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Flexible and Fully Implantable Upconversion Device for Wireless Optogenetic Stimulation of Spinal Cord in Behaving Animals

Abstract

Wireless optogenetics based on upconversion technique recently provides an effective and interference-free alternative for remote brain stimulation and inhibition in behaving animals, which is of great promises for neuroscience research. However, more versatile upconversion devices are yet implemented for neural tissues other than the brain. In this study, a flexible and fully implantable upconversion device is developed for epidural spinal cord stimulation. The upconversion device is fabricated via a straightforward two-step heat-pulling process using biocompatible thermoplastic polypropylene as a backbone, which is mixed with upconversion nanoparticles (UCNPs) to form a flexible optrode device that converts near infrared (NIR) irradiation to visible lights for optogenetic manipulation of spinal cord tissues. In this system, the flexible upconversion device is fully-implantable within the rigid spine structure, and shows excellent long-term biocompatibility even after four month experiment. In anesthetized mice, the UCNPs device implanted at L4 vertebra can be used to reliably evoke hindlimb muscular activity upon NIR triggering. In behaving mice, neural modulation by the same UCNPs devices effectively inhibits the animals’ movement as a result of remote spinal cord stimulation. We believe that the flexible upconversion device provides new possibilities for wireless neural modulation in spinal cord tissues, and will become a valuable supplement to the current toolsets of upconversion based wireless optogenetics.

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Publication details

The article was received on 02 Sep 2019, accepted on 04 Nov 2019 and first published on 06 Nov 2019


Article type: Paper
DOI: 10.1039/C9NR07583F
Nanoscale, 2019, Accepted Manuscript

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    Flexible and Fully Implantable Upconversion Device for Wireless Optogenetic Stimulation of Spinal Cord in Behaving Animals

    Y. Wang, K. Xie, H. Yue, X. Chen, X. Luo, Q. Liao, M. Liu, F. Wang and P. Shi, Nanoscale, 2019, Accepted Manuscript , DOI: 10.1039/C9NR07583F

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