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http://www.bic.mni.mcgill.ca/ServicesAtlases/Cyno

A reference atlas of cynomolgus macaque monkey magnetic resonance images. The template brain volume that offers a common stereotaxic reference frame to localize anatomical and functional information in an organized and reliable way for comparison across individual cynomolgus monkeys and studies. We have used MRI volumes from a group of 18 normal adult cynomulgus monkeys (Macaca fascicularis) to create the individual atlas. Thus, the atlas does not rely on the anatomy of a single subject, but instead depends on nonlinear normalization of numerous cynomolgus monkey brains mapped to an average template image that is faithful to the location of anatomical structures. Tools for registering a native MRI to the cynomolgus macaque atlas can be found in the Software section. Viewing the atlas and associated volumes online requires Java browser support. Additionally, you may download the atlas and associated files in your chosen format.

Proper citation: McConnell Brain Imaging Center MNI Cynomolgus Macaque Atlas (RRID:SCR_008793) Copy   

•   Source: SciCrunch Registry

http://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj2

An unbiased magnetic resonance imaging template brain volume for pediatric data from birth to 4.5y age range. These volumes were created using 317 scans from 108 children enrolled in the NIH-funded MRI study of normal brain development (Almli et al., 2007, Evans and Group 2006). Templates are constructed for different age ranges. Each age range includes an average T1w, T2w, PDw maps normalized between 0 and 100. Also each age range includes a binary brain mask. Tools for using these atlases can be found in the Software section.

Proper citation: NIHPD Objective 2 atlases (birth - 4.5 years) (RRID:SCR_008795) Copy   

•   Source: SciCrunch Registry

http://www.bic.mni.mcgill.ca/ServicesAtlases/Rhesus

A reference atlas of rhesus macaque monkey magnetic resonance images that offers a common stereotaxic reference frame. The atlas can be used to localize anatomical and functional information in an organized and reliable way for comparison across individual rhesus monkeys and studies. We have used MRI volumes from a group of 7 normal adult rhesus monkeys (Macaca mulatta) to create the individual atlas. Thus, the atlas does not rely on the anatomy of a single subject, but instead depends on nonlinear normalization of numerous rhesus monkey brains mapped to an average template image that is faithful to the location of anatomical structures. Tools for registering a native MRI to the rhesus macaque atlas can be found in the Software section. Viewing the atlas and associated volumes online requires Java browser support. Additionally, you may download the atlas and associated files in your chosen format.

Proper citation: McConnell Brain Imaging Center MNI Rhesus Macaque Atlas (RRID:SCR_008790) Copy   

•   Source: SciCrunch Registry

http://brain.io/

A startup research, development and innovation company based in The Grand Duchy of Luxembourg working on four major areas: Open Research, as Information Hub; Information Technology, as The Common Brain; Collective Awareness, as Manifesto; and Biophysics, as Human Extensibility. The Information Hub researches a methodology to conduct open research using a collaborative approach designed for multi-disciplinary interventions, multi-scope goal alignment, advanced analytics and a unified research experience for international cooperation. The Common Brain researches an open source intelligent architecture for future internet, one that is deeply sustainable over a highly distributed hybrid network, self-governed, heterogenous, and logical. Manifesto researches a methodology for a collaborative approach for policy making, open standardization, accreditation, verification and compliance. Human Extensibility researches the establishment of the scientific ground for a field of science concerned with the study of the physics and physiology of the human being, to provide techniques and genetic algorithms for human extensibility.

Proper citation: Brain.io (RRID:SCR_014527) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/broccoli/

A software package written in OpenCL (Open Computing Language) that can be used for parallel analysis of fMRI data on a large variety of hardware configurations. If BROCCOLI is running on a GPU, it can perform non-linear spatial normalization to a 1 mm brain template in 4-6 s and run a second level permutation test with 10,000 permutations.

Proper citation: BROCCOLI (RRID:SCR_014093) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/brainlife_io/

Platform for publishing reproducible code and datasets and providing access to national supercomputers, private clouds, and institutional high-performance computer systems to promote open software and data sharing to advance understanding of the human brain.

Proper citation: brainlife.io (RRID:SCR_016513) Copy   

•   Source: SciCrunch Registry

https://www.med.upenn.edu/sbia/brats2017.html

Organization that provides a conference about the methods for the segmentation of brain tumors in magnetic resonance imaging (MRI) scans. Its conferences utilize multi-institutional pre-operative MRI scans and focus on the segmentation of intrinsically heterogeneous (in appearance, shape, and histology) brain tumors, namely gliomas.

Proper citation: BraTS (RRID:SCR_016214) Copy   

•   Source: SciCrunch Registry

https://github.com/bids-standard/bids-validator

Software validation tool that checks submitted folder structure for compliance to BIDS data standard. Validates Brain Imaging Data Structure.

Proper citation: BIDS Validator (RRID:SCR_017255) Copy   

•   Source: SciCrunch Registry

https://www.drugabuse.gov

Portal provides list of genetic resources such as Brain Atlases and genomes for various species provided by National Institute of Drug Abuse.

