Literature DB >> 16553310

Complexities and uncertainties of neuronal network function.

David Parker1.   

Abstract

The nervous system generates behaviours through the activity in groups of neurons assembled into networks. Understanding these networks is thus essential to our understanding of nervous system function. Understanding a network requires information on its component cells, their interactions and their functional properties. Few networks come close to providing complete information on these aspects. However, even if complete information were available it would still only provide limited insight into network function. This is because the functional and structural properties of a network are not fixed but are plastic and can change over time. The number of interacting network components, their (variable) functional properties, and various plasticity mechanisms endows networks with considerable flexibility, but these features inevitably complicate network analyses. This review will initially discuss the general approaches and problems of network analyses. It will then examine the success of these analyses in a model spinal cord locomotor network in the lamprey, to determine to what extent in this relatively simple vertebrate system it is possible to claim detailed understanding of network function and plasticity.

Mesh:

Year:  2006        PMID: 16553310      PMCID: PMC1626546          DOI: 10.1098/rstb.2005.1779

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  91 in total

1.  Spinal motor circuits: merging development and function.

Authors:  K Sharma; C Y Peng
Journal:  Neuron       Date:  2001-02       Impact factor: 17.173

Review 2.  Spinal-Cord plasticity: independent and interactive effects of neuromodulator and activity-dependent plasticity.

Authors:  D Parker
Journal:  Mol Neurobiol       Date:  2000 Aug-Dec       Impact factor: 5.590

Review 3.  Non-mammalian models for studying neural development and function.

Authors:  Eve Marder
Journal:  Nature       Date:  2002-05-16       Impact factor: 49.962

4.  Variable properties in a single class of excitatory spinal synapse.

Authors:  David Parker
Journal:  J Neurosci       Date:  2003-04-15       Impact factor: 6.167

Review 5.  Neurobiology of lampreys.

Authors:  C M Rovainen
Journal:  Physiol Rev       Date:  1979-10       Impact factor: 37.312

6.  Ultrastructural characteristics of glutamatergic and GABAergic terminals in cat lamina IX before and after spinal cord injury.

Authors:  Q Tai; K Palazzolo; A Mautes; W Nacimiento; J P Kuhtz-Buschbeck; A C Nacimiento; H G Goshgarian
Journal:  J Spinal Cord Med       Date:  1997-07       Impact factor: 1.985

7.  Pax6 and engrailed 1 regulate two distinct aspects of renshaw cell development.

Authors:  Tamar Sapir; Eric J Geiman; Zhi Wang; Tomoko Velasquez; Sachiko Mitsui; Yoshihiro Yoshihara; Eric Frank; Francisco J Alvarez; Martyn Goulding
Journal:  J Neurosci       Date:  2004-02-04       Impact factor: 6.167

8.  Substance P modulates NMDA responses and causes long-term protein synthesis-dependent modulation of the lamprey locomotor network.

Authors:  D Parker; W Zhang; S Grillner
Journal:  J Neurosci       Date:  1998-06-15       Impact factor: 6.167

Review 9.  Distributed effects of dopamine modulation in the crustacean pyloric network.

Authors:  R M Harris-Warrick; B R Johnson; J H Peck; P Kloppenburg; A Ayali; J Skarbinski
Journal:  Ann N Y Acad Sci       Date:  1998-11-16       Impact factor: 5.691

10.  N-Methyl-D-aspartate (NMDA), kainate and quisqualate receptors and the generation of fictive locomotion in the lamprey spinal cord.

Authors:  L Brodin; S Grillner; C M Rovainen
Journal:  Brain Res       Date:  1985-01-28       Impact factor: 3.252

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  19 in total

Review 1.  Neuronal network analyses: premises, promises and uncertainties.

Authors:  David Parker
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-08-12       Impact factor: 6.237

2.  Shining light into the black box of spinal locomotor networks.

Authors:  Patrick J Whelan
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-08-12       Impact factor: 6.237

3.  The function of intersegmental connections in determining temporal characteristics of the spinal cord rhythmic output.

Authors:  A Ayali; E Fuchs; E Ben-Jacob; A Cohen
Journal:  Neuroscience       Date:  2007-05-16       Impact factor: 3.590

4.  On the derivation and tuning of phase oscillator models for lamprey central pattern generators.

Authors:  Péter L Várkonyi; Tim Kiemel; Kathleen Hoffman; Avis H Cohen; Philip Holmes
Journal:  J Comput Neurosci       Date:  2008-02-12       Impact factor: 1.621

5.  Segmental, synaptic actions of commissural interneurons in the mouse spinal cord.

Authors:  Katharina A Quinlan; Ole Kiehn
Journal:  J Neurosci       Date:  2007-06-13       Impact factor: 6.167

6.  Exciting times in the tadpole spinal cord.

Authors:  David Parker
Journal:  J Physiol       Date:  2009-04-15       Impact factor: 5.182

7.  Electrical stimulation therapies for CNS disorders and pain are mediated by competition between different neuronal networks in the brain.

Authors:  Carl L Faingold
Journal:  Med Hypotheses       Date:  2008-08-30       Impact factor: 1.538

8.  Resting state networks in human cervical spinal cord observed with fMRI.

Authors:  Pengxu Wei; Jianjun Li; Feng Gao; Derong Ye; Qin Zhong; Shujia Liu
Journal:  Eur J Appl Physiol       Date:  2009-09-24       Impact factor: 3.078

Review 9.  Flexibility in the patterning and control of axial locomotor networks in lamprey.

Authors:  James T Buchanan
Journal:  Integr Comp Biol       Date:  2011-07-09       Impact factor: 3.326

Review 10.  The role of mechanical resonance in the neural control of swimming in fishes.

Authors:  Eric D Tytell; Chia-Yu Hsu; Lisa J Fauci
Journal:  Zoology (Jena)       Date:  2013-12-21       Impact factor: 2.240

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