Serotonin transporter (SERT) and brain-derived neurotrophic factor (BDNF) are key modulators of molecular signaling, cognition and behavior. Although SERT and BDNF mutant mouse phenotypes have been extensively characterized, little is known about their self-grooming behavior. Grooming represents an important behavioral domain sensitive to environmental stimuli and is increasingly used as a model for repetitive behavioral syndromes, such as autism and attention deficit/hyperactivity disorder. The present study used heterozygous ((+/-)) SERT and BDNF male mutant mice on a C57BL/6J background and assessed their spontaneous self-grooming behavior applying both manual and automated techniques. Overall, SERT(+/-) mice displayed a general increase in grooming behavior, as indicated by more grooming bouts and more transitions between specific grooming stages. SERT(+/-) mice also aborted more grooming bouts, but showed generally unaltered activity levels in the observation chamber. In contrast, BDNF(+/-) mice displayed a global reduction in grooming activity, with fewer bouts and transitions between specific grooming stages, altered grooming syntax, as well as hypolocomotion and increased turning behavior. Finally, grooming data collected by manual and automated methods (HomeCageScan) significantly correlated in our experiments, confirming the utility of automated high-throughput quantification of grooming behaviors in various genetic mouse models with increased or decreased grooming phenotypes. Taken together, these findings indicate that mouse self-grooming behavior is a reliable behavioral biomarker of genetic deficits in SERT and BDNF pathways, and can be reliably measured using automated behavior-recognition technology.

Since various behavioral movement patterns are likely to be valid within different, unique ranges of spatial and temporal scales (e.g., instantaneous, diurnal, or seasonal) with the corresponding spatial extents, a cross-scale approach is needed for accurate classification of behaviors expressed in movement. Here, we introduce a methodology for the characterization and classification of behavioral movement data that relies on computing and analyzing movement features jointly in both the spatial and temporal domains. The proposed methodology consists of three stages. In the first stage, focusing on the spatial domain, the underlying movement space is partitioned into several zonings that correspond to different spatial scales, and features related to movement are computed for each partitioning level. In the second stage, concentrating on the temporal domain, several movement parameters are computed from trajectories across a series of temporal windows of increasing sizes, yielding another set of input features for the classification. For both the spatial and the temporal domains, the "reliable scale" is determined by an automated procedure. This is the scale at which the best classification accuracy is achieved, using only spatial or temporal input features, respectively. The third stage takes the measures from the spatial and temporal domains of movement, computed at the corresponding reliable scales, as input features for behavioral classification. With a feature selection procedure, the most relevant features contributing to known behavioral states are extracted and used to learn a classification model. The potential of the proposed approach is demonstrated on a dataset of adult zebrafish (Danio rerio) swimming movements in testing tanks, following exposure to different drug treatments. Our results show that behavioral classification accuracy greatly increases when firstly cross-scale analysis is used to determine the best analysis scale, and secondly input features from both the spatial and the temporal domains of movement are combined. These results may have several important practical applications, including drug screening for biomedical research.

A metabolite of the kynurenine pathway, kynurenic acid (KYNA) is an important endogenous neuromodulator and neuroprotector, that also exerts neurotropic effects following exogenous administration. In humans and animals, KYNA regulates affective and cognitive responses, acting mainly as an antagonist of glutamatergic receptors. However, the complete psychopharmacological profile of KYNA (which includes the activity of several neurotransmitter receptors) is poorly understood, and merit further studies. Aquatic models are rapidly emerging as useful tools in translational psychopharmacology research. Here, we exposed adult zebrafish (Danio rerio) to exogenous KYNA for 20 min, and assessed their behavior in the novel tank test. Exposure to KYNA (20 mg/L) in this paradigm evoked overt effects in fish, including decreased latency to enter the top half of the tank, increased number of top entries and longer top duration. In contrast, locomotor activity indices (swimming distance and velocity) were not affected by KYNA in this study. Overall, our results show KYNA has an anxiolytic-like pharmacological effect in zebrafish, and therefore strongly support the utility of zebrafish models in neurotropic drug screening, including drugs acting at central glutamatergic system. Robust phenotypic differences evoked by KYNA, revealed here using three-dimensional (3D) reconstructions of zebrafish locomotion in X, Y and time (Z) coordinates, confirm this notion, also demonstrating the value of 3D-based phenotyping approaches for high-throughput drug screening using zebrafish models.

