Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Transl Psychiatry. 2024 Oct 17;14(1):440. doi: 10.1038/s41398-024-03156-8.
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.
物质使用障碍（SUDs）给个人、家庭、社区和整个社会带来了深刻的身体、心理和社会经济负担，但现有的治疗选择仍然有限。深部脑-机接口（DBMIs）提供了一种创新的方法，通过促进外部设备和深部脑结构之间的有效交互，从而能够对这些区域的神经活动进行细致的监测和精确的调节。这一开创性范例有望彻底改变成瘾障碍的治疗格局。在这篇综述中，我们仔细研究了闭环 DBMIs 在治疗物质使用障碍方面的潜力，特别关注三个基本方面：与成瘾行为相关的生物标志物、神经调节技术和控制策略。尽管直接的经验证据仍然有些有限，但诸如电生理和神经化学记录、深部脑刺激、光遗传学、微流控和控制理论等前沿技术的快速发展为探索闭环 DBMIs 改善症状和增强与 SUDs 作斗争的个体整体幸福感的变革潜力提供了肥沃的土壤。
