Lassers Samuel B, Khatri Shazfa S, Chen Ruiyi, Vakilna Yash S, Tang William C, Brewer Gregory J
Department of Biomedical Engineering, University of California Irvine, Irvine, California, United States of America.
Texas Institute of Restorative Neurotechnologies (TIRN), The University of Texas Health Science Center (UTHealth), Houston, Texas, United States of America.
PLoS One. 2025 Jul 17;20(7):e0326032. doi: 10.1371/journal.pone.0326032. eCollection 2025.
Each sub-region of the hippocampus plays a critical computational role in the formation of episodic learning and memory, but studies have yet to show and interpret the individual spiking dynamics of each region and how that information is passed between each subregion. This is in part due to the difficulty in accessing individual communicating axons. Here, we created a novel microfluidic device that facilitates network growth of four separated hippocampal subregions over a micro-electrode array. This device enabled monitoring single axons over two electrodes so direction of spike propagation in interregional communication could be ascertained. In this in vitro hippocampal study, we compared spiking dynamics across two novel four-compartment device architectures: one with four sets of axon tunnels between subregions that excluded the perforant pathway from EC-CA3, and one with five sets of axon tunnels that included the EC-CA3 connection. We found 30-90% faster feed-forward firing rates (shorter interspike intervals) in axons in the five-tunnel model with 35-75% slower bursting dynamics (longer interburst intervals) compared to the four-tunnel model. The CA3-CA1 and CA1-EC axons had more spikes in bursts in the five-tunnel architecture than the four-tunnel counterpart suggesting more structured information transfer. Feedback firing rates were similar between configurations. The faster feed-forward inter-regional spiking in the more natural five-tunnel than the four-tunnel configuration suggests tighter control of spiking and possibly more precise communication between subregions.
海马体的每个子区域在情景学习和记忆的形成中都发挥着关键的计算作用，但研究尚未展示和解释每个区域的单个神经元放电动态，以及该信息如何在各个子区域之间传递。部分原因在于难以接入单个进行通信的轴突。在此，我们创建了一种新型微流控装置，该装置有助于四个分离的海马体子区域在微电极阵列上生长网络。该装置能够在两个电极上监测单个轴突，从而可以确定区域间通信中动作电位传播的方向。在这项体外海马体研究中，我们比较了两种新型四室装置架构中的神经元放电动态：一种在子区域之间有四组轴突通道，排除了从内嗅皮层到海马体CA3区的穿通通路；另一种有五组轴突通道，包括内嗅皮层 - 海马体CA3区的连接。我们发现，与四通道模型相比，五通道模型中轴突的前馈发放速率快30 - 90%（峰峰间期更短），爆发动态慢35 - 75%（爆发间期更长）。在五通道架构中，CA3 - CA1和CA1 - 内嗅皮层的轴突在爆发时有更多的动作电位，比四通道架构中的对应轴突更多，这表明信息传递更具结构性。两种配置之间的反馈发放速率相似。与四通道配置相比，更接近自然状态的五通道配置中更快的前馈区域间放电表明对放电的控制更严格，并且子区域之间的通信可能更精确。
