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Dynamic analysis of beta oscillations in Parkinsonian neural networks with the pedunculopontine nucleus under optogenetic control

光遗传刺激下对含脚桥核的帕金森神经网络中beta振荡的动力学分析

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Abstract

Clinical experiments have proven that the pedunculopontine nucleus (PPN) plays a crucial role in the modulation of beta oscillations in Parkinson’s disease (PD). Here, we propose a new computational framework by introducing the PPN and related synaptic connections to the classic basal ganglia-thalamo-cortical model. Fascinatingly, the improved model can not only simulate the basic saturated and beta activities mentioned in previous studies but also produce the normal alpha rhythm that is much closer to physiological phenomena. Specifically, the results show that Parkinsonian oscillation activities can be controlled and modulated by the connection strength between the PPN and the globus pallidus internal nucleus (GPi) and the subthalamic nucleus (STN), supporting the fact that PPN is overinhibited in PD. Meanwhile, the internal mechanism underlying these state transitions is further explained from the perspective of dynamics. Additionally, both deep brain stimulation (DBS) and optogenetic technology are considered effective in terms of abnormal oscillations. Especially when a low-frequency DBS is added to the PPN, beta oscillations can be suppressed, but it is excited again as the DBS’s frequency gradually increases to a larger value. These results coincide with the experimental results that low-frequency stimulation of the PPN is effective, and verify the rationality of the model. Furthermore, we show that optogenetic stimulation of the globus pallidus external (GPe) expressing excitatory channelrhodopsin (ChR2) can effectively inhibit beta oscillations, whereas exciting the STN and PPN has a limited effect. These results are consistent with experimental reports suggesting that the symptoms of PD’s movement disorder can be alleviated under the GPe-ChR2, but not STN-ChR2, situation. Although the functional role of the PPN and the feasibility of optogenetic stimulation remain to be clinically explored, the results obtained help us understand the mechanisms of beta oscillations in PD.

摘要

临床实验证明, 脚桥核(PPN)在帕金森病(PD)的beta振荡调控中起着至关重要的作用. 本文通过引入PPN改进了皮层-基底神经 节-丘脑网络动力学模型. 研究发现, 该模型不仅可以模拟先前研究中涉及的beta频带(13–30 Hz)的PD病态振荡行为, 还可以产生更接** **常生理活动的alpha节律. 具体地, PPN-基底神经节重要环路可以诱导beta振荡状态的产生、转迁和终止. 同时, 具体分析了其发生分 岔转迁行为的动力学机制. 此外, 模拟重现了低频DBS作用于PPN有效, 而高频刺激无效的实验现象, 进一步验证了改进模型的合理性. 研究结果表明, 在适当的光刺激条件下, GPe 的兴奋性光刺激可以有效抑制beta振荡, 而刺激STN的效果则有限, 并且理论实现了光遗 传学刺激靶向PPN以讨论对病态beta振荡的调控效果, 这些结果与实验现象一致. 虽然PPN的功能作用和光遗传刺激的可行性仍有待临 床探索, 但所获得的结果有助于我们进一步了解PD中beta振荡的调控机制.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 12072265 and 12372064).

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Authors and Affiliations

  1. School of Mathematics and Statistics, Northwestern Polytechnical University, **’an, 710072, China

    Yuzhi Zhao  (赵玉枝), Honghui Zhang  (张红慧) & Lin Du  (都琳)

  2. School of Aeronautic Science and Engineering, Beihang University, Bei**g, 100191, China

    Ying Yu  (于颖)

  3. School of Aeronautics, Northwestern Polytechnical University, **’an, 710072, China

    Zichen Deng  (邓子辰)

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  1. Yuzhi Zhao  (赵玉枝)
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Contributions

Author contributions Yuzhi Zhao: Investigation, Formal analysis, Methodology, Software, Validation, Writing–original draft, Writing–review & editing. Honghui Zhang: Methodology, Funding acquisition, Resources, Supervision, Writing–review & editing. Ying Yu: Conceptualization, Methodology. Lin Du: Funding acquisition, Resources, Supervision, Writing–review & editing. Zichen Deng: Resources, Supervision, Writing–review & editing.

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Correspondence to Honghui Zhang  (张红慧).

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Zhao, Y., Zhang, H., Yu, Y. et al. Dynamic analysis of beta oscillations in Parkinsonian neural networks with the pedunculopontine nucleus under optogenetic control. Acta Mech. Sin. 40, 523586 (2024). https://doi.org/10.1007/s10409-024-23586-x

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