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https://cloudreg.neurodata.io/

Software automated, terascale, cloud based image analysis pipeline for preprocessing and cross modal, nonlinear registration between volumetric datasets with artifacts. Automatic terabyte scale cross modal brain volume registration.

Proper citation: CloudReg (RRID:SCR_022795) Copy   

•   Source: SciCrunch Registry

http://www.ccnmd.pitt.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Conte Center for the Neuroscience of Mental Disorders (CCNMD) at the University of Pittsburgh offers a highly interactive scientific environment for the study of the neurobiology of schizophrenia. Integrates the laboratory and clinical research activities of investigators from the University of Pittsburgh Schools of Medicine and Arts and Sciences and the adjacent Carnegie Mellon University.

Proper citation: University of Pittsburgh Conte Center for the Neuroscience of Mental Disorders (RRID:SCR_000014) Copy   

•   Source: SciCrunch Registry

http://mindboggle.info/data.html

Complete set of free, publicly accessible, downloadable atlases, templates, and individual manually labeled brain image data, the largest collection of publicly available, manually labeled human brains in the world! http://journal.frontiersin.org/article/10.3389/fnins.2012.00171/full

Proper citation: Mindboggle-101 atlases (RRID:SCR_002439) Copy   

•   Source: SciCrunch Registry

http://www.epmba.org/

The Electronic Prenatal Mouse Brain Atlas, EPMBA, at present consists of two sets of annotated images of coronal sections from Gestational Day (GD) 12 heads and GD 16 brains of C57BL/6J mice. Ten micron thick sections were stained with hematoxylin and eosin. Images were prepared at various resolutions for annotations and for high resolution presentation. A subset of sections were annotated and linked to anatomical terms. Additionally, horizontal sections of a GD 12 head were aligned and re-assembled into a 3D volume for digital sectioning in arbitrarily oblique planes. These images were captured using a Nikon E800 stereomicroscope with a 10X objective. The resolution is 1.35 pixels/micrometer. The PC program used to grab the images, Microbrightfield's Neurolucida (version 6), stitched together a mosaic of between 10 and 50 high-res images for each tissue slice, while the user focused the scope for each mosaic tile. Since the nature of optic lenses is to focus on one central point, it was difficult to obtain a uniformly-focused field of vision; as such, small areas of these images are blurred. Images were then transferred to a Macintosh and processed in Adobe Photoshop (version 7). Color levels were adjusted for maximum clarity of the tissue, and areas surrounding the tissue were cleared of artifacts. Each image is approximately 3350 pixels wide by 2650 pixels high. A scale bar with a length of 1350 pixels/mm is visible in the lower right-hand corner of each image. The annotations have been completed for the Atlas of Developing Mouse Brain Gestational (Embryonic) Day 12 (7/5/07) as well as the Atlas of Developing Mouse Brain Embryonic Day 16 (4/26/07). The 3D EPMBA data set has been mounted on a NeuroTerrain Atlas Server (NtAS). (6/27/07).

Proper citation: EPMBA.ORG: Electronic Prenatal Mouse Brain Atlas (RRID:SCR_001882) Copy   

•   Source: SciCrunch Registry

http://www.med.unc.edu/bric/ideagroup/free-softwares/unc-infant-0-1-2-atlases

3 atlases dedicated for neonates, 1-year-olds, and 2-year-olds. Each atlas comprises a set of 3D images made up of the intensity model, tissue probability maps, and anatomical parcellation map. These atlases are constructed with the help of state-of-the-art infant MR segmentation and groupwise registration methods, on a set of longitudinal images acquired from 95 normal infants (56 males and 39 females) at neonate, 1-year-old, and 2-year-old.

Proper citation: UNC Infant 0-1-2 Atlases (RRID:SCR_002569) Copy   

•   Source: SciCrunch Registry

http://www.mouseconnectome.org/

Three-dimensional digital connectome atlas of the C57Black/6J mouse brain and catalog of neural tracer injection cases, which will eventually cover the entire brain. Serial sections of each case are available to view at 10x magnification in the interactive iConnectome viewer. The Image Gallery provides a glimpse into some of the highlights of their data set. Representative images of multi-fluorescent tracer labeling can be viewed, while more in depth examination of these and all other cases can be performed in the iConnectome viewer. Phase 1 of this project involves generating a physical map of the basic global wiring diagram by applying proven, state of the art experimental circuit tracing methods systematically, uniformly, and comprehensively to the structural organization of all major neuronal pathways in the mouse brain. Connectivity imaging data for the whole mouse brain at cellular resolution will be presented within a standard 3D anatomic frame available through the website and accompanied by a comprehensive searchable online database. A Phase 2 goal for the future will allow users to view, search, and generate driving direction-like roadmaps of neuronal pathways linking any and all structures in the nervous system. This could be looked on as a pilot project for more ambitious projects in species with larger brains, such as human, and for providing a reliable framework for more detailed local circuitry mapping projects in the mouse.