Serotonin syndrome (SS) is a serious life-threatening disorder associated with elevated brain serotonergic function. With the growing use of serotonergic drugs, SS affects a large portion of general population, becoming a major biomedical concern. SS-like behaviors have also been reported in animals following administration of serotonergic drugs. Although clinical and rodent studies have provided significant insight into the etiology of SS, its exact mechanisms and risk factors remain poorly understood. The need to develop more efficient psychotropic drugs also requires extensive high-throughput screening of novel compounds using sensitive in-vivo tests. The use of zebrafish (Danio rerio) in neuroscience research is rapidly expanding due to their homology to humans, robust behavioral and physiological responses, genetic tractability, and low costs. Here we discuss the potential of zebrafish models to study SS-related phenotypes induced by selected serotonergic drugs. Overall, zebrafish exposed to serotonergic agents and their combinations exhibit a characteristic top dwelling (surfacing behavior) and hypolocomotion which may represent potential markers of SS-like states in zebrafish. This behavior in zebrafish models positively correlates with brain concentrations of serotonin, suggesting the developing utility of zebrafish (and other aquatic models) for studying SS. Future research is expected to foster high-throughput screening of drug interactions, and pharmacogenetics studies identifying zebrafish mutations implicated in pathological SS-like states.

Zebrafish (Danio rerio) are rapidly gaining popularity in translational neuroscience and behavioral research. Physiological similarity to mammals, ease of genetic manipulations, sensitivity to pharmacological and genetic factors, robust behavior, low cost, and potential for high-throughput screening contribute to the growing utility of zebrafish models in this field. Understanding zebrafish behavioral phenotypes provides important insights into neural pathways, physiological biomarkers, and genetic underpinnings of normal and pathological brain function. Novel zebrafish paradigms continue to appear with an encouraging pace, thus necessitating a consistent terminology and improved understanding of the behavioral repertoire. What can zebrafish 'do', and how does their altered brain function translate into behavioral actions? To help address these questions, we have developed a detailed catalog of zebrafish behaviors (Zebrafish Behavior Catalog, ZBC) that covers both larval and adult models. Representing a beginning of creating a more comprehensive ethogram of zebrafish behavior, this effort will improve interpretation of published findings, foster cross-species behavioral modeling, and encourage new groups to apply zebrafish neurobehavioral paradigms in their research. In addition, this glossary creates a framework for developing a zebrafish neurobehavioral ontology, ultimately to become part of a unified animal neurobehavioral ontology, which collectively will contribute to better integration of biological data within and across species.

