(s): Development;
Implementer(s): Graham, Bruce [B.Graham at cs.stir.ac.uk];
  
*******************************************************
*** Simulator for Models of Neurite Outgrowth ***
*******************************************************

Help Contents:

1. Author Details
2. System Requirements
3. Quick User Guide
4. Model Descriptions
5. References


-----------------------------------------
1. Author Details:
-----------------------------------------
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/


-----------------------------------------
2. System Requirements:
-----------------------------------------
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.


-----------------------------------------
3. Quick User Guide:
-----------------------------------------

Button		Function
------		--------
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


-----------------------------------------
4. Model Descriptions:
-----------------------------------------

The simulator currently contains three models of neurite outgrowth.

1. BESTL
--------
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
-----
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
-------
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


-----------------------------------------
5. References:
-----------------------------------------

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.




Graham BP, van Ooyen A (2004) Transport limited effects in a model of dendritic branching. J Theor Biol 230:421-32[PubMed]

References and models cited by this paper

References and models that cite this paper

Acebes A, Ferrus A (2000) Cellular and molecular features of axon collaterals and dendrites. Trends Neurosci 23:557-65 [PubMed]

Alvarez J, Giuditta A, Koenig E (2000) Protein synthesis in axons and terminals: significance for maintenance, plasticity and regulation of phenotype. With a critique of slow transport theory. Prog Neurobiol 62:1-62 [PubMed]

Audesirk G, Cabell L, Kern M (1997) Modulation of neurite branching by protein phosphorylation in cultured rat hippocampal neurons. Brain Res Dev Brain Res 102:247-60

Burke RE, Marks WB, Ulfhake B (1992) A parsimonious description of motoneuron dendritic morphology using computer simulation. J Neurosci 12:2403-16 [PubMed]

Carriquiry AL, Ireland WP, Kliemann W, Uemura E (1991) Statistical evaluation of dendritic growth models. Bull Math Biol 53:579-89

Cline HT (2001) Dendritic arbor development and synaptogenesis. Curr Opin Neurobiol 11:118-26 [PubMed]

Dityatev AE, Chmykhova NM, Studer L, Karamian OA, Kozhanov VM, Clamann HP (1995) Comparison of the topology and growth rules of motoneuronal dendrites. J Comp Neurol 363:505-16 [PubMed]

Galbraith JA, Reese TS, Schlief ML, Gallant PE (1999) Slow transport of unpolymerized tubulin and polymerized neurofilament in the squid giant axon. Proc Natl Acad Sci U S A 96:11589-94

Graham B, Hely T, Van_Ooyen A (1998) An internal signalling model of the dendritic branching process Euro J Neurosci (Suppl.10) 10:274

Graham B, Van_Ooyen A (2001) Compartmental models of growing neurites Neurocomputing 38:31-36

Hely TA, Graham B, Ooyen AV (2001) A computational model of dendrite elongation and branching based on MAP2 phosphorylation. J Theor Biol 210:375-84 [PubMed]

Hillman DE (1979) Neuronal shape parameters and substructures as a basis of neuronal form. The Neurosciences (4th Study Program), F O Schmitt and F G Worden, ed. pp.477

Kobayashi N, Mundel P (1998) A role of microtubules during the formation of cell processes in neuronal and non-neuronal cells. Cell Tissue Res 291:163-74

Li GH, Qin CD, Wang LW (1995) Computer model of growthcone behavior and neuronal morphogenesis J Theor Biol 174:381-389

Maccioni RB, Cambiazo V (1995) Role of microtubule-associated proteins in the control of microtubule assembly. Physiol Rev 75:835-64

Mclean D, Van_Ooyen A, Graham B (2003) Continuum model for tubulin-driven neurite elongation Computational Neuroscience in Alicante, Spain

Miller KE, Samuels DC (1997) The axon as a metabolic compartment: protein degradation, transport, and maximum length of an axon. J Theor Biol 186:373-9 [PubMed]

Mitchison T, Kirschner M (2004) Dynamic instability of microtubule growth. Nature 312:237-42

Nowakowski RS, Hayes NL, Egger MD (1992) Competitive interactions during dendritic growth: a simple stochastic growth algorithm. Brain Res 576:152-6 [PubMed]

Odde DJ (1997) Estimation of the diffusion-limited rate of microtubule assembly. Biophys J 73:88-96 [PubMed]

RALL W (1959) Branching dendritic trees and motoneuron membrane resistivity. Exp Neurol 1:491-527 [PubMed]

Redmond L, Ghosh A (2001) The role of Notch and Rho GTPase signaling in the control of dendritic development. Curr Opin Neurobiol 11:111-7

Shah JV, Cleveland DW (2002) Slow axonal transport: fast motors in the slow lane. Curr Opin Cell Biol 14:58-62

