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Proceedings Paper

Concurrent electrophysiology and TPM/OCT imaging of long-term implanted electrodes (Conference Presentation)
Author(s): Daniel X. Hammer; Yu-Rong Gao; Meijun Ye; Cristin G. Welle

Paper Abstract

Microelectrodes implanted in the brain cause mechanical damage to the tissue that mediate neuroinflammation and eventual encapsulation by microglia and astrocytes. Electrophysiological signals recorded from implants used in brain-computer interfaces (BCI) degrade over time, limiting their usefulness, but the precise causes and progression are not fully understood. We are investigating the dynamics of brain morphological changes and neuroinflammation with a multimodal approach to better understand the potential causes of implant failure. We performed weekly optical coherence tomography (OCT)-guided two-photon microscopy (TPM) in the region around microelectrodes inserted under a cranial window concurrent with electrophysiological recordings. Transgenic mouse cohorts studied include Thy1-YFP, Cx3cr1, and GFAP-GFP to image neurons, microglia, and astrocytes, respectively. Single-shank, 16-channel, Michigan-style microelectrodes were inserted under the window at a 15-20° angle with an insertion depth up to cortical layer 5. Single-unit and local field potential (LFP) recordings were collected for 15 minutes while the animals moved freely in their home cages. Cellular and vascular morphology were monitored using TPM and OCT at timepoints matched to the recordings. In preliminary data, we observed a decay of neural firing rates in most of the channels after implantation. The relationship between electrophysiological measures (e.g., neural firing rate, LFP power) and neural/vascular morphological measurements (e.g., cell density, glial migration, blood flow changes) will be quantified. The multimodal approach combining electrophysiology and optical imaging provides a broader picture of the multifactorial nature of the response to implanted electrodes. Understanding and accounting for the response may lead to better BCI designs and approaches.

Paper Details

Date Published: 19 April 2017
PDF: 1 pages
Proc. SPIE 10051, Neural Imaging and Sensing, 1005108 (19 April 2017); doi: 10.1117/12.2253331
Show Author Affiliations
Daniel X. Hammer, U.S. Food and Drug Administration (United States)
Yu-Rong Gao, U.S. Food and Drug Administration (United States)
Meijun Ye, U.S. Food and Drug Administration (United States)
Cristin G. Welle, Univ. of Colorado Denver (United States)


Published in SPIE Proceedings Vol. 10051:
Neural Imaging and Sensing
Qingming Luo; Jun Ding, Editor(s)

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