用于神经记录和神经调节的多通道神经接口。

IF 9.1 2区 材料科学 Q1 CHEMISTRY, PHYSICAL
Eunmin Kim, Won Gi Chung, Enji Kim, Myoungjae Oh, Joonho Paek, Taekyeong Lee, Dayeon Kim, Seung Hyun An, Sumin Kim, Jang-Ung Park
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引用次数: 0

摘要

通过实时采集和监测神经信号,神经接口已经成为推进数字神经疗法的关键平台。传统的单通道系统在捕捉不同神经元群体之间复杂和大规模相互作用的能力上存在固有的局限性。相比之下,多通道系统提供了解码跨越多个大脑和脊髓区域的神经回路动态活动所需的高时空分辨率。本文综述了多通道神经接口技术的最新进展,包括用于高分辨率电生理记录的穿透式和非穿透式系统,以及集成了药物传递、光刺激和化学传感等附加模式的多功能平台。该领域的最新进展是由结构和材料设计的进步推动的,包括用于衬底和电极的柔软,柔性的结构和材料的开发,这些结构和材料提高了长期稳定性并最大限度地减少了组织损伤。同时,新兴的数据分析技术提高了从高维、多通道记录中解码复杂神经活动模式的能力。这些技术进步扩大了神经接口在脑机接口(bmi)中的潜在应用,促进了精确的神经调节,神经状态的实时监测,以及与虚拟和增强现实等沉浸式系统的集成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-Channel Neural Interface for Neural Recording and Neuromodulation.

Neural interfaces have emerged as pivotal platforms for advancing digital neurotherapies by enabling the real-time acquisition and monitoring of neural signals. Traditional single-channel systems are inherently limited in their capacity to capture the complex and large-scale interactions among diverse neuronal populations. In contrast, multi-channel systems provide the high spatiotemporal resolution necessary to decode the dynamic activity of neural circuits across multiple brain and spinal cord regions. This review provides a comprehensive overview of recent advances in multi-channel neural interface technologies, encompassing both penetrating and non-penetrating systems for high-resolution electrophysiological recording, as well as multifunctional platforms that integrate additional modalities such as drug delivery, optical stimulation, and chemical sensing. Recent progress in this field has been driven by advances in structural and material design, including the development of soft, flexible architectures and materials for both substrates and electrodes, which improve long-term stability and minimize tissue damage. In parallel, emerging data analysis techniques have enhanced the capacity to decode complex neural activity patterns from high-dimensional, multi-channel recordings. These technological advancements have broadened the potential applications of neural interfaces in brain-machine interfaces (BMIs), facilitating precise neuromodulation, real-time monitoring of neurological states, and integration with immersive systems such as virtual and augmented reality.

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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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