Abstract

Neuronal exocytosis facilitates the propagation of information through the nervous system pertaining to bodily function, memory, and emotions. Using amperometry, an electrochemical technique that directly detects electroactive molecules, the sub-millisecond dynamics of exocytosis are revealed and the modulation of neurotransmitter secretion due to neurodegenerative diseases or pharmacological treatments can be studied. The method of detection using amperometry is the exchange of electrons due to a redox reaction at an electrochemically sensitive electrode. As electroactive molecules, such as dopamine, undergo oxidation, electrons are released from the molecule to the electrode and an oxidation current is generated and recorded. Despite the significance of traditional single-cell amperometry, it is a costly, labor-intensive, and low-throughput, procedure. The focus of this dissertation is the development of a monolithic CMOS-based neurochemical sensing system that can provide a high-throughput of up to 1024 single-cell recordings in a single experiment, significantly reducing the number of experiments required for studying the effects of neurodegenerative diseases or new pharmacological treatments on the exocytosis process. The neurochemical detection system detailed in this dissertation is based on a CMOS amplifier array that contains 1024 independent electrode-amplifier units, each of which contains a transimpedance amplifier with comparable noise performance to a high-quality electrophysiology amplifier that is used for traditional single-cell amperometry. Using this novel technology, single exocytosis events are monitored simultaneously from numerous single-cells in experiments to reveal the secretion characteristics from groups of cells before and after pharmacological treatments which target the modulation of neurotransmitters in the brain, such as drugs for depression or Parkinson's disease.

Notes

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Graduation Date

2021

Semester

Summer

Advisor

Kim, Brian

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Electrical and Computer Engineering

Degree Program

Electrical Engineering

Format

application/pdf

Identifier

CFE0008753;DP0025484

URL

https://purls.library.ucf.edu/go/DP0025484

Language

English

Release Date

August 2021

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

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