Electrogenetics: Genetically Encoded Electrophysiology

Limited Access
This item is unavailable until:



Journal Title

Journal ISSN

Volume Title

Repository Usage Stats



There are about 86 billion neurons in the human brain, connected by trillions of synapses. Deciphering the electrical signaling between neurons is key to understanding the brain in both health and disease. As understanding begins with observation, the past decade has brought significant investment in scalable, stable neural recording technologies. An ideal recording platform would have the ability to record from thousands of neurons simultaneously with millisecond temporal precision and knowledge of the genetic identity of each cell—all while being low-cost, scalable, and amenable to simple data storage. Moreover, deciphering how disease progression remodels neural ensembles requires recordings with months-long stability. To date, no recording technology offers these features in combination. Here, we present an approach that aims to address these limitations. We conceived genetically encoded electrophysiology, in which we establish a covalent link between genetically tagged neurons and surface modified electrodes via novel engineered conductive polymers. The approach retains millisecond temporal resolution native to electrophysiology while combining genetic specificity of tagged neurons. This method utilizes a covalent reaction between the HaloTag protein and its chemical ligand, which was successfully used by the Tadross lab for cell-type specific delivery of drugs. We detail the development of each component of genetically encoded electrophysiology, beginning with engineered conductive polymers and incorporation of HaloTag binding ligand. Through different assays, we verify both successful polymerization onto electrodes and HaloTag ligand availability for HaloTag protein binding. We further demonstrate the concept in cultured neurons using custom microelectrode arrays and development platform. We provide proof-of-concept data to support our approach and demonstrate its feasibility. We discuss the implications of future work which could build on the proof-of-concept technology to refine the approach, optimize it for use in culture and adapt it to in vivo—animal—recordings.





Weaver, Isaac (2022). Electrogenetics: Genetically Encoded Electrophysiology. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/26831.


Dukes student scholarship is made available to the public using a Creative Commons Attribution / Non-commercial / No derivative (CC-BY-NC-ND) license.