"... we present an integrated suite of open-source, multi-scale computational tools called PyRhO. The purpose of developing PyRhO is three-fold: (i) to characterize new (and existing) opsins by automatically fitting a minimal set of experimental data to three-, four-, or six-state kinetic models, (ii) to simulate these models at the channel, neuron and network levels, and (iii) provide functional insights through model selection and virtual experiments in silico. The module is written in Python with an additional IPython/Jupyter notebook based GUI, allowing models to be fit, simulations to be run and results to be shared through simply interacting with a webpage. The seamless integration of model fitting algorithms with simulation environments (including NEURON and Brian2) for these virtual opsins will enable neuroscientists to gain a comprehensive understanding of their behavior and rapidly identify the most suitable variant for application in a particular biological system. ..."
Model Type: Neuron or other electrically excitable cell; Channel/Receptor
Cell Type(s): Squid axon; Abstract integrate-and-fire leaky neuron
Receptors: Opsins
Model Concept(s): Parameter Fitting; Ion Channel Kinetics; Methods
Simulation Environment: Python (web link to model); NEURON (web link to model); Brian 2 (web link to model)
Implementer(s): Evans, Benjamin D [benjamin.evans at imperial.ac.uk]
References:
Evans BD, Jarvis S, Schultz SR, Nikolic K. (2016). PyRhO: A Multiscale Optogenetics Simulation Platform. Frontiers in neuroinformatics. 10 [PubMed]