Event Abstract Back to Event The Neuroscience Information Framework (NIF): A Unified Semantic Framework and Associated Tools for Discovery, Integration, and Utilization of Biomedical Data and Resources on the Web Jeffrey S. Grethe1*, Anita Bandrowski1, Davis Banks1, Jonathan Cachat1, Jing Chen1, Christopher Condit1, Amarnath Gupta2, Fahim Imam1, Stephen D. Larson1, Yueling Li1, Ibrahim B. Ozyurt1, Andrea M. Stagg1, Luis Marenco3, Perry Miller3, Rixin Wang3, Gordon M. Shepherd4, Giorgio Ascoli5 and Maryann E. Martone1 1 University of California, San Diego, Center for Research in Biological Systems, School of Medicine, United States 2 San Diego Supercomputer Center, United States 3 Yale University School of Medicine, Center for Medical Informatics, United States 4 Yale University, Department of Neurobiology, United States 5 George Mason University, Krasnow Institute for Advanced Study, United States The Neuroscience Information Framework (NIF; http://neuinfo.org) has recently launched a completely re-designed discovery portal for finding and integrating neuroscience-relevant resources, data, and literature. The new portal provides users with new tools to visualize data content (e.g. through analytics that provide a landscape analysis of where data can be found for topics of interest) to more personalized services via myNIF (e.g. the saving of favorite searches). The portal searches across 3 primary collections: (1) NIF Registry: A human-curated registry of neuroscience-relevant resources annotated with the NIF vocabulary; (2) NIF Literature: A full text indexed corpus derived from the PubMed Open Access subset as well as an entire index of PubMed; (3) NIF Database Federation: A federation of independent databases that enables discovery and access to public research data, contained in databases and structured web resources (e.g. queryable web services) that are sometimes referred to as the deep or hidden web. To further enable the utilization of this vast collection of information, the NIF is applying semantic web technologies to its holdings. By defining a set of standards and best practices for describing and representing data such semantic web and linked data technologies eliminate the barriers between database silos and foster the evolution of the Web into a Web of data. Such technologies are being successfully applied as integration engines for linking biological elements in many domains. Exposing NIF’s content as Linked Open Data will enable further integration with the growing amount of information available from the linked open data cloud – thereby providing much richer resources for the neuroscientist. The publication of this content relies on NIF’s comprehensive ontology (NIFSTD) that covers major domains in neuroscience, including diseases, brain anatomy, cell types, subcellular anatomy, small molecules, techniques and resource descriptors. Over the past year, NIF has continued to grow significantly in content, providing access to over 6,000 resources through the Registry, and more than 200 independent data resources in the data federation, making NIF the largest source of biomedical information on the web. NIF’s tools help people find and utilize neuroscience related resources - provides a consistent and easy to implement framework for those who are providing such resources, e.g., data, and those looking to utilize these data and resources. In this demonstration we will provide a tour of NIF’s suite of services, tools, and data: * Search through NIF’s newly re-designed semantically-enhanced discovery portal * Working with NIF’s linked data (e.g. nervous system connectivity) via SPARQL * Services and tools that provide access to the NIF data federation - the largest collection of Neuroscience relevant information on the web * Contributing to the NeuroLex – a community resource for neuroscience terminology built on a semantic media-wiki platform * Curation and normalization of data utilizing NIF’s Google Refine services * NIF’s semantically enhanced data