Model of the Xenopus tadpole swimming spinal network (Roberts et al. 2014)

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This is a NEURON-python and MATLAB simulation code for generating anatomical or probabilistic connectivity and simulating the neuronal dynamics of the neuronal network controlling swimming in Xenopus tadpoles. For more details about this model, see Ferrario et al, 2018, eLife and Roberts et al, 2014, J of Neurosci
1 . Ferrario A, Merrison-Hort R, Soffe SR, Borisyuk R (2018) Structural and functional properties of a probabilistic model of neuronal connectivity in a simple locomotor network. Elife [PubMed]
2 . Roberts A, Conte D, Hull M, Merrison-Hort R, al Azad AK, Buhl E, Borisyuk R, Soffe SR (2014) Can simple rules control development of a pioneer vertebrate neuronal network generating behavior? J Neurosci 34:608-21 [PubMed]
3 . Borisyuk R, Al Azad AK, Conte D, Roberts A, Soffe SR (2014) A developmental approach to predicting neuronal connectivity from small biological datasets: a gradient-based neuron growth model. PLoS One 9:e89461 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Axon;
Brain Region(s)/Organism:
Cell Type(s): Hodgkin-Huxley neuron;
Channel(s): I_Ks; I Potassium; I Calcium;
Gap Junctions: Gap junctions;
Receptor(s): AMPA; Gaba; NMDA;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: MATLAB; NEURON;
Model Concept(s): Activity Patterns; Connectivity matrix; Oscillations;
Implementer(s): Ferrario, Andrea [andrea.ferrario at]; Borisyuk, Roman [rborisyuk at]; Merrison-Hort, Robert ;
Search NeuronDB for information about:  AMPA; NMDA; Gaba; I Calcium; I Potassium; I_Ks; Gaba; Glutamate;
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