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

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NETMORPH is a simulation tool for building synaptically connected networks with realistic neuron morphologies. Axonal and dendritic morphologies are created by using stochastic rules for the behavior of individual growth cones, the structures at the tip of outgrowing axons and dendrites that mediate elongation and branching. Axons and dendrites are not guided by any extracellular cues. Synapses are formed when crossing axonal and dendritic segments come sufficiently close to each other. See the README in the archive for more information.
Reference:
1 . 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 [PubMed]
2 . van Ooyen A, Carnell A, de Ridder S, Tarigan B, Mansvelder HD, Bijma F, de Gunst M, van Pelt (2014) Independently outgrowing neurons and geometry-based synapse formation produce networks with realistic synaptic connectivity. PLoS One 9:e85858 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; 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: C or C++ program;
Model Concept(s): Methods;
Implementer(s):
  
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netmorph_neuron3d
NETMORPH
NEURON3D
README
                            
NETMORPH is a modular simulation tool for building synaptically
connected networks with realistic neuron morphologies.  Axonal and
dendritic morphologies are created by using stochastic rules for the
behavior of individual growth cones, the structures at the tip of
outgrowing axons and dendrites (collectively called neurites) that
mediate neurite elongation and branching. In brief, each growth cone
has at each time step a probability to elongate the trailing neurite,
to branch and produce two daughter growth cones, and to turn and
change the direction of neurite outgrowth. The parameter values of the
outgrowth model can be optimized so as to obtain an optimal match with
the morphology of specific neuron types. Neurons are positioned in 3D
space and grow out independently of each other. Axons and dendrites
are not guided by any extracellular cues. Synapses between neurons are
formed when crossing axonal and dendritic segments come sufficiently
close to each other.

NETMORPH is written in C++ and tailored to a Unix operating
environment. Windows users can provide such an environment through
Cygwin. After compilation of NETMORPH, one can grow single-neuron
morphologies or networks of neurons with realistic morphologies. A
simulation run of NETMORPH is based on a script, a text file
containing the parameter values of the simulation. The output of
NETMORPH consists of a number of files specifying the generated neuron
morphologies and synaptic connectivity. Visualization of neurons and
networks can be done by a basic visualization tool incorporated in
NETMORPH or by a separate java program called NEURON3D.

Provided here are 1) the NETMORPH program (version 2011-06-24), 2) the
NETMORPH manual (updated 2014-04-03), 3) the visualization program
NEURON3D (file name: Neuron4D.rar), and 4) some documentation on
NEURON3D. The NETMORPH manual describes how NETMORPH can be installed,
provides a number of example scripts, and explains all the parameters
that control a NETMORPH simulation. NETMORPH was developed in the
Neuroinformatics Group at the Department of Integrative
Neurophysiology, VU University Amsterdam, The Netherlands, by Randal
Koene, Jaap van Pelt and Arjen van Ooyen, with assistance from Betty
Tijms, Peter van Hees, Frank Postma, Sander de Ridder, Sacha
Hoedemaker, Andrew Carnell and Pieter Laurens Baljon. The work was
supported by grants from the Netherlands Organization for Scientific
Research (CASPAN: 635.100.005) and the European Union (NEURoVERS-it:
019247; SECO: 216593) awarded to Jaap van Pelt and Arjen van Ooyen.

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[PubMed]

References and models cited by this paper

References and models that cite this paper

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

Ascoli GA, Krichmar JL (2000) L-Neuron: a modeling tool for the effcient generation and parsimonious description of dendritic morphology. Neurocomputing 32:1003-1011

Ascoli GA, Krichmar JL, Nasuto SJ, Senft SL (2001) Generation, description and storage of dendritic morphology data. Philos Trans R Soc Lond B Biol Sci 356:1131-45 [PubMed]

Ascoli GA, Krichmar JL, Scorcioni R, Nasuto SJ, Senft SL (2001) Computer generation and quantitative morphometric analysis of virtual neurons. Anat Embryol (Berl) 204:283-301 [PubMed]

