PROJECT SUMMARY Many computations in the nervous system occur at the level of individual neurites within large extensively branched arbors (i.e., subcellular processing). Most neurites operate in dense neuropils, in which processes of diverse cell types are tightly packed and abundantly interconnected. To understand subcellular processing, we need to measure neurite responses to physiological stimuli and relate them to local patterns of synaptic inputs. To delineate the functional architecture of neuropils and reveal the logic of their connectivity, we need to characterize neurite responses and synapse patterns at high density. Neurite responses can be observed by two-photon imaging, and synaptic inputs can be reconstructed in serial-section electron microscopy (ssEM). A number of technical obstacles have precluded the combination of these techniques (i.e., functional connectomics) to study subcellular processing in dense neuropils. Here, we develop new tools and approaches to overcome these obstacles. In Aim 1, we develop genetic, viral, and computational tools for multispectral two-photon calcium imaging and signal demixing to enable dense functional characterization of neuropils. In Aim 2, we devise a novel strategy for combining two-photon imaging and ssEM (i.e., multimodal imaging), and establish a high-throughput ssEM method for analyzing local synaptic connectivity patterns in the context of larger-scale circuit wiring (i.e., multiresolution imaging). We use our advances to study amacrine cells (ACs), a diverse class of retinal interneurons. The neurites of more than 50 AC types extract salient visual information in a dense neuropil the inner retina. We will acquire a complete functional connectomic dataset of ACs. This dataset, which will be made publicly available, will form the basis of a future R01 application to study the mechanisms of subcellular processing in ACs, the functional architecture of the AC neuropil, and the logic of its connectivity.