美国西北大学John A. Rogers团队宣布他们研究出模式无线经颅光遗传学产生人工感知。这一研究成果发表在2025年12月8日出版的国际学术期刊《自然—神经科学》上。

在这里，该团队展示了一种小型化的、完全可植入的经颅光遗传神经刺激器，旨在通过实时无线对大的皮质集合进行图案化来产生人工感知。实验验证的数值模拟表征了光和热的传播，而神经元的反应则通过体内电生理学和分子方法进行评估。操作性学习过程中的线索辨别证明了小鼠感知的人工感知的无线起源，其中跨大皮质网络的空间距离和基于顺序的辨别分析预测了表现。这些概念和技术上的进步扩大了对人工模式神经活动及其大脑感知的理解，以指导下一代全光学大脑的进化。机通信。

据悉，合成独立于典型感觉通道的可感知人工神经输入仍然是开发下一代脑机接口的一个基本挑战。。建立一个具有长期稳定性的微创、无线有效和小型化平台对于创造能够介导人工感知反馈的研究方法和临床有意义的生物界面至关重要。

附：英文原文

Title: Patterned wireless transcranial optogenetics generates artificial perception

Author: Wu, Mingzheng, Yang, Yiyuan, Zhang, Jinglan, Efimov, Andrew I., Li, Xiuyuan, Zhang, Kaiqing, Wang, Yue, Bodkin, Kevin L., Riahi, Mohammad, Gu, Jianyu, Wang, Glingna, Kim, Minsung, Zeng, Liangsong, Liu, Jiaqi, Yoon, Lauren H., Zhang, Haohui, Freda, Sara N., Lee, Minkyu, Kang, Jiheon, Ciatti, Joanna L., Ting, Kaila, Cheng, Stephen, Zhang, Xincheng, Sun, He, Zhang, Wenming, Zhang, Yi, Banks, Anthony, Good, Cameron H., Cox, Julia M., Pinto, Lucas, Vzquez-Guardado, Abraham, Huang, Yonggang, Kozorovitskiy, Yevgenia, Rogers, John A.

Issue&Volume: 2025-12-08

Abstract: Synthesizing perceivable artificial neural inputs independent of typical sensory channels remains a fundamental challenge in developing next-generation brainmachine interfaces. Establishing a minimally invasive, wirelessly effective and miniaturized platform with long-term stability is crucial for creating research methods and clinically meaningful biointerfaces capable of mediating artificial perceptual feedback. Here we demonstrate a miniaturized, fully implantable transcranial optogenetic neural stimulator designed to generate artificial perceptions by patterning large cortical ensembles wirelessly in real time. Experimentally validated numerical simulations characterized light and heat propagation, whereas neuronal responses were assessed by in vivo electrophysiology and molecular methods. Cue discrimination during operant learning demonstrated the wireless genesis of artificial percepts sensed by mice, where spatial distance across large cortical networks and sequential order-based analyses of discrimination predicted performance. These conceptual and technical advances expand understanding of artificially patterned neural activity and its perception by the brain to guide the evolution of next-generation all-optical brainmachine communication.

DOI: 10.1038/s41593-025-02127-6

Source: https://www.nature.com/articles/s41593-025-02127-6