- 學位論文
網路架構及核心樞紐對神經迴路中的縱向及橫向資訊傳遞效率之影響
How network architectures and hubs affect efficiency of vertical and horizontal information propagations in neural circuits — a theoretical analysis
摘要
典型的網路分析大多基於最短路徑進行分析。然而這些分析方法無法展現出神經網路兩種特性性： 第一，神經網路有特定的資訊傳遞方向。第二，在功能上，經由多個突觸的路徑可能比最短路徑來得 重要。為了考慮到此兩個特性，我們量化兩個全新的特性：第一，縱向傳遞：所有輸入到輸出間的主 要資訊傳遞路徑多快會建立完成。第二：橫向傳遞：訊息進入網路後多快散佈到眾多的輸出節點。我 們分析了線蟲的神經網路、果蠅的前腦橋網路，並用人工產生的規則網路、小世界網路以及隨機網路 作為比較。結果顯示比起小世界網路，線蟲及前腦橋神經網路在縱向及橫向傳遞上更有效率。更多的 分析顯示在小世界網路中，不同的核心樞紐可以改善不同的傳遞效率：區域型核心樞紐可以提昇縱向 傳遞、無親型核心樞紐可以改善橫向傳遞、連接型核心樞紐可以同時提昇縱向及橫向的傳遞效率。此 外，在破壞線蟲神經網路的核心樞紐之實驗，也同樣支持此結果。我們的實驗結果顯示在神經網路的 訊息傳遞中，不同的核心樞紐可能扮演不同的重要功能及角色，而這也啟發我們，對於初階感知系統 中聯絡神經元之功能的想像。
並列摘要
Typical analyses of the network architecture focus on the shortest path. However, the approach may not fully characterize the features of neural networks in at least two ways: a) A neural network has a specific direction of information flow. b) The neural pathways via multiple synaptic connections may be functionally more important than the shortest pathways. To address the issues, we measures two novel quantities: a) Vertical propagation is how quickly the main information pathway are established between input and output nodes. b) Horizontal propagation is how quickly the information from input neurons could propagate to multiple output neurons. We analysed the C. Elegans neural network, protocerebral bridge network in Drosophila, and, as comparison, artificially generated regular, small-world and random networks. Our results show that the C. Elegans and PCB neural networks are more efficient in both vertical and horizontal propagation than the small-world networks. Further analysis show that different hubs could improve the different propagation efficiency in small-world networks: provincial hubs enhance vertical propagation, kinless hubs improve horizontal propagation, and connector hubs increase the efficiency of the both propagations. In addition, this result could be supported by lesioning hubs in the C. Elegans neural network. Our results suggest that the various hubs may play different important roles in information propagations of the neural networks, and our works may deliver insight into the functions of the interneurons in primary sensory systems.