BACKGROUND: Parkinson's disease (PD) is a common neurological degenerative disease that cannot be completely cured, although drugs can improve or alleviate its symptoms. Optogenetic technology, which stimulates or inhibits neurons with excellent spatial and temporal resolution, provides a new idea and approach for the precise treatment of Parkinson's disease. However, the neural mechanism of photogenetic regulation remains unclear. OBJECTIVE: In this paper, we want to study the nonlinear features of EEG signals in the striatum and globus pallidus through optogenetic stimulation of the substantia nigra compact part. METHODS: Rotenone was injected stereotactically into the substantia nigra compact area and ventral tegmental area of SD rats to construct rotenone-treated rats. Then, for the optogenetic manipulation, we injected adeno-associated virus expressing channelrhodopsin to stimulate the globus pallidus and the striatum with a 1âmW blue light and collected LFP signals before, during, and after light stimulation. Finally, the collected LFP signals were analyzed by using nonlinear dynamic algorithms. RESULTS: After observing the behavior and brain morphology, 16 models were finally determined to be successful. LFP results showed that approximate entropy and fractal dimension of rats in the control group were significantly greater than those in the experimental group after light treatment (p < 0.05). The LFP nonlinear features in the globus pallidus and striatum of rotenone-treated rats showed significant statistical differences before and after light stimulation (p < 0.05). CONCLUSION: Optogenetic technology can regulate the characteristic value of LFP signals in rotenone-treated rats to a certain extent. Approximate entropy and fractal dimension algorithm can be used as an effective index to study LFP changes in rotenone-treated rats.
Study on the Regulation Effect of Optogenetic Technology on LFP of the Basal Ganglia Nucleus in Rotenone-Treated Rats.
光遗传技术对鱼藤酮处理大鼠基底神经节核局部场电位调控作用的研究
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作者:Zhao Zongya, Niu Yanxiang, Chen Peiqi, Zhu Yu, Shi Liangliang, Zhao Xuewei, Wang Chang, Zhang Yehong, Gao Zhixian, Jiang Wenshuai, Ren Wu, Gu Renjun, Yu Yi
| 期刊: | Neural Plasticity | 影响因子: | 3.700 |
| 时间: | 2021 | 起止号: | 2021 Jul 28; 2021:9938566 |
| doi: | 10.1155/2021/9938566 | 研究方向: | 神经科学 |
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