Literature DB >> 21724619

Coping with variability in small neuronal networks.

Ronald L Calabrese1, Brian J Norris, Angela Wenning, Terrence M Wright.   

Abstract

Experimental and corresponding modeling studies indicate that there is a 2- to 5-fold variation of intrinsic and synaptic parameters across animals while functional output is maintained. Here, we review experiments, using the heartbeat central pattern generator (CPG) in medicinal leeches, which explore the consequences of animal-to-animal variation in synaptic strength for coordinated motor output. We focus on a set of segmental heart motor neurons that all receive inhibitory synaptic input from the same four premotor interneurons. These four premotor inputs fire in a phase progression and the motor neurons also fire in a phase progression because of differences in synaptic strength profiles of the four inputs among segments. Our work tested the hypothesis that functional output is maintained in the face of animal-to-animal variation in the absolute strength of connections because relative strengths of the four inputs onto particular motor neurons is maintained across animals. Our experiments showed that relative strength is not strictly maintained across animals even as functional output is maintained, and animal-to-animal variations in strength of particular inputs do not correlate strongly with output phase. Further experiments measured the precise temporal pattern of the premotor inputs, the segmental synaptic strength profiles of their connections onto motor neurons, and the temporal pattern (phase progression) of those motor neurons all in the same animal for a series of 12 animals. The analysis of input and output in this sample of 12 individuals suggests that the number (four) of inputs to each motor neuron and the variability of the temporal pattern of input from the CPG across individuals weaken the influence of the strength of individual inputs. Moreover, the temporal pattern of the output varies as much across individuals as that of the input. Essentially, each animal arrives at a unique solution for how the network produces functional output.

Mesh:

Year:  2011        PMID: 21724619      PMCID: PMC3223479          DOI: 10.1093/icb/icr074

Source DB:  PubMed          Journal:  Integr Comp Biol        ISSN: 1540-7063            Impact factor:   3.326


  26 in total

1.  Failure of averaging in the construction of a conductance-based neuron model.

Authors:  Jorge Golowasch; Mark S Goldman; L F Abbott; Eve Marder
Journal:  J Neurophysiol       Date:  2002-02       Impact factor: 2.714

2.  Heartbeat control in leeches. I. Constriction pattern and neural modulation of blood pressure in intact animals.

Authors:  Angela Wenning; Gennady S Cymbalyuk; Ronald L Calabrese
Journal:  J Neurophysiol       Date:  2003-09-17       Impact factor: 2.714

Review 3.  Neuronal control of leech behavior.

Authors:  William B Kristan; Ronald L Calabrese; W Otto Friesen
Journal:  Prog Neurobiol       Date:  2005-11-02       Impact factor: 11.685

4.  Similar network activity from disparate circuit parameters.

Authors:  Astrid A Prinz; Dirk Bucher; Eve Marder
Journal:  Nat Neurosci       Date:  2004-11-21       Impact factor: 24.884

Review 5.  Invertebrate central pattern generation moves along.

Authors:  Eve Marder; Dirk Bucher; David J Schulz; Adam L Taylor
Journal:  Curr Biol       Date:  2005-09-06       Impact factor: 10.834

Review 6.  Variability, compensation and homeostasis in neuron and network function.

Authors:  Eve Marder; Jean-Marc Goaillard
Journal:  Nat Rev Neurosci       Date:  2006-07       Impact factor: 34.870

7.  A central pattern generator producing alternative outputs: temporal pattern of premotor activity.

Authors:  Brian J Norris; Adam L Weaver; Lee G Morris; Angela Wenning; Paul A García; Ronald L Calabrese
Journal:  J Neurophysiol       Date:  2006-04-12       Impact factor: 2.714

8.  Variable channel expression in identified single and electrically coupled neurons in different animals.

Authors:  David J Schulz; Jean-Marc Goaillard; Eve Marder
Journal:  Nat Neurosci       Date:  2006-01-29       Impact factor: 24.884

Review 9.  Principles of rhythmic motor pattern generation.

Authors:  E Marder; R L Calabrese
Journal:  Physiol Rev       Date:  1996-07       Impact factor: 37.312

10.  Constancy and variability in the output of a central pattern generator.

Authors:  Brian J Norris; Angela Wenning; Terrence Michael Wright; Ronald L Calabrese
Journal:  J Neurosci       Date:  2011-03-23       Impact factor: 6.167

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  27 in total

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Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2012-05-11       Impact factor: 1.836

2.  Motor neuronal activity varies least among individuals when it matters most for behavior.

Authors:  Miranda J Cullins; Kendrick M Shaw; Jeffrey P Gill; Hillel J Chiel
Journal:  J Neurophysiol       Date:  2014-11-19       Impact factor: 2.714

Review 3.  Biodiversity Meets Neuroscience: From the Sequencing Ship (Ship-Seq) to Deciphering Parallel Evolution of Neural Systems in Omic's Era.

Authors:  Leonid L Moroz
Journal:  Integr Comp Biol       Date:  2015-07-10       Impact factor: 3.326

4.  Distributions of active spinal cord neurons during swimming and scratching motor patterns.

Authors:  Jonathan W Mui; Katie L Willis; Zhao-Zhe Hao; Ari Berkowitz
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2012-09-18       Impact factor: 1.836

5.  Animal-to-animal variability in the phasing of the crustacean cardiac motor pattern: an experimental and computational analysis.

Authors:  Alex H Williams; Molly A Kwiatkowski; Adam L Mortimer; Eve Marder; Mary Lou Zeeman; Patsy S Dickinson
Journal:  J Neurophysiol       Date:  2013-02-27       Impact factor: 2.714

6.  Variation in motor output and motor performance in a centrally generated motor pattern.

Authors:  Angela Wenning; Brian J Norris; Anca Doloc-Mihu; Ronald L Calabrese
Journal:  J Neurophysiol       Date:  2014-04-09       Impact factor: 2.714

Review 7.  Consequences of degeneracy in network function.

Authors:  Elizabeth C Cropper; Andrew M Dacks; Klaudiusz R Weiss
Journal:  Curr Opin Neurobiol       Date:  2016-08-31       Impact factor: 6.627

Review 8.  Neuromechanical principles underlying movement modularity and their implications for rehabilitation.

Authors:  Lena H Ting; Hillel J Chiel; Randy D Trumbower; Jessica L Allen; J Lucas McKay; Madeleine E Hackney; Trisha M Kesar
Journal:  Neuron       Date:  2015-04-08       Impact factor: 17.173

Review 9.  Neuromodulation of neuronal circuits: back to the future.

Authors:  Eve Marder
Journal:  Neuron       Date:  2012-10-04       Impact factor: 17.173

10.  Convergent neuromodulation onto a network neuron can have divergent effects at the network level.

Authors:  Nickolas Kintos; Michael P Nusbaum; Farzan Nadim
Journal:  J Comput Neurosci       Date:  2016-01-21       Impact factor: 1.621

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