Project Summary The BICCN has recently completed a broad survey of the cellular components of motor cortex, including transcriptomic profiling, patch-seq, multiplexed FISH, inter-areal connectivity, and single neuron morphology. Missing from this view is a detailed picture of how individual neurons and neuronal types interconnect, in large part because acquiring a comprehensive picture of individual neuronal connections is best achieved with the difficult methods of large-scale electron microscopic reconstructions. Further, there are no scalable methods to assign transcriptomic cell classes to EM reconstructions, particularly when considering the myriad set of non- local inputs. In order to fulfill the BICCN mandate, we need scalable methods for measuring connectivity that can be integrated with cross-modal data, such as from Patch-seq, or with tools that target specific cell classes in transgenic and non-transgenic species, such as non-human primate. Here, we propose to exploit both approaches—retrospectively linking EM data with Patch-seq datasets or the prospective targeting of cell classes labeling in EM reconstructions—with our large-scale electron microscopy pipeline, while continuing to improve throughput and lower its overall cost. We propose to deploy these tools to examine the motor cortex of mouse and non-human primate, to demonstrate a scalable approach to delivering data that integrate local cellular morphology, ultrastructural detail, and specific local connectivity with transcriptomic information, from Patch-seq, while identifying the source and cell type of individual afferents, with viral genetic tools.

Project Narrative The BRAIN Initiative has collected a broad survey of the cellular components found in the motor cortex, a key structure involved in high level control of our muscle movements. This project will add to that survey a map of the patterns of connections found between individual cells within motor cortex, as well as patterns of connectivity found from individual axons from several key input areas. This will help us understand the role of different cellular components in this important circuit, with important consequences for how cellular therapies and further experiments are designed.