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Direct in Vivo Electrochemical Detection of Resting Dopamine Using Poly(3,4-ethylenedioxythiophene)/Carbon Nanotube Functionalized Microelectrodes


Dopamine (DA) is a monoamine neurotransmitter responsible for the maintenance of a variety of vital life functions. In vivo DA signaling occurs over multiple time scales, from subsecond phasic release due to dopamine neuron firing to tonic release responsible for long-term DA concentration changes over minutes to hours. Due to the complex, multifaceted nature of DA signaling, analytical sensing technology must be capable of recording DA from multiple locations and over multiple time scales. Decades of research has focused on improving in vivo detection capabilities for subsecond phasic DA, but the accurate detection of absolute resting DA levels in real time has proven challenging. We have developed a poly(3,4-ethylenedioxythiophene) (PEDOT)-based nanocomposite coating that exhibits excellent DA sensing capabilities for resting DA. PEDOT/functionalized carbon nanotube (PEDOT/CNT)-coated carbon fiber microelectrodes (CFEs) are capable of directly measuring resting DA using square wave voltammetry (SWV) with high sensitivity and selectivity. Incorporation of a PEDOT/CNT coating significantly increases the sensitivity for the detection of resting DA by a factor of 422. SWV measurements performed at PEDOT/CNT-functionalized CFEs implanted in the rat dorsal striatum reveal the absolute basal DA concentration to be 82 ± 6 nM. Systemic administration of the dopamine transporter inhibitor nomifensine increases resting DA to a maximum 207 ± 16 nM at 28 ± 2 min following injection. PEDOT/CNT was also functionalized onto individual gold electrode sites along silicon microelectrode arrays (MEAs) to produce a multisite DA sensing electrode. MEA implantation allows for the quantification of basal DA from different brain regions with excellent spatial resolution. SWV detection paired with PEDOT/CNT functionalization is highly adaptable and shows great promise for tonic DA detection with high spatial and temporal resolution.


Ian Mitchell Taylor, Nikita Anurag Patel, Noah Chaim Freedman, Elisa Castagnola, Xinyan Tracy Cui

Published: 2019

PMID: 31512849


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Research Area:

Methodological Studies