Issue 4, 2020

Recent advances in fast-scan cyclic voltammetry

Abstract

Fast-scan cyclic voltammetry (FSCV) at carbon-fiber microelectrodes (CFMEs) is a versatile electrochemical technique to probe neurochemical dynamics in vivo. Progress in FSCV methodology continues to address analytical challenges arising from biological needs to measure low concentrations of neurotransmitters at specific sites. This review summarizes recent advances in FSCV method development in three areas: (1) waveform optimization, (2) electrode development, and (3) data analysis. First, FSCV waveform parameters such as holding potential, switching potential, and scan rate have been optimized to monitor new neurochemicals. The new waveform shapes introduce better selectivity toward specific molecules such as serotonin, histamine, hydrogen peroxide, octopamine, adenosine, guanosine, and neuropeptides. Second, CFMEs have been modified with nanomaterials such as carbon nanotubes or replaced with conducting polymers to enhance sensitivity, selectivity, and antifouling properties. Different geometries can be obtained by 3D-printing, manufacturing arrays, or fabricating carbon nanopipettes. Third, data analysis is important to sort through the thousands of CVs obtained. Recent developments in data analysis include preprocessing by digital filtering, principal components analysis for distinguishing analytes, and developing automated algorithms to detect peaks. Future challenges include multisite measurements, machine learning, and integration with other techniques. Advances in FSCV will accelerate research in neurochemistry to answer new biological questions about dynamics of signaling in the brain.

Graphical abstract: Recent advances in fast-scan cyclic voltammetry

Article information

Article type
Minireview
Submitted
26 sept. 2019
Accepted
27 déc. 2019
First published
27 déc. 2019

Analyst, 2020,145, 1087-1102

Recent advances in fast-scan cyclic voltammetry

P. Puthongkham and B. J. Venton, Analyst, 2020, 145, 1087 DOI: 10.1039/C9AN01925A

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