果蠅的大腦包含超過100000個神經元。過去以螢光成像描繪果蠅神經元的型態，然而這樣的成像方法大多只能一次取得一顆或少數幾顆神經元，因此要更進一步的了解果蠅大腦連結體，預測這些神經元之間的連接是一項至關重要但具有挑戰性的任務。先前的研究已經開發了幾種基於距離和接觸點作為標準來估計神經元連接的方法。第一個參數是兩個神經元之間的最短距離閾值，當兩神經元的距離小於最短距離閾值後可以將其視為接觸。第二個參數是接觸點數目的比例，我們計算兩個神經元之間有多少個接觸點的距離小於最短距離閾值。此外，我們考慮端點和分支的差異，分析以端點或分支之間的距離來預測時，何者有較好的表現。
本研究將以過去在中央複合體上的實驗數據作為標準答案，進行統計分析來確定最佳預測方法和標準。我們發現，以線段到線段的距離評估時，在10um可得精度最高，而最佳接觸點比例標準是1％，另外我們也加入神經極性的參數，特別只考慮經典的軸突到樹突的連結時，可以有更好的表現。跟以往的方法相比，我們將準確率從80%提升到91%，誤報率從5.7%降至2.5%。未來我們將在應用我們的方法到整個果蠅大腦的數據，以生成果蠅大腦的高精度連接體。

A Drosophila brain encompasses more than 100000 neurons. To delineate the connections between these neurons in a fluorescent-image-based database is a crucial but challenging task. Previous studies have developed several approaches to estimate neuronal connections based on the distance and contact point criteria. The distance criterion indicates the shortest distance between two neurons that can be considered as making a contact while the contact point criterion sets the minimum value of the contact points between two neurons that are determined to form synaptic connections. Moreover, the distance can be calculated based on the distance between terminal points or branch segments. The goal of this project is to determine the best method and the optimal criteria by performing statistical analyses based on the ground truth data, which were compiled based on previously published papers on the central complex. We found that the highest accuracy was yield from the method based on the segment to segment at distance is 10um , the best contact point criteria was 1 percent, the shortest distance occurs between axon and dendrite. We increased the TPR from 80 percent to 91percent, and decreased FPR from 5.7 percent to 2.5 percent. We will apply our method on the FlyCircuit database to generate a highly accurate connectome of the fruit fly brain.

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