Abstract
Optogenetics has a lot of potential to become an effective neuromodulative therapy for clinical applications. Selecting the correct opsin is crucial to have an optimal optogenetic tool. With computational modeling, the neuronal response to the current dynamics of an opsin can be extensively and systematically tested. Unlike electrical stimulation where the effect is directly defined by the applied field, the stimulation in optogenetics is indirect, depending on the selected opsin's non-linear kinetics. With the continuous expansion of opsin possibilities, computational studies are difficult due to the need for an accurate model of the selected opsin first. To this end, we propose a double two-state opsin model as alternative to the conventional three and four state Markov models used for opsin modeling. Furthermore, we provide a fitting procedure, which allows for autonomous model fitting starting from a vast parameter space. With this procedure, we successfully fitted two distinctive opsins (ChR2(H134R) and MerMAID). Both models are able to represent the experimental data with great accuracy and were obtained within an acceptable time frame. This is due to the absence of differential equations in the fitting procedure, with an enormous reduction in computational cost as result. The performance of the proposed model with a fit to ChR2(H134R) was tested, by comparing the neural response in a regular spiking neuron to the response obtained with the non-instantaneous, four state Markov model (4SB), derived by Williams et al. (2013). Finally, a computational speed gain was observed with the proposed model in a regular spiking and sparse Pyramidal-Interneuron-Network-Gamma (sPING) network simulation with respect to the 4SB-model, due to the former having two differential equations less. Consequently, the proposed model allows for computationally efficient optogenetic neurostimulation and with the proposed fitting procedure will be valuable for further research in the field of optogenetics.
Highlights
With optogenetics, neuronal firing can be controlled with light
To test the feasibility of the proposed double two-state opsin model structure (22OM), it was fit to two data sets
We fitted the model to the data set of a ChR2(H134R) opsin reported by Williams et al (2013), which was collected in a ChR2(H134R)-HEK293 stable cell line (Williams et al, 2013)
Summary
Neuronal firing can be controlled with light This is achieved by genetically expressing opsins, light sensitive ion channels or pumps, in cells or cell subtypes. Genetic engineering has led to a variety of opsins, such as red-shifted, step-function and ultrafast opsins, and mutants with altered ion selectivity (Gunaydin et al, 2010; Gerits and Vanduffel, 2013; Azimihashemi et al, 2014). An example of the latter is ChR2(H134R), which is addressed in this paper. An example are the MerMAIDs, which is a family of metagenomically discovered marine anion-conducting and intensely desensitizing channelrhodopsins (Oppermann et al, 2019)
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