Building New Tools for Measuring and Analyzing Dopaminergic Signaling Using Fast-Scan Cyclic Voltammetry

Abstract

To better understand the brain and how it communicates, we need to build tools that can quantify neurochemical signaling. By understanding brain function, new treatments can be developed for neurodegenerative diseases and disorders. In addition, by gaining insight into the inner workings of the brain, we can answer fundamental questions regarding learning, memory, and behavior. In this dissertation, several new tools for neurotransmitter measurement and analysis will be discussed. A new method, alternating current-coupled voltammetry has been developed, making in vivo neurotransmitter measurements safe for the subject, and moving fast-scan cyclic-voltammetry (FSCV) towards FDA compliance. A measurement and software platform was developed that expands the capabilities of FSCV, and fast-scan controlled-adsorption voltammetry (FSCAV). This new system not only allows for FSCV and FSCAV measurements to occur simultaneously, allowing for the measurement of both tonic and phasic signaling but also expands the instrumentation to allow for more individually addressable electrodes for neurotransmitter measurement. The system can also measure multiple neurotransmitters with different waveforms on discrete electrodes which previously was limited. Data analysis for FSCV was also expanded by the application of machine learning in automated neurotransmitter identification. We built classification and regression models to interpret and quantify unknown raw voltammetric data without input from the operator. Lastly, commonly used carbon-fibers in microelectrodes were studied to determine the structure-function relationship between the chemical properties of each, for application selection. Together these new tools are an important advancement in neuroanalytical instrumentation by enabling multi-region analysis, and automated identification of chemical species.