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http://hendrix.ei.dtu.dk/software/mriwarp/mriwarp.html

Warping tool for intersubject registration of brain images consisting of C functions for Unix systems plus Matlab visualization utility functions. Apart from warping there are also (command line) functions for ANALYZE header information, mirroring, translation, subsampling. The package cannot only be used as a preprocessing step in function neuroimaging but also as a step in deformation-based morphometry.

Proper citation: MRIWarp (RRID:SCR_002072) Copy   

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http://irc.cchmc.org/software/pedbrain.php

Brain imaging data collected from a large population of normal, healthy children that have been used to construct pediatric brain templates, which can be used within statistical parametric mapping for spatial normalization, tissue segmentation and visualization of imaging study results. The data has been processed and compiled in various ways to accommodate a wide range of possible research approaches. The templates are made available free of charge to all interested parties for research purposes only. When processing imaging data from children, it is important to take into account the fact that the pediatric brain differs significantly from the adult brain. Therefore, optimized processing requires appropriate reference data be used because adult reference data will introduce a systematic bias into the results. We have shown that, in the in the case of spatial normalization, the amount of non-linear deformation is dramatically less when a pediatric template is used (left, see also HBM 2002; 17:48-60). We could also show that tissue composition is substantially different between adults and children, and more so the younger the children are (right, see also MRM 2003; 50:749-757). We thus believe that the use of pediatric reference data might be more appropriate.

Proper citation: CCHMC Pediatric Brain Templates (RRID:SCR_003276) Copy   

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http://www.macbrain.org/

Portal on how the experiences of early childhood are incorporated into the structures of the developing brain, and how, in turn, those changes in the structures of the brain influence behavior. The network explores how knowledge of brain development can guide us in understanding of behavioral development and vice versa. It focuses specifically on sensitive periods and neural plasticity, the reciprocal phenomena whereby (a) the brain is negatively affected if certain experiences fail to occur within a certain time period, and (b) the brain is altered by experience at virtually any point in the life span. Here we consider not only how the structure of experience is incorporated into the structure of the brain, but also how this knowledge can influence the decisions we make about intervening in the lives of children. Research and other projects conducted by the Network fall into four broad categories: * Effects of early experience on brain development * New methods for studying brain-behavior relations * Comparative studies of early brain-behavioral development * Impact on public policy: Educating educators and the media RESOURCES NimStim Face Stimulus Set The Research Network on Early Experience and Brain Development has developed a battery of 646 facial expression stimuli for use in its own and other studies of face and emotion recognition. Images include the following expressions, displayed by a variety of models of various genders and races: fearful, happy, sad, angry, surprised, calm, neutral, disgusted. They are making these stimuli available to the public free of charge with registration and acceptance of the terms and conditions to use the stimulus set.

Proper citation: Research Network in Early Experience and Brain Development (RRID:SCR_003271) Copy   

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http://genome.ucsc.edu/cgi-bin/hgVisiGene

Virtual microscope for viewing in situ images that show where a gene is used in an organism, sometimes down to cellular resolution. The user can examine cell-by-cell as well as tissue-by-tissue expression patterns. Users can retrieve images that meet specific search criteria, then interactively zoom and scroll across the collection. Image set contributions are welcome. The following image collections are currently available for browsing: * High-quality high-resolution images of eight-week-old male mouse sagittal brain slices with reverse-complemented mRNA hybridization probes from the Allen Brain Atlas, courtesy of the Allen Institute for Brain Science * Mouse in situ images from the Jackson Lab Gene Expression Database (GXD) at MGI * Transcription factors in mouse embryos from the Mahoney Center for Neuro-Oncology * Mouse head and brain in situ images from NCBI''''s Gene Expression Nervous System Atlas (GENSAT) database * Xenopus laevis in situ images from the National Institute for Basic Biology (NIBB) XDB project

Proper citation: VisiGene Image Browser (RRID:SCR_003341) Copy   

•   Source: SciCrunch Registry

http://www.ispa.pt/ui/uie/ibbg/TilapiaBrainAtlas/index.html

Digital three-dimensional MRI atlas of the Mozambique tilapia brain, supported by Nissl staining. Images were viewed and analyzed in all orientations (transverse, sagittal, and horizontal) and manually labelled to reveal structures in the olfactory bulb, telencephalon, diencephalon, optic tectum, and cerebellum. The MRI atlas data (16-bit int) and delineation data (8-bit int) are provided in Raw data (file_name.raw), Amira format (file_name.am) and in Analyze format (file_name.img and file_name.hdr).