and tools for its maintenance * myNIF and the NIF Digest – personalized services for researchers Figure 1 Acknowledgements NIH Neuroscience Blueprint HHSN271200800035C via NIDA Keywords: Data Federation, big data, linked data, Search Engine, Registry, data integration, Neuroscience, ontology Conference: Neuroinformatics 2013, Stockholm, Sweden, 27 Aug - 29 Aug, 2013. Presentation Type: Demo Topic: Infrastructural and portal services Citation: Grethe JS, Bandrowski A, Banks D, Cachat J, Chen J, Condit C, Gupta A, Imam F, Larson SD, Li Y, Ozyurt IB, Stagg AM, Marenco L, Miller P, Wang R, Shepherd GM, Ascoli G and Martone ME (2013). The Neuroscience Information Framework (NIF): A Unified Semantic Framework and Associated Tools for Discovery, Integration, and Utilization of Biomedical Data and Resources on the Web. Front. Neuroinform. Conference Abstract: Neuroinformatics 2013. doi: 10.3389/conf.fninf.2013.09.00073 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 29 Apr 2013; Published Online: 11 Jul 2013. * Correspondence: Dr. Jeffrey S Grethe, University of California, San Diego, Center for Research in Biological Systems, School of Medicine, La Jolla, CA, 92093-0446, United States, jgrethe@ncmir.ucsd.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Jeffrey S Grethe Anita Bandrowski Davis Banks Jonathan Cachat Jing Chen Christopher Condit Amarnath Gupta Fahim Imam Stephen D Larson Yueling Li Ibrahim B Ozyurt Andrea M Stagg Luis Marenco Perry Miller Rixin Wang Gordon M Shepherd Giorgio Ascoli Maryann E Martone Google Jeffrey S Grethe Anita Bandrowski Davis Banks Jonathan Cachat Jing Chen Christopher Condit Amarnath Gupta Fahim Imam Stephen D Larson Yueling Li Ibrahim B Ozyurt Andrea M Stagg Luis Marenco Perry Miller Rixin Wang Gordon M Shepherd Giorgio Ascoli Maryann E Martone Google Scholar Jeffrey S Grethe Anita Bandrowski Davis Banks Jonathan Cachat Jing Chen Christopher Condit Amarnath Gupta Fahim Imam Stephen D Larson Yueling Li Ibrahim B Ozyurt Andrea M Stagg Luis Marenco Perry Miller Rixin Wang Gordon M Shepherd Giorgio Ascoli Maryann E Martone PubMed Jeffrey S Grethe Anita Bandrowski Davis Banks Jonathan Cachat Jing Chen Christopher Condit Amarnath Gupta Fahim Imam Stephen D Larson Yueling Li Ibrahim B Ozyurt Andrea M Stagg Luis Marenco Perry Miller Rixin Wang Gordon M Shepherd Giorgio Ascoli Maryann E Martone Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. 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Zebrafish (Danio rerio) are rapidly gaining popularity in translational neuroscience and behavioral research. Physiological similarity to mammals, ease of genetic manipulations, sensitivity to pharmacological and genetic factors, robust behavior, low cost, and potential for high-throughput screening contribute to the growing utility of zebrafish models in this field. Understanding zebrafish behavioral phenotypes provides important insights into neural pathways, physiological biomarkers, and genetic underpinnings of normal and pathological brain function. Novel zebrafish paradigms continue to appear with an encouraging pace, thus necessitating a consistent terminology and improved understanding of the behavioral repertoire. What can zebrafish 'do', and how does their altered brain function translate into behavioral actions? To help address these questions, we have developed a detailed catalog of zebrafish behaviors (Zebrafish Behavior Catalog, ZBC) that covers both larval and adult models. Representing a beginning of creating a more comprehensive ethogram of zebrafish behavior, this effort will improve interpretation of published findings, foster cross-species behavioral modeling, and encourage new groups to apply zebrafish neurobehavioral paradigms in their research. In addition, this glossary creates a framework for developing a zebrafish neurobehavioral ontology, ultimately to become part of a unified animal neurobehavioral ontology, which collectively will contribute to better integration of biological data within and across species.

