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      Synchronous Measurements of Extracellular Action Potentials and Neurochemical Activity with Carbon Fiber Electrodes in Nonhuman Primates

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          Abstract

          Measuring the dynamic relationship between neuromodulators, such as dopamine, and neuronal action potentials is imperative to understand how these fundamental modes of neural signaling interact to mediate behavior. Here, we developed methods to measure concurrently dopamine and extracellular action potentials (i.e., spikes) and applied these in a monkey performing a behavioral task. Standard fast-scan cyclic voltammetric (FSCV) electrochemical (EChem) and electrophysiological (EPhys) recording systems are combined and used to collect spike and dopamine signals, respectively, from an array of carbon fiber (CF) sensors implanted in the monkey striatum. FSCV requires the application of small voltages at the implanted sensors to measure redox currents generated from target molecules, such as dopamine. These applied voltages create artifacts at neighboring EPhys-measurement sensors, producing signals that may falsely be classified as physiological spikes. Therefore, simple automated temporal interpolation algorithms were designed to remove these artifacts and enable accurate spike extraction. We validated these methods using simulated artifacts and demonstrated an average spike recovery rate of 84.5%. This spike extraction was performed on data collected from concurrent EChem and EPhys recordings made in a task-performing monkey to discriminate cell-type specific striatal units. These identified units were shown to correlate to specific behavioral task parameters related to reward size and eye-movement direction. Synchronous measures of spike and dopamine signals displayed contrasting relations to the behavioral task parameters, as taken from our small set of representative data, suggesting a complex relationship between these two modes of neural signaling. Future application of our methods will help advance our understanding of the interactions between neuromodulator signaling and neuronal activity, to elucidate more detailed mechanisms of neural circuitry and plasticity mediating behaviors in health and in disease.

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          The capacity to predict future events permits a creature to detect, model, and manipulate the causal structure of its interactions with its environment. Behavioral experiments suggest that learning is driven by changes in the expectations about future salient events such as rewards and punishments. Physiological work has recently complemented these studies by identifying dopaminergic neurons in the primate whose fluctuating output apparently signals changes or errors in the predictions of future salient and rewarding events. Taken together, these findings can be understood through quantitative theories of adaptive optimizing control.
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            Advanced carbon electrode materials for molecular electrochemistry.

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              Ultrafast neuronal imaging of dopamine dynamics with designed genetically encoded sensors

              Neuromodulatory systems exert profound influences on brain function. Understanding how these systems modify the operating mode of target circuits requires measuring spatiotemporally precise neuromodulator release. We developed dLight1, an intensity-based genetically encoded dopamine indicator, to enable optical recording of dopamine dynamics with high spatiotemporal resolution in behaving mice. We demonstrated the utility of dLight1 by imaging dopamine dynamics simultaneously with pharmacological manipulation, electrophysiological or optogenetic stimulation, and calcium imaging of local neuronal activity. dLight1 enabled chronic tracking of learning-induced changes in millisecond dopamine transients in striatum. Further, we used dLight1 to image spatially distinct, functionally heterogeneous dopamine transients relevant to learning and motor control in cortex. We also validated our sensor design platform for developing norepinephrine, serotonin, melatonin, and opioid neuropeptide indicators.
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                Author and article information

                Journal
                bioRxiv
                BIORXIV
                bioRxiv
                Cold Spring Harbor Laboratory
                24 December 2023
                : 2023.12.23.573130
                Affiliations
                [1 ]Department of Bioengineering, University of Pittsburgh, USA
                [2 ]McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, USA
                [3 ]Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
                Author notes

                Author Contributions: H.N.S. and U.A. designed and validated methods. H.N.S. performed in vivo experiments. H.N.S, U.A., J.C., and R.M. analyzed data. H.N.S., D.J.G., and A.M.G. guided methods and experiments. H.N.S., U.A., and J.C. wrote manuscript with comments from all other authors.

                Author information
                http://orcid.org/0000-0001-5455-3207
                http://orcid.org/0000-0002-2801-7854
                http://orcid.org/0000-0002-4326-7720
                http://orcid.org/0000-0002-0389-982X
                Article
                10.1101/2023.12.23.573130
                10769335
                38187624
                4260ce81-895e-46b3-8325-dd5fb110f7de

                This work is licensed under a Creative Commons Attribution 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.

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                Categories
                Article

                multi-modal electrochemical and electrical recording,dopamine,fast-scan cyclic voltammetry,electrophysiology,neurotransmitters

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