Tamori Y (1993) Theory of dendritic morphology. PHYSICAL REVIEW. E. STATISTICAL PHYSICS, PLASMAS, FLUIDS, AND RELATED INTERDISCIPLINARY TOPICS 48:3124-3129

Uemura E, Carriquiry A, Kliemann W, Goodwin J (1995) Mathematical modeling of dendritic growth in vitro. Brain Res 671:187-94 [PubMed]

van Pelt J, Dityatev AE, Uylings HB (1997) Natural variability in the number of dendritic segments: model-based inferences about branching during neurite outgrowth. J Comp Neurol 387:325-40 [PubMed]

Van Pelt J, Uylings HB (1999) Natural variability in the geometry of dendritic branching patterns. Modeling in the Neurosciences, From Ionic Channels to Neural Networks, RR Poznanski, ed. pp.79

van Pelt J, Uylings HB (2002) Branching rates and growth functions in the outgrowth of dendritic branching patterns. Network 13:261-81 [PubMed]

Van Pelt J, Van Ooyen A, Uylings HB (2001) Modeling dendritic geometry and the development of nerve connections. Computational Neuroscience, Realistic Modeling for Experimentalists, E De Schutter, ed. pp.179

Van_Pelt J, Graham B, Uylings H (2003) Formation of dendriticbranching patterns Modeling Neural Development (chapter 4), van_Ooyan A, ed. pp.75

van_Veen M, van_Pelt J (1992) A model for outgrowth of branching neurites J Theor Biol 159:1-23

Whitford KL, Dijkhuizen P, Polleux F, Ghosh A (2002) Molecular control of cortical dendrite development. Annu Rev Neurosci 25:127-49

Graham BP, Lauchlan K, McLean DR (2006) Dynamics of outgrowth in a continuum model of neurite elongation. J Comput Neurosci 20:43-60 [Journal] [PubMed]

   Continuum model of tubulin-driven neurite elongation (Graham et al 2006) [Model]

Graham BP, van Ooyen A (2006) Mathematical modelling and numerical simulation of the morphological development of neurons. BMC Neurosci 7 Suppl 1:S9 [PubMed]

   Continuum model of tubulin-driven neurite elongation (Graham et al 2006) [Model]
   Compartmental models of growing neurites (Graham and van Ooyen 2004) [Model]

Hjorth JJ, van Pelt J, Mansvelder HD, van Ooyen A (2014) Competitive Dynamics during Resource-Driven Neurite Outgrowth. PLoS One 9:e86741 [Journal] [PubMed]

   Resource competition in growing neurites (Hjorth et al 2014) [Model]

Koene RA, Tijms B, van Hees P, Postma F, de Ridder A, Ramakers GJ, van Pelt J, van Ooyen A (2009) NETMORPH: a framework for the stochastic generation of large scale neuronal networks with realistic neuron morphologies. Neuroinformatics 7:195-210 [Journal] [PubMed]

   NETMORPH: creates NNs with realistic neuron morphologies (Koene et al. 2009, van Ooyen et al. 2014) [Model]

Sterratt D, Graham B, Gillies A, Willshaw D (2011) Principles of Computational Modelling in Neuroscience, Cambridge University Press :1-401 [Journal]

   Principles of Computational Modelling in Neuroscience (Book) (Sterratt et al. 2011) [Model]

van Elburg R (2011) Stochastic Continuous Time Neurite Branching Models with Tree and Segment Dependent Rates Journal of Theoretical Biology 276(1):159-173 [Journal]

   Continuous time stochastic model for neurite branching (van Elburg 2011) [Model]

(38 refs)

Graham BP, van Ooyen A (2006) Mathematical modelling and numerical simulation of the morphological development of neurons. BMC Neurosci 7 Suppl 1:S9[PubMed]

References and models cited by this paper

References and models that cite this paper

Acebes A, Ferrus A (2000) Cellular and molecular features of axon collaterals and dendrites. Trends Neurosci 23:557-65 [PubMed]

Aeschlimann M (2000) Biophysical models of axonal pathfinding PhD Thesis

Aeschlimann M, Tettoni L (2001) Biophysical model of axonal path finding Neurocomputing 38:87-92

Alvarez J, Giuditta A, Koenig E (2000) Protein synthesis in axons and terminals: significance for maintenance, plasticity and regulation of phenotype. With a critique of slow transport theory. Prog Neurobiol 62:1-62 [PubMed]

Ascoli GA (2002) Computational neuroanatomy: Principles and methods, Ascoli GA, ed.

