神经调节
脑-机接口
计算机科学
接口(物质)
人工神经网络
神经活动
生物神经网络
模式
领域(数学)
数据采集
高分辨率
人工智能
人机交互
神经工程
神经科学
神经假体
神经系统
神经系统
深层神经网络
作者
Eun-Min Kim,Won Gi Chung,Enji Kim,Myoungjae Oh,Jihyun Paek,Taekyeong Lee,Dayeon Kim,Sihyun An,Sumin Kim,Jang‐Ung Park
出处
期刊:Small methods
[Wiley]
日期:2025-09-25
卷期号:10 (3): e01227-e01227
标识
DOI:10.1002/smtd.202501227
摘要
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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