Proper citation: Mouse Connectome Project (RRID:SCR_004096) Copy   

•   Source: SciCrunch Registry

https://cells.ucsc.edu/

Web based tool to visualize gene expression and metadata annotation distribution throughout single cell dataset or multiple datasets. Interactive viewer for single cell expression. You can click on and hover over cells to get meta information, search for genes to color on and click clusters to show cluster specific marker genes.

Proper citation: UCSC Cell Browser (RRID:SCR_023293) Copy   

•   Source: SciCrunch Registry

http://humanconnectome.org/connectome/connectomeDB.html

Data management platform that houses all data generated by the Human Connectome Project - image data, clinical evaluations, behavioral data and more. ConnectomeDB stores raw image data, as well as results of analysis and processing pipelines. Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. ConnectomeDB is designed to be a data-mining tool, that allows users to generate and test hypotheses based on groups of subjects. Using the ConnectomeDB interface, users can easily search, browse and filter large amounts of subject data, and download necessary files for many kinds of analysis. ConnectomeDB is designed to work seamlessly with Connectome Workbench, an interactive, multidimensional visualization platform designed specifically for handling connectivity data. De-identified data within ConnectomeDB is publicly accessible. Access to additional data may be available to qualified research investigators. ConnectomeDB is being hosted on a BlueArc storage platform housed at Washington University through the year 2020. This data platform is based on XNAT, an open-source image informatics software toolkit developed by the NRG at Washington University. ConnectomeDB itself is fully open source.

Proper citation: ConnectomeDB (RRID:SCR_004830) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/funding/clinical-trials-for-researchers/practical/step-bd/index.shtml

A long-term outpatient study designed to find out which treatments, or combinations of treatments, are most effective for treating episodes of depression and mania and for preventing recurrent episodes in people with bipolar disorder. This study has been completed. (2005) STEP-BD is evaluating all the best-practice treatment options used for bipolar disorder: mood-stabilizing medications, antidepressants, atypical antipsychotics, and psychosocial interventions - or talk therapies - including Cognitive Behavioral Therapy, Family-focused Therapy, Interpersonal and Social Rhythm Therapy, and Collaborative Care (psychoeducation). There are two kinds of treatment pathways in STEP-BD, and participants may have the opportunity to take part in both. The medications and psychosocial interventions provided in these pathways are considered among the best choices of treatment for bipolar disorder in everyday clinical practice. In the Best Practice Pathway, participants are followed by a STEP-BD certified doctor and all treatment choices are individualized. Everyone enrolled in STEP-BD may participate in this pathway. Participants and their doctors work together to decide on the best treatment plans and to change these plans if needed. Also, anyone who wishes to stay on his or her current treatment upon entering STEP-BD may do so in this pathway. Adolescents and adults age 15 years and older may participate in the Best Practice Pathway. For adults age 18 and older, another way to participate is in the STEP-BD Randomized Care Pathways. Depending on their symptoms, participants may be offered treatment in one or more of these pathways during the course of the study. The participants remain on mood-stabilizing medication. However, because doctors are uncertain which of several treatment strategies work best for bipolar disorder, another medication and/or talk therapy may be added. Each Randomized Care Pathway involves a different set of these additional treatments. Unlike in the Best Practice Pathway, the participants in the Randomized Care Pathways are randomly assigned to treatments. Also, in some cases, neither the participant nor the doctor will be told which of the different medications is being added. This is called a double-blind study and is done so that the medication effects can be evaluated objectively, without any unintended bias that may come from knowing what has been assigned. Participants will not be assigned medications that they have had bad reactions to in the past, that they are strongly opposed to, or that the doctor feels are unsuitable for them. The medication(s) participants may be randomly assigned to in the Randomized Care Pathways are free of charge. There are other treatment options for participants if they do not respond well to the treatment assigned to them. Also, participants may return to the Best Practice Pathway at any time. About 1,500 individuals will be enrolled in at least one Randomized Care Pathway during their period of participation in STEP-BD. It is important to note that STEP-BD provides continuity of care. For example, if a participant starts out in the Best Practice Pathway and later chooses to enter one of the Randomized Care Pathways, he or she continues with the same STEP-BD doctor and treatment team. Then, after completing the Randomized Care Pathway, the participant may return to the Best Practice Pathway for ongoing, individually-tailored treatment. Follow the link to view study info at Clinicaltrials.gov, http://www.clinicaltrials.gov/ct/show/NCT00012558?order=1