Proper citation: Brain Atlas of the Mozambique Tilapia Oreochromis mossambicus (RRID:SCR_003501) Copy   

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http://www.humanconnectomeproject.org/

A multi-center project comprising two distinct consortia (Mass. Gen. Hosp. and USC; and Wash. U. and the U. of Minn.) seeking to map white matter fiber pathways in the human brain using leading edge neuroimaging methods, genomics, architectonics, mathematical approaches, informatics, and interactive visualization. The mapping of the complete structural and functional neural connections in vivo within and across individuals provides unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve conclusions about the living human brain. The HCP is being developed to employ advanced neuroimaging methods, and to construct an extensive informatics infrastructure to link these data and connectivity models to detailed phenomic and genomic data, building upon existing multidisciplinary and collaborative efforts currently underway. Working with other HCP partners based at Washington University in St. Louis they will provide rich data, essential imaging protocols, and sophisticated connectivity analysis tools for the neuroscience community. This project is working to achieve the following: 1) develop sophisticated tools to process high-angular diffusion (HARDI) and diffusion spectrum imaging (DSI) from normal individuals to provide the foundation for the detailed mapping of the human connectome; 2) optimize advanced high-field imaging technologies and neurocognitive tests to map the human connectome; 3) collect connectomic, behavioral, and genotype data using optimized methods in a representative sample of normal subjects; 4) design and deploy a robust, web-based informatics infrastructure, 5) develop and disseminate data acquisition and analysis, educational, and training outreach materials.

Proper citation: MGH-USC Human Connectome Project (RRID:SCR_003490) Copy   

•   Source: SciCrunch Registry

http://www.brainfacts.org/

A web portal that aggregates information and educational materials about the brain and brain diseases. Resources such as videos, key brain concepts, and hands-on activities may be used and shared with the public.

Proper citation: brainfacts.org (RRID:SCR_003514) 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

http://pons.incf.org/

Program consisting of three Task Forces and one Working Group to promote data exchange and integration in the neurosciences by developing terminology standards and formal ontologies for neural structures. Closely linked to the Program on Digital Brain Atlasing, the Program aims to establish a structured lexicon for the translation and definition of terms describing neural structures at multiple levels of granularity. The three Task Forces and one Working Group involved in the PONS effort: * Structural lexicon * Neuron registry * Representation and deployment * KnowledgeSpace Working Group Structural lexicon, Neuron registry, Representation and deployment, and KnowledgeSpace Working Group.

Proper citation: Program on Ontologies of Neural Structures (RRID:SCR_003549) Copy   

•   Source: SciCrunch Registry

http://www.incf.org/activities/our-programs/pons/cumbo

Ontology of formal definitions (i.e., machine processable) for the types of structures commonly described in neuroanatomy.

Proper citation: Common Upper Mammalian Brain Ontology (RRID:SCR_003629) Copy   

•   Source: SciCrunch Registry

http://www.nih.gov/science/amp/alzheimers.htm

The Alzheimer's disease arm of the Accelerating Medicines Partnership (AMP) that will identify biomarkers that can predict clinical outcomes, conduct a large scale analysis of human AD patient brain tissue samples to validate biological targets, and to increase the understanding of molecular pathways involved in the disease to identify new potential therapeutic targets. The initiative will deposit all data in a repository that will be accessible for use by the biomedical community. The five year endeavor, beginning in 2014, will result in several sets of project outcomes. For the biomarkers project, tau imaging and EEG data will be released in year two, as baseline data becomes available. Completed data from the randomized, blinded trials will be added after the end of the five year studies. This will include both imaging data and data from blood and spinal fluid biomarker studies. For the network analysis project, each project will general several network models of late onset AD (LOAD) and identify key drivers of disease pathogensis by the end of year three. Years four and five will be dedicated to validating the novel targets and refining the network models of LOAD, including screening novel compounds or drugs already in use for other conditions that may have the ability to modulate the likely targets.

Proper citation: Accelerating Medicines Partnership - Alzheimers (RRID:SCR_003742) Copy   

•   Source: SciCrunch Registry

http://neurovault.org/

Data repository where researchers can publicly store and share unthresholded statistical brain activation maps produced by MRI and PET studies.

Proper citation: NeuroVault (RRID:SCR_003806) Copy   

•   Source: SciCrunch Registry

http://www.mrc-cbu.cam.ac.uk/

Unit studying human cognition and the brain with about 90 researchers and postgraduate students investigating topics such as attention, emotion, language and memory. They are developing new treatments for depression, improving hearing through cochlear implants, and helping children to overcome memory problems. With a large collection of scientists engaged in both basic and translational research on the mind and brain, the Unit provides an exceptional training and academic environment that benefits postgraduate students and researchers at all levels. A significant part of their research makes use of brain imaging and they have excellent on-site facilities for magnetic resonance imaging (MRI) magnetoencephalography (MEG) and electroencephalography (EEG). They also have clinical facilities at Addenbrooke's Hospital. The Unit has close links both with the hospital and with Cambridge University.

Proper citation: MRC Cognition and Brain Sciences Unit (RRID:SCR_003818) Copy   

•   Source: SciCrunch Registry

http://synapses.clm.utexas.edu

A portal into the 3D ultrastructure of the brain providing: Anatomy of astrocytes, axons, dendrites, hippocampus, organelles, synapses; procedures of 3D reconstruction and tissue preparation; as well as an atlas of ultrastructural neurocytology (by Josef Spacek), online aligned images, and reconstructed dendrites. Synapse Web hosts an ultrastructural atlas containing more than 500 electron micrographs (added to regularly) that identify unique ultrastructural and cellular components throughout the brain. Additionally, Synapse Web has raw images, reconstructions, and quantitative data along with tutorial instructions and numerous tools for investigating the functional structure of objects that have been serial thin sectioned for electron microscopy.

