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http://mialab.mrn.org/data/index.html

An MRI data set that demonstrates the utility of a mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12-71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described, provide a useful baseline for future investigations of brain networks in health and disease.

Proper citation: MIALAB - Resting State Data (RRID:SCR_008914) Copy   

•   Source: SciCrunch Registry

http://lucene1.neuinfo.org/nif_resource/monthly_results/current/

An automatic pipeline based on an algorithm that identifies new resources in publications every month to assist the efficiency of NIF curators. The pipeline is also able to find the last time the resource's webpage was updated and whether the URL is still valid. This can assist the curator in knowing which resources need attention. Additionally, the pipeline identifies publications that reference existing NIF Registry resources as this is also of interest. These mentions are available through the Data Federation version of the NIF Registry, http://neuinfo.org/nif/nifgwt.html?query=nlx_144509 The RDF is based on an algorithm on how related it is to neuroscience. (hits of neuroscience related terms). Each potential resource gets assigned a score (based on how related it is to neuroscience) and the resources are then ranked and a list is generated.

Proper citation: NIF Registry Automated Crawl Data (RRID:SCR_012862) Copy   

•   Source: SciCrunch Registry

https://gseapy.readthedocs.io/en/latest/

Software Python package for performing gene set enrichment analysis. Used for characterizing gene expression changes by analysis of large single-cell datasets.

Proper citation: GSEApy (RRID:SCR_025803) Copy   

•   Source: SciCrunch Registry

https://painseq.shinyapps.io/harmonized_painseq_v1/

Harmonized cell atlases using sc/snRNA-seq data obtained from dorsal root ganglia and trigeminal ganglio mammalian datasets.

Proper citation: Harmonized DRG and TG Reference Atlas (RRID:SCR_025720) Copy   

•   Source: SciCrunch Registry

https://www.ohsu.edu/custom/library/digital-collections/projectionmap

Data set of thalamo-centric mesoscopic projection maps to the cortex and striatum. The maps are established through two-color, viral (rAAV)-based tracing images and high throughout imaging.

Proper citation: Mouse Thalamic Projectome Dataset (RRID:SCR_015702) Copy   

•   Source: SciCrunch Registry

https://abcdstudy.org

Long-term study of brain development and child health in the United States. The study tracks subjects' biological and behavioral development through adolescence into young adulthood to determine how childhood experiences (such as sports, videogames, social media, unhealthy sleep patterns, and smoking) interact with each other and with a child’s changing biology to affect brain development and social, behavioral, academic, health, and other outcomes.

Proper citation: ABCD Study (RRID:SCR_015769) Copy   

•   Source: SciCrunch Registry

https://github.com/smorabit/hdWGCNA

Software R package for performing weighted gene co-expression network analysis in high dimensional transcriptomics data such as single-cell RNA-seq or spatial transcriptomics.

Proper citation: hdWGCNA (RRID:SCR_027496) Copy   

•   Source: SciCrunch Registry

https://doi.org/10.17605/OSF.IO/WDR78

Open source resource of manually curated and expert reviewed infant brain segmentations hosted on OpenNeuro.org. and OSF.io. Anatomical MRI data was segmented from 71 infant imaging visits across 51 participants, using both T1w and T2w images per visit. Images showed dramatic differences in myelination and intensities across 1–9 months, emphasizing the need for densely sampled gold-standard segmentations across early life. This dataset provides a benchmark for evaluating and improving pipelines dependent upon segmentations in the youngest populations. As such, this dataset provides a vitally needed foundation for early-life large-scale studies such as HBCD.

Proper citation: Baby Open Brains (RRID:SCR_027836) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/scicrunch/about/sources/nlx_144509-1

Interactive portal for finding and submitting biomedical resources. Resources within SciCrunch have assigned RRIDs which are used to cite resources in scientific manuscripts. SciCrunch Registry, formerly NIF Registry, provides resources catalog. Allows to add new resources. Allows edit existing resources after registration. Curators are tasked with identifying and registering resources, examining data, writing configuration files to index and display data and keeping contents current.