Proper citation: Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) (RRID:SCR_008844) Copy   

•   Source: SciCrunch Registry

http://www.armystarrs.org/

Study of mental health risk and resilience factors ever conducted among military personnel. The purpose of Army STARRS is to identify as quickly as possible factors that protect or pose risks to Soldiers'' emotional well-being and overall mental health so that the Army may apply the knowledge to its ongoing health promotion, risk reduction, and suicide prevention efforts. Army STARRS investigators will use four separate study components the Historical Data Study, New Soldier Study, All Army Study, and Soldier Health Outcomes Study to identify factors that help protect a Soldier''s mental health and factors that put a Soldier''s mental health at risk. Army STARRS is a five-year study that will run through 2014. Findings will be reported as they become available, so that the Army may apply them to its ongoing health promotion, risk reduction, and suicide prevention efforts. Given its length and scope, Army STARRS will generate a vast amount of information and will allow investigators to focus on periods in a military career that are known to be high risk for psychological problems. The information gathered from volunteer participants throughout the study will help researchers identify not only potentially relevant risk factors, but potential protective factors as well. Because promoting mental health and reducing suicide risk are important for all Americans, the findings from Army STARRS will benefit not only servicemembers but the nation as a whole. NIMH has assembled a group of renowned experts to carry out this research including teams from the Uniformed Services University of the Health Sciences (USUHS), the University of California, San Diego, University of Michigan, Harvard Medical School, and NIMH. Additional Army and NIMH program staff will contribute to the oversight and implementation of the study. This research team brings together international leaders in military health, health and behavior surveys, epidemiology, suicide, and genetic and neurobiological factors involved in psychological health.

Proper citation: Army STARRS (RRID:SCR_006708) Copy   

•   Source: SciCrunch Registry

http://research.mssm.edu/cnic/

Center to advance research and training in mathematical, computational and modern imaging approaches to understanding the brain and its functions. Software tools and associated reconstruction data produced in the center are available. Researchers study the relationships between neural function and structure at levels ranging from the molecular and cellular, through network organization of the brain. This involves the development of new computational and analytic tools for imaging and visualization of 3-D neural morphology, from the gross topologic characteristics of the dendritic arbor to the fine structure of spines and their synapses. Numerical simulations of neural mechanisms based on these structural data are compared with in-vivo and in-vitro electrophysiological recordings. The group also develops new theoretical and analytic approaches to exploring the function of neural models of working memory. The goal of this analytic work is to combine biophysically realistic models and simulations with reduced mathematical models that capture essential dynamical behaviors while reproducing the functionally important features of experimental data. Research areas include: Imaging Studies, Volume Integration, Visualization Techniques, Medial Axis Extraction, Spine Detection and Classification, Applications of Rayburst, Analysis of Spatially Complex Structures, Computational Modeling, Mathematical and Analytic Studies

Proper citation: Computational Neurobiology and Imaging Center (RRID:SCR_013317) Copy   

•   Source: SciCrunch Registry

http://interactome.baderlab.org/

Project portal for the Human Reference Protein Interactome Project, which aims generate a first reference map of the human protein-protein interactome network by identifying binary protein-protein interactions (PPIs). It achieves this by systematically interrogating all pairwise combinations of predicted human protein-coding genes using proteome-scale technologies.

Proper citation: Human Reference Protein Interactome Project (RRID:SCR_015670) Copy   

•   Source: SciCrunch Registry

https://github.com/davidaknowles/leafcutter/

Software tool for identifying and quantifying RNA splicing variation. Used to study sample and population variation in intron splicing. Identifies variable intron splicing events from short read RNA-seq data and finds alternative splicing events of high complexity. Used for detecting differential splicing between sample groups, and for mapping splicing quantitative trait loci (sQTLs).

