Novel Microelectrodes and Methods for Real-Time Electrochemical Detection of Neurotransmitters

Fast-scan cyclic voltammetry (FSCV) with carbon-fiber microelectrodes (CFMEs) is one of the standard techniques for real-time detection of neurotransmitters in vivo with rapid dynamics. Although the current FSCV methods are sufficient for monitoring dopamine and some other electroactive neurotransmitters, FSCV can be further optimized to improve its analytical performance and expand the application to new molecules and new biological experiments. My dissertation examines three strategies to improve FSCV detection of neurotransmitters, including redox mechanism investigation, microelectrode modification, and automated data analysis.

Chapter 1 covers the theory and recent advances in FSCV detection of neurotransmitters, electrochemical properties of carbon nanomaterials, and signal and image processing for automated data analysis. In Chapter 2, the oxidation potential and mechanism of histamine at carbon electrodes was established to develop a better FSCV method. From electrochemical studies and surface characterization, histamine oxidation required 1.1 V and underwent one-electron, one-proton oxidation, generated polymer product, and fouled the electrode. The mechanism was utilized to explain the FSCV response of histamine. Nafion coating was then proposed to limit the electrode fouling from histamine electropolymerization to improve its FSCV detection.

Chapters 3 and 4 present two new carbon nanomaterials-modified CFMEs for dopamine detection. Carbon nanohorns (CNHs) improved the sensitivity of CFMEs for dopamine detection by increasing the electrode surface area and dopamine adsorption extent. Oxidative etching of the CNH-modified CFMEs further enhanced the adsorption and sensitivity. Nanodiamonds (NDs) size and functional groups were compared on their electrocatalytic properties and sensitivity. Carboxylated NDs improved the sensitivity by increasing the surface oxide groups and density of states to enhanced dopamine adsorption and electron transfer kinetics. Both CNHs and NDs also exhibited antifouling properties against serotonin electrochemical fouling and tissue biofouling. Thus, CNHs and NDs are beneficial for improving sensitivity and decreasing electrode fouling.

In Chapter 5, a novel software for FSCV data analysis was proposed to automate the analysis of transient adenosine events. Here, the software utilized the structural similarity image analysis to identify adenosine from the color plot by comparing it with the adenosine references. Digital filtering was also implemented to detrend the background drift to better identify smaller events. The software successfully distinguished transient adenosine events against noise and chemical interferents. The structural similarity image analysis was also generalized to detect dopamine, including simultaneous events with dopamine and adenosine.

Overall, my dissertation demonstrates novel methods to improve the FSCV detection of neurotransmitters. Knowing the histamine redox mechanism leads to better method development. Integrating carbon nanomaterials on microelectrodes enhances their electrochemical properties and analytical performance. Automated software for adenosine transient detection improves the performance and consistency of the analysis. Better methods for real-time detection of neurotransmitters will lead to the understanding of our brain chemistry to devise a treatment for neurodegenerative diseases.