Theoretical and in vivo neuroscience research suggests that functional information transfer within neuronal networks is influenced by circuit architecture. Due to the dynamic complexities of the brain, it remains a challenge to test the correlation between structure and function of a defined network. Engineering controlled neuronal networks in vitro offers a way to test structural motifs; however, no method has achieved small, multi-node networks with stable, unidirectional connections. Here, we screened ten different microchannel architectures within polydimethylsiloxane (PDMS) devices to test their potential for axonal guidance. The most successful design had a 92% probability of achieving strictly unidirectional connections between nodes. Networks built from this design were cultured on multielectrode arrays and recorded on days in vitro 9, 12, 15 and 18 to investigate spontaneous and evoked bursting activity. Transfer entropy between subsequent nodes showed up to 100 times more directional flow of information compared to the control. Additionally, directed networks produced a greater amount of information flow, reinforcing the importance of directional connections in the brain being critical for reliable communication. By controlling the parameters of network formation, we minimized response variability and achieved functional, directional networks. The technique provides us with a tool to probe the spatio-temporal effects of different network motifs.

理论和体内神经科学研究表明，神经元网络内的功能信息传递受电路体系结构的影响。由于大脑的动态复杂性，测试定义的网络的结构和功能之间的相关性仍然是一个挑战。体外工程控制的神经元网络为测试结构基序提供了一种方法。但是，没有任何方法可以实现具有稳定的单向连接的小型多节点网络。在这里，我们筛选了聚二甲基硅氧烷（PDMS）设备中的十种不同的微通道结构，以测试其对轴突引导的潜力。最成功的设计具有92％的概率在节点之间实现严格的单向连接。将以此设计构建的网络培养在多电极阵列上，并在第9、12天体外记录 15和18调查自发和诱发的爆发活动。与控件相比，后续节点之间的传递熵显示出最多100倍的信息定向流。此外，定向网络产生了大量的信息流，从而增强了大脑中定向连接对于可靠通信至关重要的重要性。通过控制网络形成的参数，我们最大程度地减少了响应变异性，并实现了功能性的定向网络。该技术为我们提供了一种工具来探究不同网络图案的时空效应。定向网络产生了大量的信息流，从而增强了大脑中定向连接的重要性，这对于可靠的通信至关重要。通过控制网络形成的参数，我们最大程度地减少了响应变异性，并实现了功能性的定向网络。该技术为我们提供了一种工具来探究不同网络图案的时空效应。定向网络产生了大量的信息流，从而增强了大脑中定向连接的重要性，这对于可靠的通信至关重要。通过控制网络形成的参数，我们最大程度地减少了响应变异性，并实现了功能性的定向网络。该技术为我们提供了一种工具来探究不同网络图案的时空效应。