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      Second-Derivative-Based Background Drift Removal for a Tonic Dopamine Measurement in Fast-Scan Cyclic Voltammetry.

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          Abstract

          The dysregulation of dopamine, a neuromodulator, is associated with a broad spectrum of brain disorders, including Parkinson's disease, addiction, and schizophrenia. Quantitative measurements of dopamine are essential for understanding dopamine functional dynamics. Fast-scan cyclic voltammetry (FSCV) is the most popular electrochemical technique for measuring real-time in vivo dopamine level changes. Standard FSCV has only analyzed "phasic dopamine" (changes in seconds) because the gradual generation of background charging current is inevitable and is the primary noise source in the low-frequency band. Although "tonic dopamine" (changes in minutes to hours) is critical for understanding the dopamine system, an electrochemical technique capable of simultaneously measuring phasic and tonic dopamine in an in vivo environment has not been established. Several modified voltammetric techniques have been developed for measuring tonic dopamine; however, the sampling rates (0.1-0.05 Hz) are too low to be useful. Further investigation of the in vivo applicability of previously developed background drift removal methods for measuring tonic dopamine levels is required. We developed a second-derivative-based background removal (SDBR) method for simultaneously measuring phasic and tonic neurotransmitter levels in real-time. The performance of this technique was tested via in silico and in vitro tonic dopamine experiments. Furthermore, its applicability was tested in vivo. SDBR is a simple, robust, postprocessing technique that can extract tonic neurotransmitter levels from all FSCV data. As SDBR is calculated in individual-scan voltammogram units, it can be applied to any real-time closed-loop system that uses a neurotransmitter as a biomarker.

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          Author and article information

          Journal
          Anal Chem
          Analytical chemistry
          American Chemical Society (ACS)
          1520-6882
          0003-2700
          Aug 23 2022
          : 94
          : 33
          Affiliations
          [1 ] Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), 333, Techno jungang-daero, Hyeonpung-myeon, Dalseong-gun, Daegu 42988, Republic of Korea.
          [2 ] Department of Brain and Cognitive Science, DGIST, 333, Techno jungang-daero, Hyeonpung-myeon, Dalseong-gun, Daegu 42988, Republic of Korea.
          [3 ] College of Transdisciplinary studies, DGIST, 333, Techno jungang-daero, Hyeonpung-myeon, Dalseong-gun, Daegu 42988, Republic of Korea.
          [4 ] Brain Engineering Convergence Research Center, DGIST, 333, Techno jungang-daero, Hyeonpung-myeon, Dalseong-gun, Daegu 42988, Republic of Korea.
          Article
          10.1021/acs.analchem.2c01047
          35939536
          241d7a40-8274-4081-83b1-96c71451d7ef
          History

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