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.