Rodent self-grooming is an important, evolutionarily conserved behavior, highly sensitive to pharmacological and genetic manipulations. Mice with aberrant grooming phenotypes are currently used to model various human disorders. Therefore, it is critical to understand the biology of grooming behavior, and to assess its translational validity to humans. The present in-silico study used publicly available gene expression and behavioral data obtained from several inbred mouse strains in the open-field, light–dark box, elevated plus- and elevated zero-maze tests. As grooming duration differed between strains, our analysis revealed several candidate genes with significant correlations between gene expression in the brain and grooming duration. The Allen Brain Atlas, STRING, GoMiner and Mouse Genome Informatics databases were used to functionally map and analyze these candidate mouse genes against their human orthologs, assessing the strain ranking of their expression and the regional distribution of expression in the mouse brain. This allowed us to identify an interconnected network of candidate genes (which have expression levels that correlate with grooming behavior), display altered patterns of expression in key brain areas related to grooming, and underlie important functions in the brain. Collectively, our results demonstrate the utility of large-scale, high-throughput data-mining and in-silico modeling for linking genomic and behavioral data, as well as their potential to identify novel neural targets for complex neurobehavioral phenotypes, including grooming.

An indole alkaloid, ibogaine is the principal psychoactive component of the iboga plant, used by indigenous peoples in West Africa for centuries. Modulating multiple neurotransmitter systems, the drug is a potent hallucinogen in humans, although its psychotropic effects remain poorly understood. Expanding the range of model species is an important strategy for translational neuroscience research. Here we exposed adult zebrafish (Danio rerio) to 10 and 20 mg/L of ibogaine, testing them in the novel tank, light-dark box, open field, mirror stimulation, social preference and shoaling tests. In the novel tank test, the zebrafish natural diving response (geotaxis) was reversed by ibogaine, inducing initial top swimming followed by bottom dwelling. Ibogaine also attenuated the innate preference for dark environments (scototaxis) in the light-dark box test. While it did not exert overt locomotor or thigmotaxic responses in the open field test, the drug altered spatiotemporal exploration of novel environment, inducing clear preference of some areas over others. Ibogaine also promoted 'mirror' exploration in the mirror stimulation test, disrupted group cohesion in the shoaling test, and evoked strong coloration responses due to melanophore aggregation, but did not alter brain c-fos expression or whole-body cortisol levels. Overall, our results support the complex pharmacological profile of ibogaine and its high sensitivity in zebrafish models, dose-dependently affecting multiple behavioral domains. While future investigations in zebrafish may help elucidate the mechanisms underlying these unique behavioral effects, our study strongly supports the developing utility of aquatic models in hallucinogenic drug research. High sensitivity of three-dimensional phenotyping approaches applied here to behavioral effects of ibogaine in zebrafish provides further evidence of how 3D reconstructions of zebrafish swimming paths may be useful for high-throughput pharmacological screening. (C) 2012 Elsevier B.V. All rights reserved.

The breadth of information resources available to researchers on the Internet continues to expand, particularly in light of recently implemented data-sharing policies required by funding agencies. However, the nature of dense, multifaceted neuroscience data and the design of contemporary search engine systems makes efficient, reliable and relevant discovery of such information a significant challenge. This challenge is specifically pertinent for online databases, whose dynamic content is 'hidden' from search engines. The Neuroscience Information Framework (NIF; http://www.neuinfo.org) was funded by the NIH Blueprint for Neuroscience Research to address the problem of finding and utilizing neuroscience-relevant resources such as software tools, data sets, experimental animals and antibodies across the Internet. From the outset, NIF sought to provide an accounting of available resources, whereas developing technical solutions to finding, accessing and utilizing them. The curators therefore, are tasked with identifying and registering resources, examining data, writing configuration files to index and display data and keeping the contents current. In the initial phases of the project, all aspects of the registration and curation processes were manual. However, as the number of resources grew, manual curation became impractical. This report describes our experiences and successes with developing automated resource discovery and semiautomated type characterization with text-mining scripts that facilitate curation team efforts to discover, integrate and display new content. We also describe the DISCO framework, a suite of automated web services that significantly reduce manual curation efforts to periodically check for resource updates. Lastly, we discuss DOMEO, a semi-automated annotation tool that improves the discovery and curation of resources that are not necessarily website-based (i.e. reagents, software tools). Although the ultimate goal of automation was to reduce the workload of the curators, it has resulted in valuable analytic by-products that address accessibility, use and citation of resources that can now be shared with resource owners and the larger scientific community. DATABASE URL: http://neuinfo.org.

Widely used in biomedical research, zebrafish (Danio rerio) are steadily gaining popularity as a model organism for studying neurobehavioral phenomena.Here, we focus on to the growing spectrum of zebrafish behavioral phenotypes and the 'bigger' biological problems these models help to address.Emphasizing the developing potential of zebrafish as a model organism in biological psychiatry, we discuss several questions related to this field: Do zebrafish have 'emotional'-like behaviors?What are their neural circuits, biomarkers, and ontogenetic origins?And, finally, how can we use this knowledge to build translational bridges to understand human emotions, motivation and personality?Representing a joint effort of several established neurobehavioral laboratories, this article outlines the mounting evidence to support emotionality in zebrafish and other fishes.This conclusion is important to justify the validity of zebrafish 'affective' paradigms and their utility for basic/translational research of normal and pathological behaviors.

