Department of Neurobiology, Stanford University, Stanford, CA 94103, USA; Stanford Neuroscience Institute, Stanford University, Stanford, CA 94103, USA.
Department of Neurology, University of California, San Francisco, San Francisco, CA 94158, USA.
Curr Biol. 2017 Aug 7;27(15):2389-2396.e4. doi: 10.1016/j.cub.2017.06.076. Epub 2017 Jul 27.
A long-standing goal of neuroscience has been to understand how computations are implemented across large-scale brain networks. By correlating spontaneous activity during "resting states" [1], studies of intrinsic brain networks in humans have demonstrated a correspondence with task-related activation patterns [2], relationships to behavior [3], and alterations in processes such as aging [4] and brain disorders [5], highlighting the importance of resting-state measurements for understanding brain function. Here, we develop methods to measure intrinsic functional connectivity in Drosophila, a powerful model for the study of neural computation. Recent studies using calcium imaging have measured neural activity at high spatial and temporal resolution in zebrafish, Drosophila larvae, and worms [6-10]. For example, calcium imaging in the zebrafish brain recently revealed correlations between the midbrain and hindbrain, demonstrating the utility of measuring intrinsic functional connections in model organisms [8]. An important component of human connectivity research is the use of brain atlases to compare findings across individuals and studies [11]. An anatomical atlas of the central adult fly brain was recently described [12]; however, combining an atlas with whole-brain calcium imaging has yet to be performed in vivo in adult Drosophila. Here, we measure intrinsic functional connectivity in Drosophila by acquiring calcium signals from the central brain. We develop an alignment procedure to assign functional data to atlas regions and correlate activity between regions to generate brain networks. This work reveals a large-scale architecture for neural communication and provides a framework for using Drosophila to study functional brain networks.
长期以来，神经科学的目标一直是了解如何在大规模脑网络中实现计算。通过对“静息状态”[1]期间的自发活动进行相关研究，人类内在脑网络的研究表明与任务相关的激活模式[2]、与行为的关系[3]以及与衰老过程[4]和大脑疾病[5]相关的过程发生改变具有对应关系，突出了静息状态测量对于理解大脑功能的重要性。在这里，我们开发了用于测量果蝇内在功能连接的方法，果蝇是神经计算研究的强大模型。最近使用钙成像的研究已经以高空间和时间分辨率测量了斑马鱼、果蝇幼虫和蠕虫中的神经活动[6-10]。例如，最近在斑马鱼大脑中的钙成像揭示了中脑和后脑之间的相关性，证明了在模型生物中测量内在功能连接的实用性[8]。人类连接研究的一个重要组成部分是使用大脑图谱来比较个体和研究之间的发现[11]。最近描述了中央成年果蝇大脑的解剖图谱[12]；然而，在成年果蝇体内，尚未将图谱与全脑钙成像结合使用。在这里，我们通过从中脑获取钙信号来测量果蝇的内在功能连接。我们开发了一种对齐程序，将功能数据分配给图谱区域，并对区域之间的活动进行相关，以生成大脑网络。这项工作揭示了神经通讯的大规模结构，并为使用果蝇研究功能大脑网络提供了框架。