Bamburg JR (2003) Introduction to cytoskeletal dynamics and pathfinding of neuronal growth cones. J Histochem Cytochem 51:407-9 [PubMed]

Belmonte MK, Bourgeron T (2006) Fragile X syndrome and autism at the intersection of genetic and neural networks. Nat Neurosci 9:1221-5 [PubMed]

Braitenberg V, Schuz A (1998) Cortex Statistics and Geometry of Neuronal Connectivity 2nd ed

Butz M, Lehmann K, Dammasch IE, Teuchert-Noodt G (2006) A theoretical network model to analyse neurogenesis and synaptogenesis in the dentate gyrus. Neural Netw 19:1490-505 [PubMed]

Costa Lda F, Manoel ET, Faucereau F, Chelly J, van Pelt J, Ramakers G (2002) A shape analysis framework for neuromorphometry. Network 13:283-310 [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]

Douglas RJ, Martin KA (2004) Neuronal circuits of the neocortex. Annu Rev Neurosci 27:419-51 [PubMed]

Eberhard JP, Wanner A, Wittum G (2006) NeuGen: a tool for the generation of realistic morphology of cortical neurons and neural networks in 3D Neurocomputing 70:327-342 [Journal]

Fields RD, Itoh K (1996) Neural cell adhesion molecules in activity-dependent development and synaptic plasticity. Trends Neurosci 19:473-80 [PubMed]

Gleeson P, Steuber V, Silver RA (2007) neuroConstruct: a tool for modeling networks of neurons in 3D space. Neuron 54:219-35 [Journal] [PubMed]

Goldberg DJ, Burmeister DW (1989) Looking into growth cones. Trends Neurosci 12:503-6 [PubMed]

Goodhill GJ (1998) Mathematical guidance for axons. Trends Neurosci 21:226-31 [PubMed]

Gordon-Weeks PR (2000) Neuronal growth cones

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]

Hellwig B (2000) A quantitative analysis of the local connectivity between pyramidal neurons in layers 2-3 of the rat visual cortex. Biol Cybern 82:111-21 [PubMed]

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 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

Hillman DE (1988) Parameters of dendritic shape and substructure Intrinsic and extrinsic determination? Intrinsic determinants of neuronal form and function. :83-113

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

Isbister CM, O'Connor TP (1999) Filopodial adhesion does not predict growth cone steering events in vivo J Neurosci. 19(7):2589-600 [PubMed]

Jan YN, Jan LY (2003) The control of dendrite development. Neuron 40:229-42 [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

Konur S, Ghosh A (2005) Calcium signaling and the control of dendritic development. Neuron 46:401-5 [PubMed]

Kowalski RJ, Williams RC (1993) Microtubule-associated protein 2 alters the dynamic properties of microtubule assembly and disassembly. J Biol Chem 268:9847-55 [PubMed]

Lamoureux P, Buxbaum RE, Heidemann SR (1998) Axonal outgrowth of cultured neurons is not limited by growth cone competition. J Cell Sci 111 ( Pt 21):3245-52 [PubMed]

Larkman AU (1991) Dendritic morphology of pyramidal neurones of the visual cortex of the rat: I. Branching patterns. J Comp Neurol 306:307-19 [PubMed]

Larkman AU, Major G, Stratford KJ, Jack JJ (1992) Dendritic morphology of pyramidal neurones of the visual cortex of the rat. IV: Electrical geometry. J Comp Neurol 323:137-52 [PubMed]

Le Be JV, Silberberg G, Wang Y, Markram H (2007) Morphological, electrophysiological, and synaptic properties of corticocallosal pyramidal cells in the neonatal rat neocortex. Cereb Cortex 17:2204-13 [PubMed]

Luczak A (2006) Spatial embedding of neuronal trees modeled by diffusive growth. J Neurosci Methods 157:132-41 [PubMed]

