神經網路體(connectome)是指全腦神經細胞間線路連接的總合，由於神經細胞數量龐大、形態各異且交錯縱橫，若要清楚描繪所有神經細胞間連接的情形，必須先取得大量單一神經細胞的影像。以果蠅為例：單一神經細胞影像係擷取自不同的腦，需要經過影像對位才能全部重組在同一個標準腦空間中，故這項工作極為繁重。此外，為了分析資訊如何在大腦內處理與流動，也必須將神經功能性數據如活體神經影像整合進來，這又是另一項挑戰；因為功能性影像也是從不同次實驗收集而來，同樣需要經過影象對位才能與單一神經細胞的結構性影像整合在一起。
果蠅腦的結構性影像傳統上是以解剖腦來獲取，但功能性影像則擷取自原位腦。由於解剖腦週邊的脂肪等結締組織已被去除，容易因機械拉扯、膨脹及重力而扭曲變形，但原位腦則無以上情形，所以要將這兩種影像做到準確對位有其困難。因此本研究發展出一種原位腦取像技術，稱為果蠅頭陣列切片取像術(簡稱FHAST)，讓結構性及功能性神經影像都能透過原位腦來擷取，以方便後續的對位與整合。FHAST技術是將果蠅頭整齊排成陣列並以洋菜膠包裹，然後用震動式切片機同時將所有果蠅頭切開，使大腦暴露出來，以進行染色和取像。FHAST保留了原位神經結構包括腦與週邊神經的連接，並且減少了神經形態的扭曲。更重要的是：FHAST切片讓我們可以在共軛焦顯微鏡上進行自動化3D取像，一次最多可設定100個果蠅腦，這極有利於神經網路體的建構。
我們運用FHAST技術所獲取的影像初步建立了一個果蠅頭參考模型，發現不論單一神經細胞影像或功能性影像均能準確對進這個參考模型中，藉此我們得以預測可能是那些神經細胞產生該功能性影像及其相關的特定行為。我們希望FHAST將來可以成為一個標準技術平台，讓不同實驗室所獲的神經影像得以整合成一個共享資料庫，進而加速影像的累積與神經網路的解析。

Mapping the connectome, a wiring diagram of the entire brain, requires large-scale imaging of numerous single neurons with diverse morphology. It is a formidable challenge to reassemble these neurons into a virtual brain and correlate their structural networks with neuronal activities, which are measured in different experiments to analyze the informational flow in the brain. Here, we report an in situ brain imaging technique called Fly Head Array Slice Tomography (FHAST), which permits the reconstruction of structural and functional data to generate an integrative connectome in Drosophila. Using FHAST, the head capsules of an array of flies can be opened with a single vibratome sectioning to expose the brains, replacing the painstaking and inconsistent brain dissection process. FHAST can reveal in situ brain neuroanatomy with minimal distortion to neuronal morphology and maintain intact neuronal connections to peripheral sensory organs. Most importantly, it enables the automated 3D imaging of 100 intact fly brains in each experiment. The established head model with in situ brain neuroanatomy allows functional data to be accurately registered and associated with 3D images of single neurons. These integrative data can then be shared, searched, visualized, and analyzed for understanding how brain-wide activities in different neurons within the same circuit function together to control complex behaviors.

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