Date of Completion
5-5-2018
Embargo Period
5-5-2021
Advisors
Martin Han, Guoan Zheng, Sabato Santaniello
Field of Study
Biomedical Engineering
Degree
Master of Science
Open Access
Open Access
Abstract
Extensive research using penetrating electrodes implanted in the central and peripheral nervous systems has been performed for many decades with significant advances made in recent years. While these penetrating devices provide proximity to individual neurons in-vivo and perform effectively for several months, they are prone to failure over a year and longer. 2D Histology studies using serial tissue sections have been extremely insightful over the years in identifying and quantifying most of these factors such as astrocytic scar formation, microgliosis, and neuronal death, around the implant sites. However, there are significant limitations of 2D histological studies in providing a holistic picture of the problems occurring at the electrode-tissue interface. In this study, we present 3D reconstruction of serial sections to overcome the limitations of 2D histological analysis. We used a cohort of software: XuvStitchTM (XuvTools), AutoAlignerTM (Bitplane AG), and ImarisTM (Bitplane AG), and coupled these with MATLAB (The MathWorks, Inc.) programming to correct warping effects and misalignment issues. Once the 3D image volume is reconstructed, we were able to use features of ImarisTM to quantify neuronal densities and astrocytic scar tissue densities around the electrode tips of a hybrid microelectrode array. This study also demonstrated advantages of quantifying around different types of microelectrodes of a hybrid array in the same intracortical space eliminating confounding factors such as varying implantation sites, lengths of study, different animals, so on and so forth. Thereby, the performance of the microelectrodes can be attributed solely to device material properties and device fabrication process.
Recommended Citation
Nambiar, Aparna, "Development of Tools for a 3D Reconstructed Intracortical Volume Around Microelectrode Arrays" (2018). Master's Theses. 1217.
https://digitalcommons.lib.uconn.edu/gs_theses/1217
Major Advisor
Martin Han