Double Two-State Opsin Model With Autonomous Parameter Inference

被引:4
|
作者
Schoeters, Ruben [1 ]
Tarnaud, Thomas [1 ]
Martens, Luc [1 ]
Joseph, Wout [1 ]
Raedt, Robrecht [2 ]
Tanghe, Emmeric [1 ]
机构
[1] Ghent Univ IMEC, Dept Informat Technol INTEL, WAVES, Ghent, Belgium
[2] Univ Ghent, Inst Neurosci, Dept Neurol, 4BRAIN, Ghent, Belgium
关键词
computational optogenetics; computational efficiency; channelrhodopsin-H134R; MerMAID; model fitting; LIGHT-DARK ADAPTATION; CHANNELRHODOPSIN; OPTOGENETICS; EVOLUTION;
D O I
10.3389/fncom.2021.688331
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Double Two-State Opsin Model With Autonomous Parameter Inference
    Schoeters, Ruben
    Tarnaud, Thomas
    Martens, Luc
    Joseph, Wout
    Raedt, Robrecht
    Tanghe, Emmeric
    Frontiers in Computational Neuroscience, 2021, 15
  • [2] Stochastic analysis and inference of a two-state genetic promoter model
    Singh, Abhyudai
    Vargas, Cesar A.
    Karmakar, Rajesh
    2013 AMERICAN CONTROL CONFERENCE (ACC), 2013, : 4563 - 4568
  • [3] A two-state jump model
    Albanese, C
    Jaimungal, S
    Rubisov, DH
    QUANTITATIVE FINANCE, 2003, 3 (02) : 145 - 154
  • [4] Consensus in the two-state Axelrod model
    Lanchier, Nicolas
    Schweinsberg, Jason
    STOCHASTIC PROCESSES AND THEIR APPLICATIONS, 2012, 122 (11) : 3701 - 3717
  • [5] A two-state model for galaxy bias
    Repp, Andrew
    Szapudi, Istvan
    MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2020, 493 (03) : 3449 - 3463
  • [6] Markov state model of the two-state behaviour of water
    Hamm, Peter
    JOURNAL OF CHEMICAL PHYSICS, 2016, 145 (13):
  • [7] The two-state model for anomalous stochastic motion
    Shushin, AI
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2002, 305 (1-2) : 200 - 204
  • [8] Anomalous two-state model for anomalous diffusion
    Shushin, AI
    PHYSICAL REVIEW E, 2001, 64 (05): : 12
  • [9] A remark on the two-state model of dielectric relaxation
    Kohne, HG
    Stockhausen, M
    ZEITSCHRIFT FUR NATURFORSCHUNG SECTION A-A JOURNAL OF PHYSICAL SCIENCES, 1996, 51 (08): : 963 - 964
  • [10] Thermodynamics of bread baking: A two-state model
    Zuecher, Ulrich
    AMERICAN JOURNAL OF PHYSICS, 2014, 82 (03) : 224 - 230