Ascoli GA (2002) Neuroanatomical algorithms for dendritic modelling. Network 13:247-60 [PubMed]

Bhalla US, Iyengar R (1999) Emergent properties of networks of biological signaling pathways. Science 283:381-7 [PubMed]

   Emergent properties of networks of biological signaling pathways (Bhalla, Iyengar 1999) [Model]

Bower J, Beeman D (1994) The Book of GENESIS: exploring realistic neural models with the GEneral NEural Simulation System

Bray D (1973) Branching patterns of individual sympathetic neurons in culture. J Cell Biol 56:702-12 [PubMed]

Burke RE, Marks WB, Ulfhake B (1992) A parsimonious description of motoneuron dendritic morphology using computer simulation. J Neurosci 12:2403-16 [PubMed]

Gh LI, Qin CD, Wang LW (1995) Computer model of growth cone behavior and neuronal morphogenesis J Theor Biol 174:381-389

Goodhill G, Urbach J (2003) Axon guidance and gradient detection by growth cones Modeling Neural Development, van_Ooyen A, ed. pp.95

Graham B, Van_Ooyen A (2001) Compartmental models of growing neurites Neurocomputing 38:31-36

Graham BP (2001) Pattern recognition in a compartmental model of a CA1 pyramidal neuron. Network 12:473-92 [Journal] [PubMed]

   Signal integration in a CA1 pyramidal cell (Graham 2001) [Model]

Graham BP, Lauchlan K, McLean DR (2006) Dynamics of outgrowth in a continuum model of neurite elongation. J Comput Neurosci 20:43-60 [Journal] [PubMed]

   Continuum model of tubulin-driven neurite elongation (Graham et al 2006) [Model]

Graham BP, van Ooyen A (2004) Transport limited effects in a model of dendritic branching. J Theor Biol 230:421-32 [PubMed]

   Compartmental models of growing neurites (Graham and van Ooyen 2004) [Model]

Hely TA, Graham B, Ooyen AV (2001) A computational model of dendrite elongation and branching based on MAP2 phosphorylation. J Theor Biol 210:375-84 [PubMed]

Hentschel H, Fine A (2003) Early dendritic and axonal morphogenesis Modeling Neural Development, van_Ooyen A, ed. pp.49

Hentschel H, Samuels D, Fine A (1998) Instabilities during the dendritic and axonal development of neuronal form Physica A 254:46-61

Hentschel HG, Fine A (1994) Instabilities in Cellular Dendritic Morphogenesis. PHYSICAL REVIEW LETTERS 73:3592-3595 [PubMed]

Hentschel HG, Fine A (1996) Diffusion-regulated control of cellular dendritic morphogenesis. Proc Biol Sci 263:1-8 [PubMed]

Hentschel HG, van Ooyen A (1999) Models of axon guidance and bundling during development. Proc Biol Sci 266:2231-8 [PubMed]

Hillman DE (1979) Neuronal shape parameters and substructures as a basis of neuronal form. The Neurosciences (4th Study Program), F O Schmitt and F G Worden, ed. pp.477

Hines M (1984) Efficient computation of branched nerve equations. Int J Biomed Comput 15:69-76 [PubMed]

Hines ML, Carnevale NT (1997) The NEURON simulation environment. Neural Comput 9:1179-209 [PubMed]

Janulevicius A, van Pelt J, van Ooyen A (2006) Compartment volume influences microtubule dynamic instability: a model study. Biophys J 90:788-98 [PubMed]

Kiddie G, Mclean D, Van_Ooyen A, Graham B (2005) Biologically plausible models of neurite outgrowth Development, dynamics and pathology of neuronal networks: from molecules to functional circuits, Progress in Brain Research, van Pelt J: Kamermans M: Levelt C: van Ooyen A: Ramakers G: Roelfsema P, ed. pp.67

Krottje JK, van Ooyen A (2007) A mathematical framework for modeling axon guidance. Bull Math Biol 69:3-31

Li GH, Qin CD, Li MH (1994) On the mechanisms of growth cone locomotion: modeling and computer simulation. J Theor Biol 169:355-62 [PubMed]

Mainen ZF, Sejnowski TJ (1996) Influence of dendritic structure on firing pattern in model neocortical neurons. Nature 382:363-6 [Journal] [PubMed]

   [2 reconstructed morphologies on NeuroMorpho.Org]
   Pyramidal Neuron Deep, Superficial; Aspiny, Stellate (Mainen and Sejnowski 1996) [Model]

Mascagni MV, Sherman AS (1998) Numerical methods for neuronal modelling. Methods in Neuronal Modeling From Synapses to Networks, 2nd Edition, Koch C:Segev I, ed. pp.569

Maskery SM, Buettner HM, Shinbrot T (2004) Growth cone pathfinding: a competition between deterministic and stochastic events. BMC Neurosci 5:22-58 [PubMed]

Mclean D, Graham B (2004) Mathematical formulation and analysis of a continuum model for tubulin-driven neurite elongation Proc Roy Soc Lond 460:2437-2456

