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Multimodal Technologies for Closed-Loop Neural Modulation and Sensing

delete2024-04-30
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PRE
AI
L
Lizhu Li
B
Bozhen Zhang
W
Wenxin Zhao
D
David Sheng
尹
尹斓 (Lan Yin)
X
Xing Sheng *
D
Dezhong Yao *
DOI:10.1002/adhm.202303289delete
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摘要

摘要

En 中文
Existing methods for studying neural circuits and treating neurological disorders are typically based on physical and chemical cues to manipulate and record neural activities. These approaches often involve predefined, rigid, and unchangeable signal patterns, which cannot be adjusted in real time according to the patient's condition or neural activities. With the continuous development of neural interfaces, conducting in vivo research on adaptive and modifiable treatments for neurological diseases and neural circuits is now possible. In this review, current and potential integration of various modalities to achieve precise, closed-loop modulation, and sensing in neural systems are summarized. Advanced materials, devices, or systems that generate or detect electrical, magnetic, optical, acoustic, or chemical signals are highlighted and utilized to interact with neural cells, tissues, and networks for closed-loop interrogation. Further, the significance of developing closed-loop techniques for diagnostics and treatment of neurological disorders such as epilepsy, depression, rehabilitation of spinal cord injury patients, and exploration of brain neural circuit functionality is elaborated. In this article, closed-loop control systems combining electric, optical, chemical, magnetic, and ultrasound signals for neural interfacing are reviewed, which achieve adaptive regulation depending on neuronal activity in real time. The remarkable development of closed-loop regulatory devices not only provides new research methods for studying neural circuits but also proposes new treatments for neurological diseases, extending their application from the brain to the whole body. image
Keyword:
closed-loop technique
neural sensing
neuromodulation

期刊

Advanced Healthcare Materials 封面图
Advanced Healthcare Materials
IF:
9.6
论文数:
7.7K
被引数:
4.4W

机构

T
tsinghua university
学者数:
11.9W
论文数: 10.0W
被引数: 137
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