High fidelity peripheral nerve interfaces
Abstract/Contents
- Abstract
- The peripheral nervous system is integral to how we perceive and interact with the world around us. It bridges our central nervous system to our organs and limbs, enabling sensorimotor control and homeostasis. Through peripheral nerve interfaces (PNIs), recording and modulation of neural activity have enabled control of prosthetic arms for amputees, restored functional grasp and bladder control in spinal cord injuries, and treated drug-resistant epilepsy and depression. However, major challenges lie in their selectivity, chronic stability, and scalability. In the first part of my work, I designed biomimetic axon-like thin-film electronics mirroring the dimensions and mechanical properties of native axons. For the first time, I demonstrated that we could evoke highly selective moments in individual mouse toes. The device could record single unit activity during locomotion and be used to decode hind limb position and velocity. Finally, immunohistochemistry revealed a lack of a fibrotic capsule around the device 1-month post-implantation, indicative of minimal foreign body response. In the second part of my work, I developed a novel microstructure, facilitating the scalable connectorization of thousands of channels between thin-film electronics and CMOS chips at a millimeter scale. This increased the channel density by 17 times in comparison to state-of-the-art methods. Leveraging this technology, I subsequently explored the use of thin-film electronics outside of the peripheral nervous system. In the Scn8a+/- in vivo model of absence epilepsy, I discovered that seizure dynamics do not have a constant site of onset or propagation trajectory. Additionally, I demonstrated that organoid neural dynamics can be recorded at the air-liquid interface with increased cell viability.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Zhao, Eric Tianjiao |
|---|---|
| Degree supervisor | Bao, Zhenan |
| Degree supervisor | Melosh, Nicholas A |
| Thesis advisor | Bao, Zhenan |
| Thesis advisor | Melosh, Nicholas A |
| Thesis advisor | Salleo, Alberto |
| Degree committee member | Salleo, Alberto |
| Associated with | Stanford University, School of Engineering |
| Associated with | Stanford University, Department of Chemical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Eric Tianjiao Zhao. |
|---|---|
| Note | Submitted to the Department of Chemical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/qb074jt1854 |
Access conditions
- Copyright
- © 2023 by Eric Tianjiao Zhao
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...