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

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

Polinsky M, Balazovich K, Tosney KW (2000) Identification of an invariant response: stable contact with schwann cells induces veil extension in sensory growth cones. J Neurosci 20:1044-55 [PubMed]

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

Ramakers GJ, Winter J, Hoogland TM, Lequin MB, van Hulten P, van Pelt J, Pool CW (1998) Depolarization stimulates lamellipodia formation and axonal but not dendritic branching in cultured rat cerebral cortex neurons. Brain Res Dev Brain Res 108:205-16 [PubMed]

Sanchez C, Diaz-Nido J, Avila J (2000) Phosphorylation of microtubule-associated protein 2 (MAP2) and its relevance for the regulation of the neuronal cytoskeleton function. Prog Neurobiol 61:133-68 [PubMed]

Scheff SW, Price DA, Schmitt FA, DeKosky ST, Mufson EJ (2007) Synaptic alterations in CA1 in mild Alzheimer disease and mild cognitive impairment. Neurology 68:1501-8 [PubMed]

Schierwagen A, Grantyn R (1986) Quantitative morphological analysis of deep superior colliculus neurons stained intracellularly with HRP in the cat. J Hirnforsch 27:611-23 [PubMed]

Schubert D, Kötter R, Luhmann HJ, Staiger JF (2006) Morphology, electrophysiology and functional input connectivity of pyramidal neurons characterizes a genuine layer va in the primary somatosensory cortex. Cereb Cortex 16:223-36 [PubMed]

   [31 reconstructed morphologies on NeuroMorpho.Org]

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

Senft SL, Ascoli GA (1999) Reconstruction of brain networks by algorithmic amplification of morphometry data Lecture Notes In Computer Science 1606:25-33

Shepherd GM, Svoboda K (2005) Laminar and columnar organization of ascending excitatory projections to layer 2-3 pyramidal neurons in rat barrel cortex. J Neurosci 25:5670-9 [PubMed]

   [66 reconstructed morphologies on NeuroMorpho.Org]

Sporns O, Chialvo DR, Kaiser M, Hilgetag CC (2004) Organization, development and function of complex brain networks. Trends Cogn Sci 8:418-25 [PubMed]

Stepanyants A, Chklovskii DB (2005) Neurogeometry and potential synaptic connectivity. Trends Neurosci 28:387-94 [PubMed]

Stepanyants A, Tamás G, Chklovskii DB (2004) Class-specific features of neuronal wiring. Neuron 43:251-9 [PubMed]

Uylings HB, Smit GJ (1975) Three-dimensional branching structure of pyramidal cell dendrites. Brain Res 87:55-60 [PubMed]

Uylings HB, van Pelt J (2002) Measures for quantifying dendritic arborizations. Network 13:397-414 [PubMed]

Uylings HB, van Pelt J, Parnavelas JG, Ruiz-Marcos A (1994) Geometrical and topological characteristics in the dendritic development of cortical pyramidal and non-pyramidal neurons. Prog Brain Res 102:109-23

van Ooyen A, van Pelt J (1994) Activity-dependent neurite outgrowth and neural network development. Prog Brain Res 102:245-59

van Ooyen A, van Pelt J (1996) Complex periodic behaviour in a neural network model with activity-dependent neurite outgrowth. J Theor Biol 179:229-42 [PubMed]

Van Ooyen A, Van Pelt J, Corner MA (1995) Implications of activity dependent neurite outgrowth for neuronal morphology and network development. J Theor Biol 172:63-82 [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 (2002) Branching rates and growth functions in the outgrowth of dendritic branching patterns. Network 13:261-81 [PubMed]

Van Pelt J, Uylings HB, Verwer RW, Pentney RJ, Woldenberg MJ (1992) Tree asymmetry--a sensitive and practical measure for binary topological trees. Bull Math Biol 54:759-84 [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, van Ooyen A, Uylings HB (2001) The need for integrating neuronal morphology databases and computational environments in exploring neuronal structure and function. Anat Embryol (Berl) 204:255-65 [PubMed]

van Veen MP, van Pelt J (1993) Terminal and intermediate segment lengths in neuronal trees with finite length. Bull Math Biol 55:277-94 [PubMed]

