Quantitative measurement of the phasic (changes in several seconds) and tonic (changes in minutes to hours) level changes of neurotransmitters is an essential technique for understanding brain functions and brain diseases regulated by the neurotransmitters. However, monitoring phasic and tonic levels of multiple neurotransmitters is still a challenging technology. Microdialysis can measure the tonic levels of multiple neurotransmitters simultaneously but has a low temporal resolution (minute) to analyze precisely. Fast-scan cyclic voltammetry (FSCV) has high temporal resolution and high sensitivity, but it was not able to simultaneously measure the tonic level of multiple neurotransmitters. The recently proposed deep learning-based FSCV method was still only capable of phasic concentration estimation of neurotransmitters. In this study, we estimate the tonic levels of dopamine and serotonin simultaneously by training a deep-learning network with the extracted tonic information from the FSCV. The proposed deep learning model was validated in vitro to simultaneously estimate tonic concentrations of two neurotransmitters with statistically significantly higher accuracy than previously proposed background subtraction-based models (p<0.001). In particular, in the case of serotonin concentration estimation error, the proposed model showed higher prediction performance than the background subtraction-based model (48 nM and 73 nM, respectively). We expect that the proposed technique will help simultaneous measurement of the phasic and tonic levels of numerous neurotransmitters in vivo soon.Clinical Relevance— This study proposes a method to simultaneously measure tonic dopamine and tonic serotonin with high temporal resolution with a single electrode in the brain.
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 widely used electrochemical technique for measuring real-time in vivo dopamine level changes. Standard FSCV has only been used to analyze “phasic dopamine” (changes in seconds), because the gradual generation of background charging current is inevitable, and acts as the main noise source in the low-frequency band. Although “tonic dopamine” (changes in minutes to hours) is key 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, but 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, post-processing 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.
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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