Kim Jeong Hee, Kim Minseok, Kim Keun-Tae, Chou Namsun, Kim Hong Nam, Cho Il-Joo, Lee Ju-Hyun, Shin Hyogeun
Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea.
School of Electronics Engineering, Kyungpook National University, Daegu, Republic of Korea.
Biosens Bioelectron. 2025 Nov 1;287:117703. doi: 10.1016/j.bios.2025.117703. Epub 2025 Jun 17.
Neural organoids provide a promising platform for biologically inspired computing due to their complex neural architecture and energy-efficient signal processing. However, the scalability of conventional organoid cultures is limited, restricting synaptic connectivity and functional capacity-significant barriers to developing high-performance bioprocessors. Here, we present a scalable three-dimensional (3D) packaging strategy for neural organoid arrays inspired by semiconductor 3D stacking technology. This approach vertically assembles Matrigel-embedded neural organoids within a polydimethylsiloxane (PDMS)-based chamber using a removable acrylic alignment plate, creating a stable multilayer structure while preserving oxygen and nutrient diffusion. Structural analysis confirms robust inter-organoid connectivity, while electrophysiological recordings reveal significantly enhanced neural dynamics in 3D organoid arrays compared to both single organoids and two-dimensional arrays. Furthermore, prolonged culture duration promotes network maturation and increases functional complexity. This 3D stacking strategy provides a simple yet effective method for expanding the physical and functional capacity of organoid-based systems, offering a viable path toward next-generation biocomputing platforms.
神经类器官因其复杂的神经结构和高效节能的信号处理能力,为受生物启发的计算提供了一个很有前景的平台。然而,传统类器官培养的可扩展性有限,限制了突触连接性和功能容量,这是开发高性能生物处理器的重大障碍。在此,我们提出了一种受半导体三维堆叠技术启发的用于神经类器官阵列的可扩展三维(3D)封装策略。这种方法使用可移除的丙烯酸对齐板,在基于聚二甲基硅氧烷(PDMS)的腔室内垂直组装包埋在基质胶中的神经类器官,形成一个稳定的多层结构,同时保持氧气和营养物质的扩散。结构分析证实了类器官间强大的连接性,而电生理记录显示,与单个类器官和二维阵列相比,三维类器官阵列中的神经动力学显著增强。此外,延长培养时间可促进网络成熟并增加功能复杂性。这种三维堆叠策略为扩展基于类器官的系统的物理和功能容量提供了一种简单而有效的方法,为下一代生物计算平台提供了一条可行的途径。