c302: a multiscale framework for modelling the nervous system of Caenorhabditis elegans

The OpenWorm project has the ambitious goal of producing a highly detailed in silico model of the nematode Caenorhabditis elegans. A crucial part of this work will be a model of the nervous system encompassing all known cell types and connections. The appropriate level of biophysical detail required in the neuronal model to reproduce observed high-level behaviours in the worm has yet to be determined. For this reason, we have developed a framework, c302, that allows different instances of neuronal networks to be generated incorporating varying levels of anatomical and physiological detail, which can be investigated and refined independently or linked to other tools developed in the OpenWorm modelling toolchain. This article is part of a discussion meeting issue ‘Connectome to behaviour: modelling C. elegans at cellular resolution’.

[1]  Tim Gollisch,et al.  Modeling Single-Neuron Dynamics and Computations: A Balance of Detail and Abstraction , 2006, Science.

[2]  R. Kerr,et al.  A consistent muscle activation strategy underlies crawling and swimming in Caenorhabditis elegans , 2015, Journal of The Royal Society Interface.

[3]  R. Prevedel,et al.  Brain-wide 3D imaging of neuronal activity in Caenorhabditis elegans with sculpted light , 2013, Nature Methods.

[4]  Michael L. Hines,et al.  NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail , 2010, PLoS Comput. Biol..

[5]  E. Jorgensen,et al.  Graded synaptic transmission at the Caenorhabditis elegans neuromuscular junction , 2009, Proceedings of the National Academy of Sciences.

[6]  L. Ségalat,et al.  Characterization of K+ currents using an in situ patch clamp technique in body wall muscle cells from Caenorhabditis elegans , 2002, The Journal of physiology.

[7]  Eugene M. Izhikevich,et al.  Simple model of spiking neurons , 2003, IEEE Trans. Neural Networks.

[8]  Alon Korngreen,et al.  Markov modeling of ion channels: implications for understanding disease. , 2014, Progress in molecular biology and translational science.

[9]  Michael L. Hines,et al.  The NEURON Book , 2006 .

[10]  Lindy Holden-Dye,et al.  The Actions of Caenorhabditis elegans Neuropeptide-Like Peptides (NLPs) on Body Wall Muscle of Ascaris suum and Pharyngeal Muscle of C. elegans , 2008, Acta biologica Hungarica.

[11]  Stephen D. Larson,et al.  Application of smoothed particle hydrodynamics to modeling mechanisms of biological tissue , 2016, Adv. Eng. Softw..

[12]  Robert C. Cannon,et al.  LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2 , 2014, Front. Neuroinform..

[13]  J. Gjorgjieva,et al.  Neurobiology of Caenorhabditis elegans Locomotion: Where Do We Stand? , 2014, Bioscience.

[14]  Steven B Augustine,et al.  A stochastic neuronal model predicts random search behaviors at multiple spatial scales in C. elegans , 2016, eLife.

[15]  Hiroaki Kitano,et al.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..

[16]  Marc-Oliver Gewaltig,et al.  Current Practice in Software Development for Computational Neuroscience and How to Improve It , 2012, PLoS Comput. Biol..

[17]  Wulfram Gerstner,et al.  Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. , 2005, Journal of neurophysiology.

[18]  Michael L. Hines,et al.  Python in neuroscience , 2015, Front. Neuroinform..

[19]  R. Kerr,et al.  Optical Imaging of Calcium Transients in Neurons and Pharyngeal Muscle of C. elegans , 2000, Neuron.

[20]  Kimberly Van Auken,et al.  WormBase: a comprehensive resource for nematode research , 2009, Nucleic Acids Res..

[21]  Steven L. Brunton,et al.  Spatiotemporal Feedback and Network Structure Drive and Encode Caenorhabditis elegans Locomotion , 2017, PLoS Comput. Biol..

[22]  伏信 進矢,et al.  アイオワで computational な夏 , 2007 .

[23]  S. R. Wicks,et al.  A Dynamic Network Simulation of the Nematode Tap Withdrawal Circuit: Predictions Concerning Synaptic Function Using Behavioral Criteria , 1996, The Journal of Neuroscience.

