Literature DB >> 21587288

Using theoretical models to analyse neural development.

Arjen van Ooyen1.   

Abstract

The development of the nervous system is an extremely complex and dynamic process. Through the continuous interplay of genetic information and changing intra- and extracellular environments, the nervous system constructs itself from precursor cells that divide and form neurons, which migrate, differentiate and establish synaptic connections. Our understanding of neural development can be greatly assisted by mathematical and computational modelling, because it allows us to bridge the gap between system-level dynamics and the lower level cellular and molecular processes. This Review shows the potential of theoretical models to examine many aspects of neural development.

Mesh:

Year:  2011        PMID: 21587288     DOI: 10.1038/nrn3031

Source DB:  PubMed          Journal:  Nat Rev Neurosci        ISSN: 1471-003X            Impact factor:   34.870


  158 in total

Review 1.  Towards a cellular and molecular understanding of neurulation.

Authors:  J F Colas; G C Schoenwolf
Journal:  Dev Dyn       Date:  2001-06       Impact factor: 3.780

Review 2.  Neuronal polarity: until GSK-3 do us part.

Authors:  Rong Li
Journal:  Curr Biol       Date:  2005-03-29       Impact factor: 10.834

Review 3.  Molecular gradients and development of retinotopic maps.

Authors:  Todd McLaughlin; Dennis D M O'Leary
Journal:  Annu Rev Neurosci       Date:  2005       Impact factor: 12.449

4.  Quantifying neurite growth mediated by interactions among secretory vesicles, microtubules, and actin networks.

Authors:  Krasimira Tsaneva-Atanasova; Andrea Burgo; Thierry Galli; David Holcman
Journal:  Biophys J       Date:  2009-02       Impact factor: 4.033

Review 5.  A simple growth model constructs critical avalanche networks.

Authors:  L F Abbott; R Rohrkemper
Journal:  Prog Brain Res       Date:  2007       Impact factor: 2.453

6.  Polyneuronal innervation of skeletal muscle in new-born rats and its elimination during maturation.

Authors:  M C Brown; J K Jansen; D Van Essen
Journal:  J Physiol       Date:  1976-10       Impact factor: 5.182

7.  Effects of inhibition on neural network development through activity-dependent neurite outgrowth.

Authors:  C van Oss; A van Ooyen
Journal:  J Theor Biol       Date:  1997-03-21       Impact factor: 2.691

8.  Cholesterol modification of sonic hedgehog is required for long-range signaling activity and effective modulation of signaling by Ptc1.

Authors:  P M Lewis; M P Dunn; J A McMahon; M Logan; J F Martin; B St-Jacques; A P McMahon
Journal:  Cell       Date:  2001-06-01       Impact factor: 41.582

9.  Regulation of patched by sonic hedgehog in the developing neural tube.

Authors:  V Marigo; C J Tabin
Journal:  Proc Natl Acad Sci U S A       Date:  1996-09-03       Impact factor: 11.205

10.  Shootin1 interacts with actin retrograde flow and L1-CAM to promote axon outgrowth.

Authors:  Tadayuki Shimada; Michinori Toriyama; Kaori Uemura; Hiroyuki Kamiguchi; Tadao Sugiura; Naoki Watanabe; Naoyuki Inagaki
Journal:  J Cell Biol       Date:  2008-06-02       Impact factor: 10.539

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  41 in total

1.  A mathematical model for selective differentiation of neural progenitor cells on micropatterned polymer substrates.

Authors:  Cory L Howk; Howard A Levine; Michael W Smiley; Surya K Mallapragada; Marit Nilsen-Hamilton; Jisun Oh; Donald S Sakaguchi
Journal:  Math Biosci       Date:  2012-04-30       Impact factor: 2.144

2.  Cell types, network homeostasis, and pathological compensation from a biologically plausible ion channel expression model.

Authors:  Timothy O'Leary; Alex H Williams; Alessio Franci; Eve Marder
Journal:  Neuron       Date:  2014-05-21       Impact factor: 17.173

Review 3.  Micro-connectomics: probing the organization of neuronal networks at the cellular scale.

Authors:  Manuel Schröter; Ole Paulsen; Edward T Bullmore
Journal:  Nat Rev Neurosci       Date:  2017-02-02       Impact factor: 34.870

4.  Efficient simulations of tubulin-driven axonal growth.

Authors:  Stefan Diehl; Erik Henningsson; Anders Heyden
Journal:  J Comput Neurosci       Date:  2016-04-28       Impact factor: 1.621

Review 5.  Neuronal morphology goes digital: a research hub for cellular and system neuroscience.

Authors:  Ruchi Parekh; Giorgio A Ascoli
Journal:  Neuron       Date:  2013-03-20       Impact factor: 17.173

Review 6.  Quantitative investigations of axonal and dendritic arbors: development, structure, function, and pathology.

Authors:  Ruchi Parekh; Giorgio A Ascoli
Journal:  Neuroscientist       Date:  2014-06-27       Impact factor: 7.519

7.  Growth dynamics explain the development of spatiotemporal burst activity of young cultured neuronal networks in detail.

Authors:  Taras A Gritsun; Joost le Feber; Wim L C Rutten
Journal:  PLoS One       Date:  2012-09-19       Impact factor: 3.240

8.  How neurons migrate: a dynamic in-silico model of neuronal migration in the developing cortex.

Authors:  Yaki Setty; Chih-Chun Chen; Maria Secrier; Nikita Skoblov; Dimitrios Kalamatianos; Stephen Emmott
Journal:  BMC Syst Biol       Date:  2011-09-30

9.  Language development after cochlear implantation: an epigenetic model.

Authors:  Timothy M Markman; Alexandra L Quittner; Laurie S Eisenberg; Emily A Tobey; Donna Thal; John K Niparko; Nae-Yuh Wang
Journal:  J Neurodev Disord       Date:  2011-11-19       Impact factor: 4.025

10.  A neural network model of ventriloquism effect and aftereffect.

Authors:  Elisa Magosso; Cristiano Cuppini; Mauro Ursino
Journal:  PLoS One       Date:  2012-08-03       Impact factor: 3.240

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