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

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

Van_pelt J, Schierwagen A, Uylings HBM (2001) Modeling dendritic morphological complexity of cat superior colliculus neurons Neurocomputing 38:403-408

Van_pelt J, Uylings HBM (2007) Modeling Biology-Structures, Behaviors, Evolution, chapter Modeling Neuronal Growth and Shape :195-215

Wang Y, Gupta A, Toledo-Rodriguez M, Wu CZ, Markram H (2002) Anatomical, physiological, molecular and circuit properties of nest basket cells in the developing somatosensory cortex. Cereb Cortex 12:395-410 [PubMed]

   [204 reconstructed morphologies on NeuroMorpho.Org]

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]

Maki-Marttunen T, Acimovic J, Ruohonen K, Linne ML (2013) Structure-Dynamics Relationships in Bursting Neuronal Networks Revealed Using a Prediction Framework PLOS ONE 8(7):e69373 [Journal]

   Structure-dynamics relationships in bursting neuronal networks revealed (Mäki-Marttunen et al. 2013) [Model]

Parekh R, Ascoli GA (2013) Neuronal morphology goes digital: a research hub for cellular and system neuroscience. Neuron 77:1017-38 [Journal] [PubMed]

   Neuronal morphology goes digital ... (Parekh & Ascoli 2013) [Model]

Schneider CJ, Cuntz H, Soltesz I (2014) Linking Macroscopic with Microscopic Neuroanatomy Using Synthetic Neuronal Populations. PLoS Comput Biol 10:e1003921 [Journal] [PubMed]

   Generation of granule cell dendritic morphology (Schneider 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]

van Ooyen A, Carnell A, de Ridder S, Tarigan B, Mansvelder HD, Bijma F, de Gunst M, van Pelt (2014) Independently outgrowing neurons and geometry-based synapse formation produce networks with realistic synaptic connectivity. PLoS One 9:e85858 [Journal] [PubMed]

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

(73 refs)

van Ooyen A, Carnell A, de Ridder S, Tarigan B, Mansvelder HD, Bijma F, de Gunst M, van Pelt (2014) Independently outgrowing neurons and geometry-based synapse formation produce networks with realistic synaptic connectivity. PLoS One 9:e85858[PubMed]

References and models cited by this paper

References and models that cite this paper

Amirikian B (2005) A phenomenological theory of spatially structured local synaptic connectivity. PLoS Comput Biol 1:e11 [PubMed]

Arendt T, Schindler C, Bruckner MK, Eschrich K, Bigl V, Zedlick D, Marcova L (1997) Plastic neuronal remodeling is impaired in patients with Alzheimer's disease carrying apolipoprotein epsilon 4 allele. J Neurosci 17:516-29 [PubMed]

Ascoli GA (2006) Mobilizing the base of neuroscience data: the case of neuronal morphologies. Nat Rev Neurosci 7:318-24 [PubMed]

Barabási AL (2009) Scale-free networks: a decade and beyond. Science 325:412-3 [PubMed]

Bassett DS, Bullmore E (2006) Small-world brain networks. Neuroscientist 12:512-23 [PubMed]

Benson DL, Colman DR, Huntley GW (2001) Molecules, maps and synapse specificity. Nat Rev Neurosci 2:899-909 [PubMed]

Bettencourt LM, Stephens GJ, Ham MI, Gross GW (2007) Functional structure of cortical neuronal networks grown in vitro. Phys Rev E Stat Nonlin Soft Matter Phys 75:021915-34 [PubMed]

Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10:186-98 [PubMed]

Chen W, Maex R, Adams R, Steuber V, Calcraft L, Davey N (2011) Clustering predicts memory performance in networks of spiking and non-spiking neurons. Front Comput Neurosci 5:14 [PubMed]

