SIM-CE: An Advanced Simulink Platform for Studying the Brain of Caenorhabditis elegans

We introduce SIM-CE, an advanced, user-friendly modeling and simulation environment in Simulink for performing multi-scale behavioral analysis of the nervous system of Caenorhabditis elegans (C. elegans). SIM-CE contains an implementation of the mathematical models of C. elegans's neurons and synapses, in Simulink, which can be easily extended and particularized by the user. The Simulink model is able to capture both complex dynamics of ion channels and additional biophysical detail such as intracellular calcium concentration. We demonstrate the performance of SIM-CE by carrying out neuronal, synaptic and neural-circuit-level behavioral simulations. Such environment enables the user to capture unknown properties of the neural circuits, test hypotheses and determine the origin of many behavioral plasticities exhibited by the worm.

[1]  C. Koch,et al.  Methods in Neuronal Modeling: From Ions to Networks , 1998 .

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

[3]  A. Hodgkin,et al.  A quantitative description of membrane current and its application to conduction and excitation in nerve , 1990 .

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

[5]  Jessica Fuerst,et al.  Nerve Muscle And Synapse , 2016 .

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

[7]  D Schild,et al.  Small conductance potassium channels cause an activity-dependent spike frequency adaptation and make the transfer function of neurons logarithmic. , 1999, Biophysical journal.

[8]  S R Wicks,et al.  Effects of tap withdrawal response habituation on other withdrawal behaviors: the localization of habituation in the nematode Caenorhabditis elegans. , 1997, Behavioral neuroscience.

[9]  Yuishi Iwasaki,et al.  Quantitative Modeling of Neuronal Dynamics in C. elegans , 2010, ICONIP.

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

[11]  L. Salkoff,et al.  Potassium channels in C. elegans. , 2005, WormBook : the online review of C. elegans biology.

[12]  O. Hobert The neuronal genome of Caenorhabditis elegans. , 2013, WormBook : the online review of C. elegans biology.

[13]  J. Dormand,et al.  A family of embedded Runge-Kutta formulae , 1980 .

[14]  S. Brenner,et al.  The structure of the nervous system of the nematode Caenorhabditis elegans. , 1986, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[15]  Erik De Schutter,et al.  Computational Modeling Methods for Neuroscientists , 2009 .

[16]  Subhajyoti De,et al.  Dopamine Mediates Context-Dependent Modulation of Sensory Plasticity in C. elegans , 2007, Neuron.

[17]  Radu Grosu,et al.  Investigations on the Nervous System of Caenorhabditis elegans , 2016 .

[18]  Radu Grosu,et al.  Non-Associative Learning Representation in the Nervous System of the Nematode Caenorhabditis elegans , 2017, ArXiv.

[19]  F. Sesti,et al.  Auto‐phosphorylation of a voltage‐gated K+ channel controls non‐associative learning , 2009, The EMBO journal.

[20]  Evan L Ardiel,et al.  An elegant mind: learning and memory in Caenorhabditis elegans. , 2010, Learning & memory.

[21]  S. Lockery,et al.  Active Currents Regulate Sensitivity and Dynamic Range in C. elegans Neurons , 1998, Neuron.