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PyRhO: A Multiscale Optogenetics Simulation Platform

By Benjamin D. Evans, Sarah eJarvis, Simon R. Schultz and Konstantin eNikolic


Optogenetics has become a key tool for understanding the function of neural circuits and controlling their behaviour. An array of directly light driven opsins have been genetically isolated from several families of organisms, with a wide range of temporal and spectral properties. In order to characterise, understand and apply these opsins, we present an integrated suite of open-source, multi-scale computational tools called PyRhO. The purpose of developing PyRhO is threefold: (i) to characterise 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 & 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 behaviour and rapidly identify the most suitable variant for application in a particular biological system. This process may thereby guide not only experimental design and opsin choice but also alterations of the opsin genetic code in a neuro-engineering feed-back loop. In this way, we expect PyRhO will help to significantly advance optogenetics as a tool for transforming biological sciences

Topics: spiking neurons, optogenetics, python, NEURON simulator, Opsin, Jupyter, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Publisher: Frontiers Media S.A.
Year: 2016
DOI identifier: 10.3389/fninf.2016.00008
OAI identifier: oai:doaj.org/article:da110fadf8904486a0edd0acea0d3782
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