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, Zhouping Tang
{"title":"利用深度脑机接口的传感和刺激功能：克服药物使用障碍的新曙光。","authors":"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, Zhouping Tang","doi":"10.1038/s41398-024-03156-8","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":23278,"journal":{"name":"Translational Psychiatry","volume":null,"pages":null},"PeriodicalIF":5.8000,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11487193/pdf/","citationCount":"0","resultStr":"{\"title\":\"Harnessing the sensing and stimulation function of deep brain-machine interfaces: a new dawn for overcoming substance use disorders.\",\"authors\":\"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, Zhouping Tang\",\"doi\":\"10.1038/s41398-024-03156-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":23278,\"journal\":{\"name\":\"Translational Psychiatry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2024-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11487193/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Translational Psychiatry\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1038/s41398-024-03156-8\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHIATRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational Psychiatry","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41398-024-03156-8","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}
Harnessing the sensing and stimulation function of deep brain-machine interfaces: a new dawn for overcoming substance use disorders.
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.
期刊介绍：
Psychiatry has suffered tremendously by the limited translational pipeline. Nobel laureate Julius Axelrod''s discovery in 1961 of monoamine reuptake by pre-synaptic neurons still forms the basis of contemporary antidepressant treatment. There is a grievous gap between the explosion of knowledge in neuroscience and conceptually novel treatments for our patients. Translational Psychiatry bridges this gap by fostering and highlighting the pathway from discovery to clinical applications, healthcare and global health. We view translation broadly as the full spectrum of work that marks the pathway from discovery to global health, inclusive. The steps of translation that are within the scope of Translational Psychiatry include (i) fundamental discovery, (ii) bench to bedside, (iii) bedside to clinical applications (clinical trials), (iv) translation to policy and health care guidelines, (v) assessment of health policy and usage, and (vi) global health. All areas of medical research, including — but not restricted to — molecular biology, genetics, pharmacology, imaging and epidemiology are welcome as they contribute to enhance the field of translational psychiatry.
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