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Bioelectronics: From Nanoscopic Intracellular Probe to Macroscopic Brain-Electronics Interface

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2017-04-28

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Fu, Tian-Ming. 2017. Bioelectronics: From Nanoscopic Intracellular Probe to Macroscopic Brain-Electronics Interface. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences.

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Abstract

The structural and dynamical hierarchies of biological systems, especially the brain, spanning multiple spatiotemporal scales pose great challenges for fundamental research and biomedical study. Bioelectronics-based probes with detection resolution down to the subcellular scale and volumetric coverage up to the entire system have emerged as a promising approach to overcome the challenges. However, the invasiveness of conventional bioelectronics at both nano- and macro-scopic levels has limited their potential advances. Building upon recent progresses in nanoscience and flexible electronics, my PhD work has focused on the development of novel bioelectronics with structure and mechanics resembling biological systems for monitoring and modulation at different length and time scales with minimum perturbation. On the nano-scopic scale, I will describe the design and demonstration of a subcellular electrical probe by exploiting a unique three-dimension (3D) nanowire-nanotube structure, where a nanowire detector is synthetically-integrated with a nanotube probe. On the macro-scopic scale, I will introduce a novel concept—mesh electronics, a 3D electronic network with brain-like structure and mechanics, and its long-term interface with the nervous system in vivo. First, I will report the implementation of a syringe-injection paradigm to deliver this ultra-flexible mesh electronics into in vivo brain. Importantly, I will demonstrate that centimeter-scale mesh electronics could be loaded into and injected through a needle as small as 100 µm. Besides, I will discuss an automated conductive ink printing method that can electrically link the injected mesh electronics to external recording instruments with quantitative connectivity. Second, I will demonstrate an alternative in vivo implantation paradigm for the mesh electronics by temporarily changing it to a rigid state through liquid nitrogen frozen. Third, I will present the results showing minimal gliosis and 3D neuronal interpenetration as well as stable tracking of the same neurons and neural circuits from mouse brains for at least eight months from chronically implanted mesh electronics. Significantly, these unique long-term brain-electronics interface have been further exploited to enable stable electrical stimulation and single neuron tracking in longitudinal studies of brain aging in freely behaving mice. Going beyond the brain, I will show the application of mesh electronics for in vivo electrophysiology from mouse reina, a highly curved structure that has been almost exclusively studied ex vivo. Specifically, I will demonstrate that the tissue-like mesh electronics enabled conformal integration with and chronic recording from retinal ganglion cells with characteristic light responses. Finally, I will describe about our recent efforts in increasing the density and total number of recording sites of mesh electronics to achieve stable long-term large-scale mapping of behavior related microcircuits and neural pathways. Together, the unique capabilities of the mesh electronics open up new opportunities to exploit the seamless interface between electronics and nervous systems at biologically relevant spatio-temporal scales for fundamental neuroscience research and translational applications. Looking to the future, I will briefly discuss the possibility of integrating nanoscopic multifunctional components into the tissue-like mesh electronics platform to go beyond current neuron-centric brain research by exploring glia-neuron interactions in live animals, which could potentially offer valuable insights into brain computation and glia-based therapies for neurodegenerative diseases.

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nanoelectronics, flexible electronics, bioelectronics, neurotechnology, brain probe, brain mapping

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