Chklovskii DB, Mel BW, Svoboda K (2004) Cortical rewiring and information storage. Nature 431:782-8 [PubMed]

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

Cook SC, Wellman CL (2004) Chronic stress alters dendritic morphology in rat medial prefrontal cortex. J Neurobiol 60:236-48 [PubMed]

Costa Lda F, Manoel ET, Faucereau F, Chelly J, van Pelt J, Ramakers G (2002) A shape analysis framework for neuromorphometry. Network 13:283-310 [PubMed]

Courchesne E, Redcay E, Morgan JT, Kennedy DP (2005) Autism at the beginning: microstructural and growth abnormalities underlying the cognitive and behavioral phenotype of autism. Dev Psychopathol 17:577-97 [PubMed]

Cullen TJ, Walker MA, Eastwood SL, Esiri MM, Harrison PJ, Crow TJ (2006) Anomalies of asymmetry of pyramidal cell density and structure in dorsolateral prefrontal cortex in schizophrenia. Br J Psychiatry 188:26-31 [PubMed]

da Silva S, Wang F (2011) Retrograde neural circuit specification by target-derived neurotrophins and growth factors. Curr Opin Neurobiol 21:61-7 [PubMed]

Feldmeyer D, bke J, Silver RA, Sakmann B (2002) Synaptic connections between layer 4 spiny neurone-layer 2-3 pyramidal cell pairs in juvenile rat barrel cortex: physiology and anatomy of interlaminar signalling within a cortical column. J Physiol 538:803-22 [PubMed]

Gaiteri C, Rubin JE (2011) The interaction of intrinsic dynamics and network topology in determining network burst synchrony. Front Comput Neurosci 5:10 [PubMed]

Gerhard F, Pipa G, Lima B, Neuenschwander S, Gerstner W (2011) Extraction of Network Topology From Multi-Electrode Recordings: Is there a Small-World Effect? Front Comput Neurosci 5:4-25 [PubMed]

He Y, Chen ZJ, Evans AC (2007) Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. Cereb Cortex 17:2407-19 [PubMed]

Hellwig B (2000) A quantitative analysis of the local connectivity between pyramidal neurons in layers 2-3 of the rat visual cortex. Biol Cybern 82:111-21 [PubMed]

Hill SL, Wang Y, Riachi I, Schurmann F, Markram H (2012) Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits. Proc Natl Acad Sci U S A 109:E2885-94 [PubMed]

Holmgren C, Harkany T, Svennenfors B, Zilberter Y (2003) Pyramidal cell communication within local networks in layer 2-3 of rat neocortex. J Physiol 551:139-53 [PubMed]

Isbister CM, O'Connor TP (1999) Filopodial adhesion does not predict growth cone steering events in vivo J Neurosci. 19(7):2589-600 [PubMed]

Kaiser M, Hilgetag CC, van Ooyen A (2009) A simple rule for axon outgrowth and synaptic competition generates realistic connection lengths and filling fractions. Cereb Cortex 19:3001-10 [PubMed]

Kaufmann WE, Moser HW (2000) Dendritic anomalies in disorders associated with mental retardation. Cereb Cortex 10:981-91 [PubMed]

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]

Kvajo M, McKellar H, Arguello PA, Drew LJ, Moore H, MacDermott AB, Karayiorgou M, Gogos JA (2008) A mutation in mouse Disc1 that models a schizophrenia risk allele leads to specific alterations in neuronal architecture and cognition. Proc Natl Acad Sci U S A 105:7076-81 [PubMed]

Lago-Fernandez LF, Huerta R, Corbacho F, Siguenza JA (2000) Fast response and temporal coherent oscillations in small-world networks. Phys Rev Lett 84:2758-61 [PubMed]

Larkman AU (1991) Dendritic morphology of pyramidal neurones of the visual cortex of the rat: I. Branching patterns. J Comp Neurol 306:307-19 [PubMed]