Proper citation: Synapse Web (RRID:SCR_003577) Copy   

•   Source: SciCrunch Registry

http://medschool.umaryland.edu/btbank/

The objective of this human tissue repository is to systematically collect, store, and distribute brain and other tissues for research dedicated to the improved understanding, care, and treatment of individuals with developmental disorders. Brain sections are primarily frozen in isopentane / dry ice. Tissues are stored in 10% formalin and frozen at -85 degrees C. Of special interest are individuals with Down syndrome and other chromosomal defects, mitochondrial encephalopathies, phenylketonuria and other aminoacidopathies, maternal PKU, Rett syndrome, leukodystrophies, lysosomal disorders, dyslexia, autism, and other neurodevelopmental disorders. The brain and tissue banks have extensive experience in arranging for the rapid retrieval of tissue upon the death of individuals who die while at home, in hospitals or hospice care. As a special service, the brain and tissue banks are able to assist researchers who are working with patients who intend to donate tissues at the time of their death. Immediately after retrieval of the tissue, the brain and tissue banks will forward needed tissue to the referring investigators and ensure proper storage and cataloging of any additional tissues as part of the brain and tissue banks. The recipient of tissue and the brain and tissue banks are required to sign a Tissue Transfer Agreement before any tissues are transferred.

Proper citation: NICHD Brain and Tissue Bank for Developmental Disorders (RRID:SCR_003601) Copy   

•   Source: SciCrunch Registry

http://rfmri.org/

A network for supporting resting-state fMRI (R-fMRI) related studies. It connects R-fMRI researchers (as nodes) by their sharings (as edges). Through the network, ideas, comments, resources, tools, experiences, and data can be shared. Researchers (nodes) with basic neuroscience, methodological, or clinical backgrounds can connect with each other in the network. It also contains a preprint server that allows neuroscientists to share their preprints, comment on each others research and get back valuable information about their experiments from their colleagues. This is based on the arXiv model. Ultimately, the network aims to enhance collaborations among researchers, especially to translate knowledge of basic neuroscience and methodology to clinical applications (bench to bedside).

Proper citation: RFMRI.ORG (RRID:SCR_004042) Copy   

•   Source: SciCrunch Registry

http://www.caneucre.org

Cre expressing mice under the control of promoters with a design focus on the brain. Each promoter is derived from human sequence, but the resulting expression is assessed in the mouse for the activation of a LacZ reporter gene by the Cre activity. Promoters tested as large MaxiPromoters (BACs inserted into the mouse genome) and MiniPromoters (plasmid-based sequences inserted either into the mouse genome or introduced within AAV viruses). The Cre-related project continues from the Pleiades Promoter Project. Here is the list of genes for which icre/ERT2 mice are currently in development: AGTR1, CARTPT, CLDN5, CLVS2, CRH, GABRA6, HTR1A, HTR1B, KCNA4, KDM5C, MKI67, NEUROD6, NKX6-1, NOV, NPY2R, NR2E1, OLIG2, POU4F2, SLITRK6, SOX1, SOX3, SOX9,, SPRY1, VSX2

Proper citation: CanEuCre (RRID:SCR_004159) Copy   

•   Source: SciCrunch Registry

http://www.hedtags.org/

Strategy guide for HED Annotation. Framework for systematically describing laboratory and real world events.HED tags are comma separated path strings. Organized in forest of groups with roots Event, Item, Sensory presentation, Attribute, Action, Participant, Experiment context, and Paradigm. Used for preparing brain imaging data for automated analysis and meta analysis. Applied to brain imaging EEG, MEG, fNIRS, multimodal mobile brain or body imaging, ECG, EMG, GSR, or behavioral data. Part of Brain Imaging Data Structure standard for brain imaging.

Proper citation: HED Tags (RRID:SCR_014074) Copy   

•   Source: SciCrunch Registry

http://www.sci.utah.edu/software/fluorender.html

Interactive rendering tool for confocal microscopy data visualization. Combines rendering of multi-channel volume data and polygon mesh data, where properties of each dataset can be adjusted independently and quickly. Designed for neurobiologists, allowing them to better visualize confocal data from fluorescently-stained brains, but it is also useful for other biological samples. Features include feature tracking, 3D measurement tools, multiple render modes for multi-channel confocal data, and volume paint selection and segmentation.

Proper citation: FluoRender (RRID:SCR_014303) Copy   

•   Source: SciCrunch Registry

https://github.com/BlueBrain/BluePyOpt

An extensible framework for data-driven model parameter optimization that wraps and standardizes several existing open-source tools. BluePyOpt abstracts the optimization and evaluation tasks into various reusable and flexible discrete elements according to established best-practices. It also provides methods for setting up both small- and large-scale optimizations on a variety of platforms.

Proper citation: BluePyOpt (RRID:SCR_014753) Copy   

•   Source: SciCrunch Registry