Multifunctional fiber-based neural interfaces
Author(s)
Park, Seongjun
DownloadFull printable version (26.26Mb)
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Polina Anikeeva.
Terms of use
Metadata
Show full item recordAbstract
Neurological disorders affect up to a billion people worldwide, and their socioeconomic burden is projected to increase as the population ages. However, our ability to understand and to treat neural disorders is currently limited by the lack of tools capable of interfacing with the brain over extended periods of time. This is hypothesized to stem from the mismatch in mechanical and chemical properties between the neural probes and the neural tissues, which leads to foreign body response and functional device failure due to tissue scarring in the probe vicinity. To address the challenge, I developed fiber-based bioelectronic devices integrating diverse modalities within a single platform using thermal drawing process (TDP). All-polymer or hydrogel integrated probes with optical, electrical, and fluidic capabilities were developed all within the 100-200 [mu]m diameter, which allowed one-step surgery to the mouse brain and spinal cord for optogenetic experiments. This probe also addressed the challenge of biocompatibility and enabled the recording isolated action potentials for 3 months. In addition, I applied TPD to produce biocompatible polymer-based neural scaffold with various geometries (round, rectangular, micro-grooved) and dimensions between 50-200 [mu]m. This allowed for investigation of the enhancement of neurite growth as a function of fiber parameters. We found that the topographical features and the narrow channels generally led to enhanced growth. This thesis illustrated a variety of applications of multifunctional fiber-based devices in neuroscience and neural engineering, which anticipated to enable basic studies of the nervous system and future treatment of neurological disorders.
Description
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 161-174).
Date issued
2018Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.