Le Be JV, Silberberg G, Wang Y, Markram H (2007) Morphological, electrophysiological, and synaptic properties of corticocallosal pyramidal cells in the neonatal rat neocortex. Cereb Cortex 17:2204-13 [PubMed]

Liu Y, Liang M, Zhou Y, He Y, Hao Y, Song M, Yu C, Liu H, Liu Z, Jiang T (2008) Disrupted small-world networks in schizophrenia. Brain 131:945-61 [PubMed]

Lohmann H, Rörig B (1994) Long-range horizontal connections between supragranular pyramidal cells in the extrastriate visual cortex of the rat. J Comp Neurol 344:543-58 [PubMed]

Maass W, Natschlager T, Markram H (2002) Real-time computing without stable states: a new framework for neural computation based on perturbations. Neural Comput 14:2531-60 [PubMed]

Magarinos AM, McEwen BS, Flugge G, Fuchs E (1996) Chronic psychosocial stress causes apical dendritic atrophy of hippocampal CA3 pyramidal neurons in subordinate tree shrews. J Neurosci 16:3534-40 [PubMed]

Magee JC (2000) Dendritic integration of excitatory synaptic input. Nat Rev Neurosci 1:181-90 [PubMed]

Micheloyannis S, Pachou E, Stam CJ, Breakspear M, Bitsios P, Vourkas M, Erimaki S, Zervakis M (2006) Small-world networks and disturbed functional connectivity in schizophrenia. Schizophr Res 87:60-6 [PubMed]

Moolman DL, Vitolo OV, Vonsattel JP, Shelanski ML (2004) Dendrite and dendritic spine alterations in Alzheimer models. J Neurocytol 33:377-87 [PubMed]

Morelli LG, Abramson G, Kuperman MN (2004) Associative memory on a small-world neural network Eur Phys J 38:495-500

Neymotin SA, Jacobs KM, Fenton AA, Lytton WW (2011) Synaptic information transfer in computer models of neocortical columns. J Comput Neurosci. 30(1):69-84 [Journal] [PubMed]

   Synaptic information transfer in computer models of neocortical columns (Neymotin et al. 2010) [Model]

Nuñez JL, Kim BY, Juraska JM (1998) Neonatal cryoanesthesia affects the morphology of the visual cortex in the adult rat. Brain Res Dev Brain Res 111:89-98 [PubMed]

Perin R, Berger TK, Markram H (2011) A synaptic organizing principle for cortical neuronal groups. Proc Natl Acad Sci U S A 108:5419-24 [PubMed]

   [289 reconstructed morphologies on NeuroMorpho.Org]

Pernice V, Staude B, Cardanobile S, Rotter S (2011) How structure determines correlations in neuronal networks. PLoS Comput Biol 7:e1002059 [PubMed]

Polinsky M, Balazovich K, Tosney KW (2000) Identification of an invariant response: stable contact with schwann cells induces veil extension in sensory growth cones. J Neurosci 20:1044-55 [PubMed]

Polleux F (2005) Genetic mechanisms specifying cortical connectivity: let's make some projections together. Neuron 46:395-400 [PubMed]

Radley JJ, Sisti HM, Hao J, Rocher AB, McCall T, Hof PR, McEwen BS, Morrison JH (2004) Chronic behavioral stress induces apical dendritic reorganization in pyramidal neurons of the medial prefrontal cortex. Neuroscience 125:1-6 [PubMed]

Roxin A (2011) The role of degree distribution in shaping the dynamics in networks of sparsely connected spiking neurons. Front Comput Neurosci 5:8 [PubMed]

Shepherd GM, Svoboda K (2005) Laminar and columnar organization of ascending excitatory projections to layer 2-3 pyramidal neurons in rat barrel cortex. J Neurosci 25:5670-9 [PubMed]

   [66 reconstructed morphologies on NeuroMorpho.Org]

Song S, Sjostrom PJ, Reigl M, Nelson S, Chklovskii DB (2005) Highly nonrandom features of synaptic connectivity in local cortical circuits. PLoS Biol 3:e68-88 [PubMed]

