Imperial College London

DrKonstantinNikolic

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Visiting Professor
 
 
 
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Contact

 

+44 (0)20 7594 1594k.nikolic

 
 
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Location

 

Bessemer 420CBessemer BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Evans:2016:10.3389/fninf.2016.00008,
author = {Evans, B and Jarvis, S and Schultz, S and Nikolic, K},
doi = {10.3389/fninf.2016.00008},
journal = {Frontiers in Neuroinformatics},
title = {PyRhO: A Multiscale Optogenetics Simulation Platform},
url = {http://dx.doi.org/10.3389/fninf.2016.00008},
volume = {10},
year = {2016}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Optogenetics has become a key tool for understanding the function of neural circuits and controlling their behavior. 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 characterize, 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 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. 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.
AU - Evans,B
AU - Jarvis,S
AU - Schultz,S
AU - Nikolic,K
DO - 10.3389/fninf.2016.00008
PY - 2016///
SN - 1662-5196
TI - PyRhO: A Multiscale Optogenetics Simulation Platform
T2 - Frontiers in Neuroinformatics
UR - http://dx.doi.org/10.3389/fninf.2016.00008
UR - http://hdl.handle.net/10044/1/29725
VL - 10
ER -