2023
Tutorial: using NEURON for neuromechanical simulations
Fietkiewicz C, McDougal R, Marco D, Chiel H, Thomas P. Tutorial: using NEURON for neuromechanical simulations. Frontiers In Computational Neuroscience 2023, 17: 1143323. PMID: 37583894, PMCID: PMC10424731, DOI: 10.3389/fncom.2023.1143323.Peer-Reviewed Original ResearchUse of pointersCode modularityCode reuseSeparate specificationComplex adaptive behaviorSimulation platformDifferent computational modelsComplicated syntaxClosed-loop modelSimulation toolNeuromechanical modelingNeuron simulationsLevel of complexityComputational modelNeuromechanical simulationsTutorialPointersNon-smooth dynamicsPedagogical modelNeural dynamicsProgramming optionsBody dynamicsModelingAdaptive behaviorFirst step
2019
NetPyNE, a tool for data-driven multiscale modeling of brain circuits
Dura-Bernal S, Suter BA, Gleeson P, Cantarelli M, Quintana A, Rodriguez F, Kedziora DJ, Chadderdon GL, Kerr CC, Neymotin SA, McDougal RA, Hines M, Shepherd GM, Lytton WW. NetPyNE, a tool for data-driven multiscale modeling of brain circuits. ELife 2019, 8: e44494. PMID: 31025934, PMCID: PMC6534378, DOI: 10.7554/elife.44494.Peer-Reviewed Original ResearchConceptsInformation-theoretic measuresDeclarative languageImplementation codeGraphical interfaceNetPyNENetwork parametersTheoretic measuresNetwork modelNeuron networkStandardized formatUsersMillions of cellsConnectivity rulesExperimental datasetsNetworkRaster plotMultiscale network modelMultiple scalesDatasetToolModelersSpecificationModel parametersModelingVisualization
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