[24]  Padraig Gleeson,et al.  Geppetto: a reusable modular open platform for exploring neuroscience data and models , 2018, Philosophical Transactions of the Royal Society B: Biological Sciences.

[25]  Michael L. Hines,et al.  Trends in Programming Languages for Neuroscience Simulations , 2009, Front. Neurosci..

[26]  Stephen D. Larson,et al.  Towards a virtual C. elegans: A framework for simulation and visualization of the neuromuscular system in a 3D physical environment , 2012, Silico Biol..

[27]  Michael L. Hines,et al.  Open Source Brain: A Collaborative Resource for Visualizing, Analyzing, Simulating, and Developing Standardized Models of Neurons and Circuits , 2018, Neuron.

[28]  Nicholas Cain,et al.  Inferring cortical function in the mouse visual system through large-scale systems neuroscience , 2016, Proceedings of the National Academy of Sciences.

[29]  Edward T. Bullmore,et al.  The Multilayer Connectome of Caenorhabditis elegans , 2016, PLoS Comput. Biol..

[30]  L. Ségalat,et al.  The L-type voltage-dependent Ca2+ channel EGL-19 controls body wall muscle function in Caenorhabditis elegans , 2002, The Journal of cell biology.

[31]  Randall D. Beer,et al.  An Integrated Neuromechanical Model of Steering in C. elegans , 2015, ECAL.

[32]  W. Wildman,et al.  Theoretical Neuroscience , 2014 .

[33]  Eric L. Schwartz,et al.  Computational Neuroscience , 1993, Neuromethods.

[34]  Andrew P. Davison,et al.  libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience , 2014, Front. Neuroinform..

[35]  Masahiro Kuramochi,et al.  A Computational Model Based on Multi-Regional Calcium Imaging Represents the Spatio-Temporal Dynamics in a Caenorhabditis elegans Sensory Neuron , 2017, PloS one.

[36]  Andrew P. Davison,et al.  A Commitment to Open Source in Neuroscience , 2017, Neuron.

[37]  Jordan H. Boyle,et al.  Gait Modulation in C. elegans: An Integrated Neuromechanical Model , 2012, Front. Comput. Neurosci..

[38]  Theodore H. Lindsay,et al.  Global Brain Dynamics Embed the Motor Command Sequence of Caenorhabditis elegans , 2015, Cell.

[39]  E. Marder,et al.  Similar network activity from disparate circuit parameters , 2004, Nature Neuroscience.

[40]  Aravinthan D. T. Samuel,et al.  Proprioceptive Coupling within Motor Neurons Drives C. elegans Forward Locomotion , 2012, Neuron.

[41]  Lav R. Varshney,et al.  Structural Properties of the Caenorhabditis elegans Neuronal Network , 2009, PLoS Comput. Biol..

[42]  Jordan H. Boyle,et al.  Caenorhabditis elegans body wall muscles are simple actuators , 2008, Biosyst..

[43]  Michael L. Hines,et al.  Open Source Brain: a collaborative resource for visualizing, analyzing, simulating and developing standardized models of neurons and circuits , 2018, bioRxiv.

[44]  Yee Lian Chew,et al.  Network control principles predict neuron function in the Caenorhabditis elegans connectome , 2017, Nature.

[45]  James G. King,et al.  Reconstruction and Simulation of Neocortical Microcircuitry , 2015, Cell.

[46]  S. Larson,et al.  Three-dimensional simulation of the Caenorhabditis elegans body and muscle cells in liquid and gel environments for behavioural analysis , 2018, Philosophical Transactions of the Royal Society B: Biological Sciences.

[47]  Paul W. Sternberg,et al.  Synaptic polarity of the interneuron circuit controlling C. elegans locomotion , 2013, Front. Comput. Neurosci..

[48]  Peter A. Appleby The role of multiple chemotactic mechanisms in a model of chemotaxis in C. elegans: different mechanisms are specialised for different environments , 2013, Journal of Computational Neuroscience.

[49]  Stephen D. Larson,et al.  OpenWorm: an open-science approach to modeling Caenorhabditis elegans , 2014, Front. Comput. Neurosci..

[50]  A. Hodgkin,et al.  A quantitative description of membrane current and its application to conduction and excitation in nerve , 1952, The Journal of physiology.