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bioRxiv · 10.1101/2021.08.02.454747

Low amplitude burst detection of catecholamines

Eltahir, A. M.·White, J.·Lohrenz, T. M.·Montague, R.
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Abstract

Machine learning advances in electrochemical detection have recently produced sub-second and concurrent detection of dopamine and serotonin during perception and action tasks in conscious humans. Here, we present a new machine learning approach to sub-second, concurrent separation of dopamine, norepinephrine, and serotonin. The method exploits a low amplitude burst protocol for the controlled voltage waveform and we demonstrate its efficacy by showing how it separates dopamine-induced signals from norepinephrine induced signals. Previous efforts to deploy electrochemical detection of dopamine in vivo have not separated the dopamine-dependent signal from a norepinephrine-dependent signal. Consequently, this new method can provide new insights into concurrent signaling by these two important neuromodulators.

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Eltahir, A. M., White, J., Lohrenz, T. M., Montague, R.. 2021-08-04. Low amplitude burst detection of catecholamines. https://doi.org/10.1101/2021.08.02.454747

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