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      Automated behavioural analysis reveals the basic behavioural repertoire of the urochordate Ciona intestinalis

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          Abstract

          Quantitative analysis of animal behaviour in model organisms is becoming an increasingly essential approach for tackling the great challenge of understanding how activity in the brain gives rise to behaviour. Here we used automated image-based tracking to extract behavioural features from an organism of great importance in understanding the evolution of chordates, the free-swimming larval form of the tunicate Ciona intestinalis, which has a compact and fully mapped nervous system composed of only 231 neurons. We analysed hundreds of videos of larvae and we extracted basic geometric and physical descriptors of larval behaviour. Importantly, we used machine learning methods to create an objective ontology of behaviours for C. intestinalis larvae. We identified eleven behavioural modes using agglomerative clustering. Using our pipeline for quantitative behavioural analysis, we demonstrate that C. intestinalis larvae exhibit sensory arousal and thigmotaxis. Notably, the anxiotropic drug modafinil modulates thigmotactic behaviour. Furthermore, we tested the robustness of the larval behavioural repertoire by comparing different rearing conditions, ages and group sizes. This study shows that C. intestinalis larval behaviour can be broken down to a set of stereotyped behaviours that are used to different extents in a context-dependent manner.

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          idTracker: tracking individuals in a group by automatic identification of unmarked animals.

          Animals in groups touch each other, move in paths that cross, and interact in complex ways. Current video tracking methods sometimes switch identities of unmarked individuals during these interactions. These errors propagate and result in random assignments after a few minutes unless manually corrected. We present idTracker, a multitracking algorithm that extracts a characteristic fingerprint from each animal in a video recording of a group. It then uses these fingerprints to identify every individual throughout the video. Tracking by identification prevents propagation of errors, and the correct identities can be maintained indefinitely. idTracker distinguishes animals even when humans cannot, such as for size-matched siblings, and reidentifies animals after they temporarily disappear from view or across different videos. It is robust, easy to use and general. We tested it on fish (Danio rerio and Oryzias latipes), flies (Drosophila melanogaster), ants (Messor structor) and mice (Mus musculus).
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            Automated image-based tracking and its application in ecology.

            The behavior of individuals determines the strength and outcome of ecological interactions, which drive population, community, and ecosystem organization. Bio-logging, such as telemetry and animal-borne imaging, provides essential individual viewpoints, tracks, and life histories, but requires capture of individuals and is often impractical to scale. Recent developments in automated image-based tracking offers opportunities to remotely quantify and understand individual behavior at scales and resolutions not previously possible, providing an essential supplement to other tracking methodologies in ecology. Automated image-based tracking should continue to advance the field of ecology by enabling better understanding of the linkages between individual and higher-level ecological processes, via high-throughput quantitative analysis of complex ecological patterns and processes across scales, including analysis of environmental drivers. Copyright © 2014 Elsevier Ltd. All rights reserved.
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              Modafinil: a review of neurochemical actions and effects on cognition.

              Modafinil (2-[(Diphenylmethyl) sulfinyl] acetamide, Provigil) is an FDA-approved medication with wake-promoting properties. Pre-clinical studies of modafinil suggest a complex profile of neurochemical and behavioral effects, distinct from those of amphetamine. In addition, modafinil shows initial promise for a variety of off-label indications in psychiatry, including treatment-resistant depression, attention-deficit/hyperactivity disorder, and schizophrenia. Cognitive dysfunction may be a particularly important emerging treatment target for modafinil, across these and other neuropsychiatric disorders. We aimed to comprehensively review the empirical literature on neurochemical actions of modafinil, and effects on cognition in animal models, healthy adult humans, and clinical populations. We searched PubMed with the search term 'modafinil' and reviewed all English-language articles for neurochemical, neurophysiological, cognitive, or information-processing experimental measures. We additionally summarized the pharmacokinetic profile of modafinil and clinical efficacy in psychiatric patients. Modafinil exhibits robust effects on catecholamines, serotonin, glutamate, gamma amino-butyric acid, orexin, and histamine systems in the brain. Many of these effects may be secondary to catecholamine effects, with some selectivity for cortical over subcortical sites of action. In addition, modafinil (at well-tolerated doses) improves function in several cognitive domains, including working memory and episodic memory, and other processes dependent on prefrontal cortex and cognitive control. These effects are observed in rodents, healthy adults, and across several psychiatric disorders. Furthermore, modafinil appears to be well-tolerated, with a low rate of adverse events and a low liability to abuse. Modafinil has a number of neurochemical actions in the brain, which may be related to primary effects on catecholaminergic systems. These effects are in general advantageous for cognitive processes. Overall, modafinil is an excellent candidate agent for remediation of cognitive dysfunction in neuropsychiatric disorders.
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                Author and article information

                Contributors
                Marios.Chatzigeorgiou@uib.no
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                20 February 2019
                20 February 2019
                2019
                : 9
                : 2416
                Affiliations
                [1 ]ISNI 0000 0004 1936 7443, GRID grid.7914.b, Sars International Centre for Marine Molecular Biology, , University of Bergen, Thormøhlensgate 55, ; 5006 Bergen, Norway
                [2 ]ISNI 0000 0001 2175 3544, GRID grid.418671.d, École Nationale Supérieure de Chimie de Montpellier, 240 Avenue du Professeur Emile Jeanbrau, ; 34090 Montpellier, France
                [3 ]ISNI 0000 0001 2217 0017, GRID grid.7452.4, University Paris Diderot-Paris7, 5 rue Thomas Mann, ; 75013 Paris, France
                Author information
                http://orcid.org/0000-0002-4795-6558
                Article
                38791
                10.1038/s41598-019-38791-5
                6382837
                30787329
                2cae5a9a-8ebd-4fb1-b47e-986a6f849b53
                © The Author(s) 2019

                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
                : 30 October 2018
                : 9 January 2019
                Funding
                Funded by: Sars Centre Core Budget
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