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      Graded recruitment of pupil-linked neuromodulation by parametric stimulation of the vagus nerve

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          Abstract

          Vagus nerve stimulation (VNS) is thought to affect neural activity by recruiting brain-wide release of neuromodulators. VNS is used in treatment-resistant epilepsy, and is increasingly being explored for other disorders, such as depression, and as a cognitive enhancer. However, the promise of VNS is only partially fulfilled due to a lack of mechanistic understanding of the transfer function between stimulation parameters and neuromodulatory response, together with a lack of biosensors for assaying stimulation efficacy in real time. We here develop an approach to VNS in head-fixed mice on a treadmill and show that pupil dilation is a reliable and convenient biosensor for VNS-evoked cortical neuromodulation. In an ‘optimal’ zone of stimulation parameters, current leakage and off-target effects are minimized and the extent of pupil dilation tracks VNS-evoked basal-forebrain cholinergic axon activity in neocortex. Thus, pupil dilation is a sensitive readout of the moment-by-moment, titratable effects of VNS on brain state.

          Abstract

          Despite its wide and growing use, the mechanisms by which in vivo vagus nerve stimulation (VNS) exerts its therapeutic benefits are still largely unknown. Here, the authors show in mice that pupil dilation is a reliable and noninvasive biosensor for titratable VNS-evoked cortical neuromodulation by acetylcholine.

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          Most cited references55

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          Nonparametric statistical testing of EEG- and MEG-data.

          In this paper, we show how ElectroEncephaloGraphic (EEG) and MagnetoEncephaloGraphic (MEG) data can be analyzed statistically using nonparametric techniques. Nonparametric statistical tests offer complete freedom to the user with respect to the test statistic by means of which the experimental conditions are compared. This freedom provides a straightforward way to solve the multiple comparisons problem (MCP) and it allows to incorporate biophysically motivated constraints in the test statistic, which may drastically increase the sensitivity of the statistical test. The paper is written for two audiences: (1) empirical neuroscientists looking for the most appropriate data analysis method, and (2) methodologists interested in the theoretical concepts behind nonparametric statistical tests. For the empirical neuroscientist, a large part of the paper is written in a tutorial-like fashion, enabling neuroscientists to construct their own statistical test, maximizing the sensitivity to the expected effect. And for the methodologist, it is explained why the nonparametric test is formally correct. This means that we formulate a null hypothesis (identical probability distribution in the different experimental conditions) and show that the nonparametric test controls the false alarm rate under this null hypothesis.
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            An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance.

            Historically, the locus coeruleus-norepinephrine (LC-NE) system has been implicated in arousal, but recent findings suggest that this system plays a more complex and specific role in the control of behavior than investigators previously thought. We review neurophysiological and modeling studies in monkey that support a new theory of LC-NE function. LC neurons exhibit two modes of activity, phasic and tonic. Phasic LC activation is driven by the outcome of task-related decision processes and is proposed to facilitate ensuing behaviors and to help optimize task performance (exploitation). When utility in the task wanes, LC neurons exhibit a tonic activity mode, associated with disengagement from the current task and a search for alternative behaviors (exploration). Monkey LC receives prominent, direct inputs from the anterior cingulate (ACC) and orbitofrontal cortices (OFC), both of which are thought to monitor task-related utility. We propose that these frontal areas produce the above patterns of LC activity to optimize utility on both short and long timescales.
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              MNE software for processing MEG and EEG data.

              Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals originating from neural currents in the brain. Using these signals to characterize and locate brain activity is a challenging task, as evidenced by several decades of methodological contributions. MNE, whose name stems from its capability to compute cortically-constrained minimum-norm current estimates from M/EEG data, is a software package that provides comprehensive analysis tools and workflows including preprocessing, source estimation, time-frequency analysis, statistical analysis, and several methods to estimate functional connectivity between distributed brain regions. The present paper gives detailed information about the MNE package and describes typical use cases while also warning about potential caveats in analysis. The MNE package is a collaborative effort of multiple institutes striving to implement and share best methods and to facilitate distribution of analysis pipelines to advance reproducibility of research. Full documentation is available at http://martinos.org/mne. © 2013.
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                Author and article information

                Contributors
                matthew.mcginley@bcm.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                9 March 2021
                9 March 2021
                2021
                : 12
                : 1539
                Affiliations
                [1 ]GRID grid.39382.33, ISNI 0000 0001 2160 926X, Department of Neuroscience, , Baylor College of Medicine, ; Houston, TX USA
                [2 ]GRID grid.416975.8, ISNI 0000 0001 2200 2638, Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, ; Houston, TX USA
                [3 ]Department of Biomedical Engineering, Madison, WI USA
                [4 ]GRID grid.169077.e, ISNI 0000 0004 1937 2197, Department of Biomedical Engineering, , Purdue University, ; West Lafayette, IN USA
                [5 ]GRID grid.21940.3e, ISNI 0000 0004 1936 8278, Department of Electrical and Computer Engineering, , Rice University, ; Houston, TX USA
                Author information
                http://orcid.org/0000-0002-5875-8282
                http://orcid.org/0000-0002-6363-4137
                http://orcid.org/0000-0002-8710-7497
                http://orcid.org/0000-0002-6516-9670
                Article
                21730
                10.1038/s41467-021-21730-2
                7943774
                33750784
                8e12c537-3952-411e-abc5-442fd812d118
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 24 March 2020
                : 29 January 2021
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                neuroscience,auditory system,cortex,locus coeruleus,wakefulness
                Uncategorized
                neuroscience, auditory system, cortex, locus coeruleus, wakefulness

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