Mapping cell types, dynamics, and connections in neural circuits

Abstract

Neuroscience is limited by the difficulty of recording neural activity, identifying cell types, and mapping connectivity in high throughput. In this thesis, I present several scalable technologies aimed at improving our ability to characterize the activity, composition, and connectivity of neural circuits. My primary contributions include the design for a nanofabricated electrical recording device and a new approach to nanofabrication within swellable hydrogels; a high-throughput method for mapping the locations of cell types in tissue; an approach to direct sequencing of proteins at the single molecule level; an approach to directly recording neural activity into the sequence of RNA, enabling it to be detected by DNA sequencing; and a method for molecular barcoding of neurons, with the goal of enabling a high-throughput approach to neural circuit mapping. I conclude with a consideration of the limitations of the academic incentive structure as concerns the development and deployment of new technologies, and propose a structure for basic science research, complementary to the academic structure, based on the systematic establishment of well-funded, highly focused research projects with clear goals, an incentive to rapidly disseminate information, and limited lifetimes.