Mapping cell types, dynamics, and connections in neural circuits
Author(s)Rodriques, Samuel Gordon.
Massachusetts Institute of Technology. Department of Physics.
Edward S. Boyden and Jeff Gore.
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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.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Physics, 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 227-249).
DepartmentMassachusetts Institute of Technology. Department of Physics
Massachusetts Institute of Technology