1,3,5-Trinitroperhydro-1,3,5-triazine (RDX) is a nitroamine explosive, with common toxic effects including seizures. Here, we explore the behavioral effects of acute RDX exposure in adult zebrafish Danio rerio, a rapidly developing model in neuroscience and neurotoxicology research. Overall, a 30-min exposure to RDX low dose of 0.1mM evoked behavioral activation in zebrafish, while a higher dose of 1mM markedly reduced exploration, increased freezing and evoked seizure-like responses (i.e., bouts of hyperactivity, spasms, and corkscrew swimming). Likewise, whole-body cortisol levels were also significantly elevated in fish exposed to 1mM (but not 0.1mM) RDX. In line with clinical and animal data, our study demonstrates the dose-dependent behavioral activation and pro-convulsant effects of RDX in zebrafish-based models.

The number of available neuroscience resources (databases, tools, materials, and networks) available via the Web continues to expand, particularly in light of newly implemented data sharing policies required by funding agencies and journals. However, the nature of dense, multifaceted neuroscience data and the design of classic search engine systems make efficient, reliable, and relevant discovery of such resources a significant challenge. This challenge is especially pertinent for online databases, whose dynamic content is largely opaque to contemporary search engines. The Neuroscience Information Framework was initiated to address this problem of finding and utilizing neuroscience-relevant resources. Since its first production release in 2008, NIF has been surveying the resource landscape for the neurosciences, identifying relevant resources and working to make them easily discoverable by the neuroscience community. In this chapter, we provide a survey of the resource landscape for neuroscience: what types of resources are available, how many there are, what they contain, and most importantly, ways in which these resources can be utilized by the research community to advance neuroscience research.

Intra-session habituation to novelty reflects spatial working memory (related to exploration and cognition), and is observed in various species, including zebrafish (Danio rerio). With the growing understanding of complex zebrafish behaviors, the extent to which they habituate remains unclear. Here we perform a large-scale characterization of zebrafish novelty-evoked (novel tank and open field) behaviors, to establish their grouping based on intra-session habituation and sensitivity to anxiolytic or anxiogenic manipulations. We also assess multiple behaviors in high- and low-anxiety sub-cohorts of a large heterogeneous zebrafish population, comparing their habituation profiles. Overall, our analyses demonstrate that anxiety responsivity and the ability to habituate show little correlation for multiple zebrafish behaviors, suggesting that they most likely represent distinct behavioral phenomena in novel environments. Using these data, we also present the habituome - a new conceptual approach to study affective and cognitive responses in zebrafish by examining a big set of their habituation phenotypes. Given marked similarity in animal novelty exploration, this approach may also be used to construct habituomes in other model organisms, including rodents and humans. (C) 2012 Elsevier B.V. All rights reserved.

Zebrafish (Danio rerio) are rapidly becoming an important model organism in neuroscience research, representing an excellent species to study complex social phenotypes. Zebrafish actively form shoals, which can be used to quantify their shoaling behaviors, highly sensitive to various experimental manipulations. Recent advances in video-tracking techniques have enabled simultaneous tracking of multiple subjects, previously assessed by manual scoring of animal behavior. Here we examined the effect of group-size in the shoaling paradigm (ranging from 2 to 8 fish), and evaluated the ability of novel video-tracking tools to accurately track an entire shoal, compared to traditional manual analysis of shoaling phenotypes. To further validate our approach, the effects of the psychotropic drugs lysergic acid diethylamide (LSD) and 3,4-methlenedioxymethamphetamine (MDMA), as well as exposure to alarm pheromone, previously shown to affect zebrafish shoaling, were examined. Overall, a significant difference in group size was shown in the 2-fish vs. the 3-, 4-, 5-, 6-, 7- and 8-fish groups. Moreover, both LSD and MDMA treatments reduced shoaling (assessed by increased inter-fish distance) as well as proximity (time spent together) among fish. In contrast, exposure to alarm pheromone yielded an increase in shoaling and in proximity in a time-dependent manner. Importantly, a highly significant correlation for manual vs. automated analyses was revealed across all experiments. Collectively, this study further supports the utility of zebrafish to study social behavior, also demonstrating the capacity of video-tracking technology to assess zebrafish shoaling in a high-throughput and reliable manner.