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Date of Award

Spring 2019

Rights

Access restricted for 1 year to EWU users with an active EWU NetID

Date Available to Non-EWU Users

June 2020

Document Type

Thesis: EWU Only

Degree Name

Master of Science (MS) in Biology

Department

Biology

Abstract

Dopamine (DA) is a neurohormone highly involved in learning and memory. Oxytocin (OXT), another neurohormone, has also been implicated in learning and memory. Fast-scan cyclic voltammetry (FSCV) is a method used for the real-time examination of DA neurotransmission in the brain. Implanting FSCV electrodes is an invasive technique that likely results in an inflammatory response (i.e. gliosis) that can restrict FSCV recording of DA signals. Neural cell adhesion molecule (NCAM) may reduce gliosis and potentially improve the ability of FSCV electrodes to monitor DA signaling. Chapter 1 Methods: FSCV electrodes were coated with NCAM and implanted in the rat brain. Non-NCAM coated electrodes were implanted in the contralateral hemisphere. Electrode recoveries (stability of electrode signals) were monitored for 8 weeks post surgery. Chapter 1 Results: NCAM coated electrodes stabilized sooner than their control counterparts (n=8). Chapter 2 Methods: FSCV electrodes were implanted in the rat brain and DA signals were experimentally evoked (i.e. electrically stimulated). Once clear DA signals were evoked and recorded, rats were exposed to intranasal OXT (n=3) or saline (n=3) and OXTinduced changes DA signaling was monitored for 1 h. Chapter 2 Results: Intranasal OXT increased DA signaling (i.e. peak height of DA current), relative to controls. Conclusions: NCAM coating expedites the ability of FSCV electrodes to monitor DA signaling in the rat brain. In addition, intranasal OXT increases DA neurotransmission, elucidating a potential mechanism for a modulatory role of OXT in learning and memory.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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