Proper citation: SciCrunch Registry (RRID:SCR_005400) Copy   

•   Source: SciCrunch Registry

http://biositemaps.ncbcs.org/rds/search.html

Resource Discovery System is a web-accessible and searchable inventory of biomedical research resources. Powered by the Resource Discovery System (RDS) that includes a standards-based informatics infrastructure * Biositemaps Information Model * Biomedical Resource Ontology Extensions * Web Services distributed web-accessible inventory framework * Biositemap Resource Editor * Resource Discovery System Source code and project documentation to be made available on an open-source basis. Contributing institutions: University of Pittsburgh, University of Michigan, Stanford University, Oregon Health & Science University, University of Texas Houston. Duke University, Emory University, University of California Davis, University of California San Diego, National Institutes of Health, Inventory Resources Working Group Members

Proper citation: Resource Discovery System (RRID:SCR_005554) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/scicrunch/data/source/nlx_154697-7/search?q=*

Virtual database currently indexing interaction between genes and diseases from Online Mendelian Inheritance in Man (OMIM) and Comparative Toxicogenomics Database (CTD).

Proper citation: Integrated Gene-Disease Interaction (RRID:SCR_006173) Copy   

•   Source: SciCrunch Registry

http://www.cpc.unc.edu/projects/addhealth

Longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. Public data on about 21,000 people first surveyed in 1994 are available on the first phases of the study, as well as study design specifications. It also includes some parent and biomarker data. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The restricted-use contract includes four hours of free consultation with appropriate staff; after that, there''s a fee for help. Researchers can also share information through a listserv devoted to the database.

Proper citation: Add Health (National Longitudinal Study of Adolescent Health) (RRID:SCR_007434) Copy   

•   Source: SciCrunch Registry

https://confluence.crbs.ucsd.edu/display/NIF/DRG

Gene expression data from published journal articles that test hypotheses relevant to neuroscience of addiction and addictive behavior. Data types include effects of particular drug, strain, or knock out on particular gene, in particular anatomical region. Focuses on gene expression data and exposes data from investigations using DNA microarrays, polymerase chain reaction, immunohistochemistry and in-situ hybridizations. Data are available for query through NIF interface.Data submissions are welcome.

Proper citation: Drug Related Gene Database (RRID:SCR_003330) Copy   

•   Source: SciCrunch Registry

http://www.exocarta.org/

Manually curated database of exosomal proteins, RNA and lipids. Web based compendium of exosomal cargo. Database catalogs information from both published and unpublished exosomal studies. Mode of exosomal purification and characterization, biophysical and molecular properties are listed.

Proper citation: ExoCarta (RRID:SCR_021960) Copy   

•   Source: SciCrunch Registry

https://github.com/ABCD-STUDY/delay-discounting

Software that performs a delay-discounting task measuring impulsivity. Used in ABCD study.

Proper citation: delay-discounting (RRID:SCR_016031) Copy   

•   Source: SciCrunch Registry

https://expfactory.github.io

Software that generates container-based behavioral experiments for reproducible science. It offers a library of experiments, games, and surveys, support for multiple kinds of databases, and robust documentation for the provided tools.

