@article{47183de616674b6895c1d63fd99a061b,
title = "Modulation of deep neural circuits with sonogenetics",
abstract = "Noninvasive control of neuronal activity in the deep brain can be illuminating for probing brain function and treating dysfunctions. Here, we present a sonogenetic approach for controlling distinct mouse behavior with circuit specificity and subsecond temporal resolution. Targeted neurons in subcortical regions were made to express a mutant large conductance mechanosensitive ion channel (MscL-G22S), enabling ultrasound to trigger activity in MscL-expressing neurons in the dorsal striatum and increase locomotion in freely moving mice. Ultrasound stimulation of MscL-expressing neurons in the ventral tegmental area could activate the mesolimbic pathway to trigger dopamine release in the nucleus accumbens and modulate appetitive conditioning. Moreover, sonogenetic stimulation of the subthalamic nuclei of Parkinson's disease model mice improved their motor coordination and mobile time. Neuronal responses to ultrasound pulse trains were rapid, reversible, and repeatable. We also confirmed that the MscL-G22S mutant is more effective to sensitize neurons to ultrasound compared to the wild-type MscL. Altogether, we lay out a sonogenetic approach which can selectively manipulate targeted cells to activate defined neural pathways, affect specific behaviors, and relieve symptoms of neurodegenerative disease.",
keywords = "MscL-G22S, neural circuits, neuromodulation, sonogenetics, ultrasound",
author = "Quanxiang Xian and Zhihai Qiu and Suresh Murugappan and Shashwati Kala and Wong, {Kin Fung} and Danni Li and Guofeng Li and Yizhou Jiang and Yong Wu and Min Su and Xuandi Hou and Jiejun Zhu and Jinghui Guo and Weibao Qiu and Lei Sun",
note = "Funding Information: ACKNOWLEDGMENTS. This work was supported by Guangdong High-Level Innovation Research Institute (2021B0909050004), Hong Kong Research Grants Council General Research Fund (15104520, 15102417, and 15326416), Hong Kong Innovation Technology Fund (MRP/018/18X and MHP/014/19), Shenzhen-HongKong-MacauScience andTechnology Program(SGDX20201103095400001), Key-Area Research and Development Program of Guangdong Province (2018B030331001), and internal funding from the Hong Kong Polytechnic University (1-ZVW8 and 1-CD76).We would like to thank the facilities and technical support from University Research Facility in Life Sciences and University Research Facility in Behavioral and Systems Neuroscience of The Hong Kong Polytechnic University. Funding Information: This work was supported by Guangdong High-Level Innovation Research Institute (2021B0909050004), Hong Kong Research Grants Council General Research Fund (15104520, 15102417, and 15326416), Hong Kong Innovation Technology Fund (MRP/018/18X and MHP/014/19), Shenzhen-Hong Kong-Macau Science and Technology Program (SGDX20201103095400001), Key-Area Research and Development Program of Guangdong Province (2018B030331001), and internal funding from the Hong Kong Polytechnic University (1-ZVW8 and 1-CD76). We would like to thank the facilities and technical support from University Research Facility in Life Sciences and University Research Facility in Behavioral and Systems Neuroscience of The Hong Kong Polytechnic University. Publisher Copyright: Copyright {\textcopyright} 2023 the Author(s). Published by PNAS.",
year = "2023",
month = may,
day = "30",
doi = "10.1073/pnas.2220575120",
language = "English",
volume = "120",
pages = "e2220575120",
journal = "Proceedings of the National Academy of Sciences of the United States of America",
issn = "0027-8424",
publisher = "National Academy of Sciences",
number = "22",
}