Flexible modeling of large-scale neural network stimulation: Electrical and optical extensions to The Virtual Electrode Recording Tool for EXtracellular Potentials (VERTEX)

大规模神经网络刺激的灵活建模:细胞外电位虚拟电极记录工具 (VERTEX) 的电学和光学扩展

阅读:4

Abstract

BACKGROUND: Computational models that predict effects of neural stimulation can serve as a preliminary tool to inform in-vivo research, reducing costs, time, and ethical considerations. However, current models do not support the diverse neural stimulation techniques used in-vivo, including the expanding selection of electrodes, stimulation modalities, and stimulation protocols. NEW METHOD: We developed several extensions to The Virtual Electrode Recording Tool for EXtracellular Potentials (VERTEX), the MATLAB-based neural stimulation tool. VERTEX simulates input currents in a large population of multi-compartment neurons within a small cortical slice to model electric field stimulation, while recording local field potentials (LFPs) and spiking activity. Our extensions enhance this framework with support for multiple pairs of parametrically defined electrodes and biphasic, bipolar stimulation delivered at programmable delays. To support the growing use of optogenetic approaches for targeted neural stimulation, we introduced a feature that models optogenetic stimulation through an additional VERTEX input function that converts irradiance to currents at optogenetically responsive neurons. Finally, we added extensions to allow complex stimulation protocols including paired-pulse, spatiotemporal patterned, and closed-loop stimulation. RESULTS: We demonstrated these novel features using VERTEX's built-in functionalities, with results consistent with other models and experimental work. COMPARISON WITH EXISTING METHODS: Unlike other tools, our extensions enable both electric field and optogenetic stimulation, provide a range of open- and closed-loop protocols, and offer flexible settings within a large-scale cortical network of neurons with realistic biophysical properties. CONCLUSIONS: Our extensions provide an all-in-one platform to efficiently and systematically test diverse, targeted, and individualized stimulation patterns.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。