Proper citation: The Experiment Factory (RRID:SCR_016107) Copy   

•   Source: SciCrunch Registry

http://www.ctalearning.com/

A searchable, keyword-indexed bibliography on conditioned taste aversion learning, the avoidance of fluids and foods previously associated with the aversive effects of a variety of drugs. The database includes articles as early as 1951, and papers just published given that the database is ongoing and constantly updated. In the mid 1950''s, John Garcia and his colleagues at the Radiological Defense Laboratory at Hunters Point in San Francisco assessed the effects of ionizing radiation on a myriad of behaviors in the laboratory rat. One of their behavioral findings was that radiated rats avoided consumption of solutions that had been present during radiation, presumably due to the association of the taste of the solution with the aversive effects of the radiation. These results were published in Science and introduced to the literature the phenomenon of conditioned taste aversion learning (or the Garcia Effect). Subsequently, Garcia and his colleagues demonstrated that such learning appeared unique in a number of respects, including the fact that these aversions were acquired often in a single conditioning trial, selectively to gustatory stimuli and even when long delays were imposed between access to the solution and administration of the aversive agent. Together, these unique characteristics appeared to violate the basic tenets of traditional learning theory and along with a number of other behavioral phenomena (e.g., bird song learning, species-specific defense reactions, tonic immobility and schedule-induced polydipsia) introduced the concept of biological constraints on learning that forced a reconceptualization of the role evolution played in the acquisition of behavior (Garcia and Ervin, 1968; Revusky and Garcia, 1970; Rozin and Kalat, 1971). Although the initial investigations into conditioned taste aversion learning focused on these biological and evolutionary issues and their relation to learning, research in this area soon assessed the basic generality of the phenomenon, specifically, under what conditions such learning did or did not occur. With such research, a wide variety of gustatory stimuli were reported as effective conditioned stimuli and an extensive list of drugs with diverse consequences were reported as effective aversion-inducing agents. Aversions were established in a range of strains and species and under many experimental conditions. Research in this area continues to extend the conditions under which such learning occurs and to demonstrate its biological, neurochemical and anatomical substrates. Although the conditions under which aversion learning are reported to occur appear to generalize from the specific conditions under which they were originally reported, a number of factors including sex, age, training and testing procedures, deprivation level and drug history, all affect the rate of its acquisition and its terminal strength (Riley, 1998). In addition to these experimental demonstrations and assessments of generality, research on conditioned taste aversions has expanded to include investigations into its research and clinical applications (Braveman and Bronstein, 1985). In so doing, taste aversion learning has been applied to the characterization and classification of drug toxicity, the demonstration of the stimulus properties of abused drugs, the management of wildlife predation, the assessment of the etiology and treatment of cancer anorexia, the study of the biochemistry and molecular biology of learning, the etiology and control of alcohol use and abuse, the receptor characterization of the motivational effects of drugs, the occurrence of drug interactions, the characterization of drug withdrawal, the determination of taste psychophysics, the treatment of autoimmune diseases and the evaluation of the role of malaise in drug-induced satiety and drug-induced behavioral deficits. The speed with which aversions are acquired and the relative robustness of this preparation have made conditioned taste aversion learning a widely used, highly replicable and sensitive tool. In 1976, we published the first of three bibliographies on conditioned taste aversion learning. In this initial publication (see Riley and Baril, 1976), we listed and annotated 403 papers in this field. Subsequent lists published in 1977 (Riley and Clarke, 1977) and 1985 (Riley and Tuck, 1985) listed 632 and 1373 papers, respectively. Since that time, we have maintained a bibliography on taste aversion learning utilizing a variety of journal and on-line searches as well as benefiting from the generous contribution of preprints, reprints and pdf files from many colleagues. To date, the number of papers on conditioned taste aversion learning is approaching 3000. The present database lists these papers and provides a mechanism for searching the articles according to a number of search functions. Specifically, it was constructed to provide the reader access to these articles via a variety of search terms, including Author(s), Key Words, Date, Article Title and Journal. One can search for single or multiple items within any specific category. Further, one can search a single or combination of categories. The database is constantly being updated, and any feedback and suggestions are welcome and can be sent to CTALearning (at) american.edu.

Proper citation: Conditioned Taste Aversion: An Annotated Bibliography (RRID:SCR_005953) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/

Software repository for comparing structural (MRI) and functional neuroimaging (fMRI, PET, EEG, MEG) software tools and resources. NITRC collects and points to standardized information about structural or functional neuroimaging tool or resource.