Mclean D, van_Ooyen A, Graham B (2004) Continuum model for tubulin-driven neurite elongation Neurocomputing 58:511-516

Mel BW (1993) Synaptic integration in an excitable dendritic tree. J Neurophysiol 70:1086-101 [Journal] [PubMed]

Miller KE, Samuels DC (1997) The axon as a metabolic compartment: protein degradation, transport, and maximum length of an axon. J Theor Biol 186:373-9 [PubMed]

Mogilner A, Edelstein-Keshet L (2002) Regulation of actin dynamics in rapidly moving cells: a quantitative analysis. Biophys J 83:1237-58 [PubMed]

Odde DJ (1997) Estimation of the diffusion-limited rate of microtubule assembly. Biophys J 73:88-96 [PubMed]

Odde DJ, Cassimeris L, Buettner HM (1995) Kinetics of microtubule catastrophe assessed by probabilistic analysis. Biophys J 69:796-802 [PubMed]

Pedigo S, Williams RC (2002) Concentration dependence of variability in growth rates of microtubules. Biophys J 83:1809-19 [PubMed]

Samsonovich AV, Ascoli GA (2003) Statistical morphological analysis of hippocampal principal neurons indicates cell-specific repulsion of dendrites from their own cell. J Neurosci Res 71:173-87 [PubMed]

Samsonovich AV, Ascoli GA (2005) Statistical determinants of dendritic morphology in hippocampal pyramidal neurons: A hidden Markov model. Hippocampus 15:166-83 [PubMed]

Samuels DC, Hentschel HG, Fine A (1996) The origin of neuronal polarization: a model of axon formation. Philos Trans R Soc Lond B Biol Sci 351:1147-56

Segev I, Burke RE (1998) Compartmental models of complex neurons Methods In Neuronal Modeling, Koch C:Segev I, ed. pp.93

Segev R, Ben-Jacob E (2000) Generic modeling of chemotactic based self-wiring of neural networks. Neural Netw 13:185-99 [PubMed]

Segev R, Ben-Jacob E (2001) Chemical waves and internal energy during cooperative self-wiring of neural nets Neurocomputing 38:875-879

Shefi O, Golebowicz S, Ben-Jacob E, Ayali A (2005) A two-phase growth strategy in cultured neuronal networks as reflected by the distribution of neurite branching angles. J Neurobiol 62:361-8 [PubMed]

Shefi O, Harel A, Chklovskii D, Ben-Jacob E, Ayali A (2004) Biophysical constraints on neuronal branching Neurocomputing 58:487-495

Smith DA, Simmons RM (2001) Models of motor-assisted transport of intracellular particles. Biophys J 80:45-68 [PubMed]

Tamori Y (1993) Theory of dendritic morphology. PHYSICAL REVIEW. E. STATISTICAL PHYSICS, PLASMAS, FLUIDS, AND RELATED INTERDISCIPLINARY TOPICS 48:3124-3129

van Ooyen A, Duijnhouwer J, Remme MW, van Pelt J (2002) The effect of dendritic topology on firing patterns in model neurons. Network 13:311-25 [PubMed]

Van Pelt J, Uylings HB (1999) Natural variability in the geometry of dendritic branching patterns. Modeling in the Neurosciences, From Ionic Channels to Neural Networks, RR Poznanski, ed. pp.79

Van Veen MP, Van Pelt J (1994) Neuritic growth rate described by modeling microtubule dynamics. Bull Math Biol 56:249-73 [PubMed]

van_Ooyen A (2003) Modeling Neural Development

Van_ooyen A, Graham B, Ramakers G (2001) Competition for tubulin between growing neurites during development Neurocomputing 38:73-78

van_Ooyen A, van_Pelt J (2002) Competition in neuronal morphogenesis and the development of nerve connections Computational Neuroanatomy: Principles and Methods, Ascoli G, ed. pp.219

Van_Pelt J, Graham B, Uylings H (2003) Formation of dendriticbranching patterns Modeling Neural Development (chapter 4), van_Ooyan A, ed. pp.75

van_Veen M, van_Pelt J (1992) A model for outgrowth of branching neurites J Theor Biol 159:1-23

Willshaw D, Price D (2003) Models for topographic map formation Modeling Neural Development, van_Ooyen A, ed. pp.213

Diehl S, Henningsson E, Heyden A (2016) Efficient simulations of tubulin-driven axonal growth. J Comput Neurosci [Journal] [PubMed]

   Axon growth model (Diehl et al. 2016) [Model]

Sterratt D, Graham B, Gillies A, Willshaw D (2011) Principles of Computational Modelling in Neuroscience, Cambridge University Press :1-401 [Journal]

   Principles of Computational Modelling in Neuroscience (Book) (Sterratt et al. 2011) [Model]

(61 refs)