Proper citation: LeafCutter (RRID:SCR_017639) Copy   

•   Source: SciCrunch Registry

https://github.com/zburkett/VoICE

Software that groups vocal elements of birdsong by creating a high dimensionality dataset through scoring spectral similarity between vocalizations.

Proper citation: Vocal Inventory Clustering Engine (VoICE) (RRID:SCR_016004) Copy   

•   Source: SciCrunch Registry

https://github.com/broadinstitute/Drop-seq

Software Java tools for analyzing Drop-seq data. Used to analyze gene expression from thousands of individual cells simultaneously. Analyzes mRNA transcripts while remembering origin cell transcript.

Proper citation: Drop-seq tools (RRID:SCR_018142) Copy   

•   Source: SciCrunch Registry

http://krasnow1.gmu.edu/CENlab/software.html

Stochastic reaction-diffusion simulator in Java which is used for simulating neuronal signaling pathways.

Proper citation: NeuroRD (RRID:SCR_014769) Copy   

•   Source: SciCrunch Registry

http://openneuro.org

Open platform for analyzing and sharing neuroimaging data from human brain imaging research studies. Brain Imaging Data Structure ( BIDS) compliant database. Formerly known as OpenfMRI. Data archives to hold magnetic resonance imaging data. Platform for sharing MRI, MEG, EEG, iEEG, and ECoG data.

Proper citation: OpenNeuro (RRID:SCR_005031) Copy   

•   Source: SciCrunch Registry

http://headit.ucsd.edu

Platform for sharing, download, and re-analysis or meta-analysis of sophisticated, fully annotated, human electrophysiological data sets. It uses EEG Study Schema (ESS) files to provide task, data collection, and subject metadata, including Hierarchical Event Descriptor (HED) tag descriptions of all identified experimental events. Visospatial task data also available from, http://sccn.ucsd.edu/eeglab/data/headit.html: A 238-channel, single-subject EEG data set recorded at the Swartz Center, UCSD, by Arnaud Delorme, Julie Onton, and Scott Makeig is al.

Proper citation: HeadIT (RRID:SCR_005657) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/about/advisory-boards-and-groups/namhc/reports/mri-research-safety-ethics.pdf

NIMH recognizes the need to consider safety and ethical issues related to both the administration of MR (magnetic resonance) facilities and the use of these facilities for research. This document summarizes the points to consider discussed by the National Advisory Mental Health Council (NAMHC) Workgroup. Examples of safe and ethical practices are discussed in relation to several issues. These examples are intended to be illustrative and should not be interpreted as an exhaustive or exclusive list. This document was presented to the full NIMH Council on September 15, 2006 and approved unanimously. By making the points to consider document available publicly, NIMH intends to provide a resource for researchers and institutions that use MRI in research. The agenda was organized into six topics, which provide the organization for the points to consider that follow: A. MRI screening B. Training, operating, and emergency procedures C. Physical facilities D. Scanning/participant health variables E. Context- Specific Considerations: University vs. medical settings F. Additional data needs and updating The NIMH believes that investigators, institutions and facilities can use this document as a resource for the development, administration, evaluation, and use of MRI research facilities.

Proper citation: MRI Research Safety and Ethics (RRID:SCR_005642) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/educational-resources/brain-basics/brain-basics.shtml

Brain Basics provides information on how the brain works, how mental illnesses are disorders of the brain, and ongoing research that helps us better understand and treat disorders. Mental disorders are common. You may have a friend, colleague, or relative with a mental disorder, or perhaps you have experienced one yourself at some point. Such disorders include depression, anxiety disorders, bipolar disorder, attention deficit hyperactivity disorder (ADHD), and many others. Some people who develop a mental illness may recover completely; others may have repeated episodes of illness with relatively stable periods in between. Still others live with symptoms of mental illness every day. They can be moderate, or serious and cause severe disability. Through research, we know that mental disorders are brain disorders. Evidence shows that they can be related to changes in the anatomy, physiology, and chemistry of the nervous system. When the brain cannot effectively coordinate the billions of cells in the body, the results can affect many aspects of life. Scientists are continually learning more about how the brain grows and works in healthy people, and how normal brain development and function can go awry, leading to mental illnesses. Brain Basics will introduce you to some of this science, such as: * How the brain develops * How genes and the environment affect the brain * The basic structure of the brain * How different parts of the brain communicate and work with each other * How changes in the brain can lead to mental disorders, such as depression.

Proper citation: Brain Basics (RRID:SCR_005606) Copy   

•   Source: SciCrunch Registry