PhD defence by Kunyang Sui

Supervisors

• Principal supervisor: Associate Professor Christos Markos, DTU Electro
• Co-supervisor: Associate Professor Rune W. Berg, University of Copenhagen

Evaluation Board

• Senior Researcher Ferruccio Pisanello, Center For Biomolecular Nanotechnologies, Instituto Italiano di Tecnologia, IT
• Professor Preben Kidmose, Department of Electrical and Computer Engineering, Aarhus University

Chairman

• Associate Professor Jesper Lægsgaard, DTU Electro

Master of Ceremony

• Senior Researcher Getinet Woyessa, DTU Electro

Abstract:

The brain is the most important and complex part of the human body. Comprehending the intricated function and the dynamic nerve system in deep brain regions is paramount for suppressing and treating neurological diseases such as Parkinson’s, epilepsy, major depression, etc. Therefore, there is a significant drive from many research groups around the globe towards the development of implantable novel neural tools to explore brain function and its neural circuit dynamics. Traditionally used semiconductor-based brain implants are produced with complicated procedures such as microfabrication or lithography, which result in a high production cost. Additionally, their high stiffness would cause serious inflammatory responses after implantation and lead to a reduced signal-to-noise ratio in neural activity recordings, especially during longterm in vivo experiments. In this thesis, we have developed flexible multifunctional fiber-based neural devices for neuromodulation and recordings. More specifically, multi-materials and microstructures have been integrated into polymer optical fibers during the thermal drawing process to increase their functionality. Several hundred meters of multifunctional optical fibers can be produced in a single drawing process. In addition, a comprehensive study of the multifunctional fiber-based brain implant has been carried out, including the optimization of the implant design, the modification of the fabrication method, and the development of new kinds of fiber-based implants for different applications. We anticipate the polymer fiber-based neural devices presented in this thesis will open new possibilities for studying neural networks and brain functions in deep brain regions.