Multifunctional fiber-based neural interfaces

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2018

Author dc:creator

• Park, Seongjun

Advisor dc:contributor.advisor

• Polina Anikeeva.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/118086

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/118086