Proper citation: NeuroImaging Tools and Resources Collaboratory (NITRC) (RRID:SCR_003430) Copy   

•   Source: SciCrunch Registry

http://brainarray.mbni.med.umich.edu/Brainarray/Database/ProbeMatchDB/ncbi_probmatch_para_step1.asp

Matches a list of microarray probes across different microrarray platforms (GeneChip, EST from different vendors, Operon Oligos) and species (human, mouse and rat), based on NCBI UniGene and HomoloGene. The capability to match protein sequence IDs has just been added to facilitate proteomic studies. The ProbeMatchDB is mainly used for the design of verification experiments or comparing the microarray results from different platforms. It can be used for finding equivalent EST clones in the Research Genetics sequence verified clone set based on results from Affymetirx GeneChips. It will also help to identify probes representing orthologous genes across human, mouse and rat on different microarray platforms.

Proper citation: ProbeMatchDB 2.0 (RRID:SCR_003433) Copy   

•   Source: SciCrunch Registry

http://www.pediatricmri.nih.gov/

Data sets of clinical / behavioral and image data are available for download by qualified researchers from a seven year, multi-site, longitudinal study using magnetic resonance technologies to study brain maturation in healthy, typically-developing infants, children, and adolescents and to correlate brain development with cognitive and behavioral development. The information obtained in this study is expected to provide essential data for understanding the course of normal brain development as a basis for understanding atypical brain development associated with a variety of developmental, neurological, and neuropsychiatric disorders affecting children and adults. This study enrolled over 500 children, ranging from infancy to young adulthood. The goal was to study each participant at least three times over the course of the project at one of six Pediatric Centers across the United States. Brain MR and clinical/behavioral data have been compiled and analyzed at a Data Coordinating Center and Clinical Coordinating Center. Additionally, MR spectroscopy and DTI data are being analyzed. The study was organized around two objectives corresponding to two age ranges at the time of enrollment, each with its own protocols. * Objective 1 enrolled children ages 4 years, 6 months through 18 years (total N = 433). This sample was recruited across the six Pediatric Study Centers using community based sampling to reflect the demographics of the United States in terms of income, race, and ethnicity. The subjects were studied with both imaging and clinical/behavioral measures at two year intervals for three time points. * Objective 2 enrolled newborns, infants, toddlers, and preschoolers from birth through 4 years, 5 months, who were studied three or more times at two Pediatric Study Centers at intervals ranging from three months for the youngest subjects to one year as the children approach the Objective 1 age range. Both imaging and clinical/behavioral measures were collected at each time point. Participant recruitment used community based sampling that included hospital venues (e.g., maternity wards and nurseries, satellite physician offices, and well-child clinics), community organizations (e.g., day-care centers, schools, and churches), and siblings of children participating in other research at the Pediatric Study Centers. At timepoint 1, of those enrolled, 114 children had T1 scans that passed quality control checks. Staged data release plan: The first data release included structural MR images and clinical/behavioral data from the first assessments, Visit 1, for Objective 1. A second data release included structural MRI and clinical/behavioral data from the second visit for Objective 1. A third data release included structural MRI data for both Objective 1 and 2 and all time points, as well as preliminary spectroscopy data. A fourth data release added cortical thickness, gyrification and cortical surface data. Yet to be released are longitudinally registered anatomic MRI data and diffusion tensor data. A collaborative effort among the participating centers and NIH resulted in age-appropriate MR protocols and clinical/behavioral batteries of instruments. A summary of this protocol is available as a Protocol release document. Details of the project, such as study design, rationale, recruitment, instrument battery, MRI acquisition details, and quality controls can be found in the study protocol. Also available are the MRI procedure manual and Clinical/Behavioral procedure manuals for Objective 1 and Objective 2.

Proper citation: NIH MRI Study of Normal Brain Development (RRID:SCR_003394) Copy   

•   Source: SciCrunch Registry