Sousa N, Lukoyanov NV, Madeira MD, Almeida OF, Paula-Barbosa MM (2000) Reorganization of the morphology of hippocampal neurites and synapses after stress-induced damage correlates with behavioral improvement. Neuroscience 97:253-66 [PubMed]

Sporns O, Chialvo DR, Kaiser M, Hilgetag CC (2004) Organization, development and function of complex brain networks. Trends Cogn Sci 8:418-25 [PubMed]

Sporns O, Tononi G, Edelman GM (2000) Theoretical neuroanatomy: relating anatomical and functional connectivity in graphs and cortical connection matrices. Cereb Cortex 10:127-41 [PubMed]

Sporns O, Zwi JD (2004) The small world of the cerebral cortex. Neuroinformatics 2:145-62 [PubMed]

Stam CJ, Reijneveld JC (2007) Graph theoretical analysis of complex networks in the brain. Nonlinear Biomed Phys 1:3 [PubMed]

Stepanyants A, Chklovskii DB (2005) Neurogeometry and potential synaptic connectivity. Trends Neurosci 28:387-94 [PubMed]

Stepanyants A, Tamás G, Chklovskii DB (2004) Class-specific features of neuronal wiring. Neuron 43:251-9 [PubMed]

Supekar K, Menon V, Rubin D, Musen M, Greicius MD (2008) Network analysis of intrinsic functional brain connectivity in Alzheimer's disease. PLoS Comput Biol 4:e1000100 [PubMed]

Takahashi N, Sasaki T, Matsumoto W, Matsuki N, Ikegaya Y (2010) Circuit topology for synchronizing neurons in spontaneously active networks. Proc Natl Acad Sci U S A 107:10244-9 [PubMed]

Tessier-Lavigne M (1994) Axon guidance by diffusible repellants and attractants. Curr Opin Genet Dev 4:596-601 [PubMed]

Tigerholm J, Migliore M, Fransén E (2013) Integration of synchronous synaptic input in CA1 pyramidal neuron depends on spatial and temporal distributions of the input. Hippocampus 23:87-99 [PubMed]

Uylings HB, van Pelt J, Parnavelas JG, Ruiz-Marcos A (1994) Geometrical and topological characteristics in the dendritic development of cortical pyramidal and non-pyramidal neurons. Prog Brain Res 102:109-23

van den Heuvel MP, Sporns O (2011) Rich-club organization of the human connectome. J Neurosci 31:15775-86 [PubMed]

van Pelt J, Carnell A, de Ridder S, Mansvelder HD, van Ooyen A (2010) An algorithm for finding candidate synaptic sites in computer generated networks of neurons with realistic morphologies. Front Comput Neurosci 4:148 [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, van Ooyen A, Uylings HB (2001) The need for integrating neuronal morphology databases and computational environments in exploring neuronal structure and function. Anat Embryol (Berl) 204:255-65 [PubMed]

Voges N, Perrinet L (2012) Complex dynamics in recurrent cortical networks based on spatially realistic connectivities. Front Comput Neurosci 6:41 [PubMed]

Watts DJ, Strogatz SH (1998) Collective dynamics of 'small-world' networks. Nature 393:440-2 [PubMed]

Yamada M, Wada Y, Tsukagoshi H, Otomo E, Hayakawa M (1988) A quantitative Golgi study of basal dendrites of hippocampal CA1 pyramidal cells in senile dementia of Alzheimer type. J Neurol Neurosurg Psychiatry 51:1088-90 [PubMed]

Yu S, Huang D, Singer W, Nikolic D (2008) A small world of neuronal synchrony. Cereb Cortex 18:2891-901 [PubMed]

Reimann MW, King JG, Muller EB, Ramaswamy S, Markram H (2015) An algorithm to predict the connectome of neural microcircuits. Front Comput Neurosci 9:120 [Journal] [PubMed]

(70 refs)