1. Harnessing the sensing and stimulation function of deep brain-machine interfaces: a new dawn for overcoming substance use disorders
- Author
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Danyang Chen, Zhixian Zhao, Jian Shi, Shengjie Li, Xinran Xu, Zhuojin Wu, Yingxin Tang, Na Liu, Wenhong Zhou, Changmao Ni, Bo Ma, Junya Wang, Jun Zhang, Li Huang, Zheng You, Ping Zhang, and Zhouping Tang
- Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Abstract Substance use disorders (SUDs) imposes profound physical, psychological, and socioeconomic burdens on individuals, families, communities, and society as a whole, but the available treatment options remain limited. Deep brain-machine interfaces (DBMIs) provide an innovative approach by facilitating efficient interactions between external devices and deep brain structures, thereby enabling the meticulous monitoring and precise modulation of neural activity in these regions. This pioneering paradigm holds significant promise for revolutionizing the treatment landscape of addictive disorders. In this review, we carefully examine the potential of closed-loop DBMIs for addressing SUDs, with a specific emphasis on three fundamental aspects: addictive behaviors-related biomarkers, neuromodulation techniques, and control policies. Although direct empirical evidence is still somewhat limited, rapid advancements in cutting-edge technologies such as electrophysiological and neurochemical recordings, deep brain stimulation, optogenetics, microfluidics, and control theory offer fertile ground for exploring the transformative potential of closed-loop DBMIs for ameliorating symptoms and enhancing the overall well-being of individuals struggling with SUDs.
- Published
- 2024
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