Proper citation: Compilation of Genetics Resource Databases (RRID:SCR_017501) Copy   

•   Source: SciCrunch Registry

https://github.com/nipy/heudiconv

Software tool as flexible DICOM converter for organizing brain imaging data into structured directory layouts.

Proper citation: HeuDiConv: a heuristic-centric DICOM converter (RRID:SCR_017427) Copy   

•   Source: SciCrunch Registry

https://cic.ini.usc.edu/

Project to create complete mesoscale connectivity atlas of the C57Black/6 mouse brain and to subsequently generate its global neural networks.

Proper citation: Mouse Connectome Project (RRID:SCR_017313) Copy   

•   Source: SciCrunch Registry

http://www.morf-brain.com/

Portal devoted to suite of MORF reporter mice labels of Cre positive neurons and glia distributed stochastically throughout brain and can be imaged with endogenous fluorescence (mNeonGreen in MORF1 and EGFP in TIGRE-MORF) or stained for multivalent immunoreporter (Spaghetti Monster fluorescent protein V5, or smFP-V5, in MORF3). MORF technology used to label and reconstruct thousands genetically defined cells per brain for large scale, unbiased classification and quantitative analyses of CNS cell types brainwide.

Proper citation: Mononucleotide Repeat Frameshift Portal (RRID:SCR_021125) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/retro/BeijingEOEC.html

Data set of 48 healthy controls from a community (student) sample from Beijing Normal University in China with 3 resting state fMRI scans each. During the first scan participants were instructed to rest with their eyes closed. The second and third resting state scan were randomized between resting with eyes open versus eyes closed. In addition this dataset contains a 64-direction DTI scan for every participant. The following data are released for every participant: * 6-minute resting state fMRI scan (R-fMRI) * MPRAGE anatomical scan, defaced to protect patient confidentiality * 64-direction diffusion tensor imaging scan (2mm isotropic) * Demographic information and information on the counterbalancing of eyes open versus eyes closed.

Proper citation: Beijing: Eyes Open Eyes Closed Study (RRID:SCR_001507) Copy   

•   Source: SciCrunch Registry

http://www.nmr.mgh.harvard.edu/CFNT/index

Biomedical technology research center that develops and applies innovative neuroimaging technologies and techniques to enable closer examination of the human brain, and thereby contribute to better understanding of the brain in health and disease. They develop new techniques and advance existing technologies for acquisition and analysis of functionally specific images of the working brain, with unprecedented physiological precision and spatiotemporal resolution. The research and development aims to improve and extend existing methods for non-invasive magnetic resonance image analysis and acquisition, electromagnetic source imaging, optical neuroimaging, and most recently, combined MR-PET neuroimaging. The Resource provides an essential interactive environment, within which an interdisciplinary team of highly skilled scientists, engineers, and clinicians with diverse expertise in multiple modalities and disciplines. The resource supports service use of the Center's facilities by neuroscientists throughout the country, provide extensive training opportunities for students, fellows, and staff scientists, and seek to advance the field of brain mapping through active dissemination of new knowledge and technology.

Proper citation: Center for Functional Neuroimaging Technologies (RRID:SCR_001423) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/resources/Tools/record/nlx_144509-1/6b508d2a-fd5f-56f2-93cf-462fcd52548e/search?q=*&l=&facet%5B%5D=Parent%20Organization:University%20of%20Michigan;%20Michigan;%20USA&sort=added

THIS RESOURCE IS NO LONGER IN SERVICE. Documented September 12, 2017.

Dataset in Bilingual exposure optimizes left-hemisphere dominance for selective attention processes in the developing brain by Arredondo, Su, Satterfield, & Kovelman (XX) Does early bilingual exposure alter the representations of cognitive processes in the developing brain? Theories of bilingual development have suggested that bilingual language switching might improve children''s executive function and foster the maturation of prefrontal brain regions that support higher cognition. To test this hypothesis, we used functional Near Infrared Spectroscopy to measure brain activity in Spanish-English bilingual and English-monolingual children during a visuo-spatial executive function task of attentional control (N=27, ages 7-13). Prior findings suggest that while young children start with bilateral activation for the task, it becomes right-lateralized with age (Konrad et al., 2005). Indeed monolinguals showed bilateral frontal activation, however young bilinguals showed greater activation in left language areas relative to right hemisphere and relative to monolinguals. The findings suggest that bilingual experience optimizes attention mechanisms in the language hemisphere, and highlight the importance of early experiences for neurodevelopmental plasticity of higher cognition. These data are made available from Ioulia Kovelman''s Language and Literacy Lab at University of Michigan and may be exported through the NIF Data Federation. To cite these data please use this text Data were published by Arredondo et al. (XX) and made available via the NIF at XX

Proper citation: Arredondo ANT fNIRS dataset1 (RRID:SCR_002653) Copy   

•   Source: SciCrunch Registry

http://ranchobiosciences.com/gse4271/

Curated data set from a study that investigated 77 primary high-grade astrocytomas and 23 matched recurrences so that changes in gene expression related to both survival and disease progression can be identified. Samples in the study include WHO grade III and IV astrocytomas with a wide range of survival times.

Proper citation: GSE4271 (RRID:SCR_003643) Copy   

•   Source: SciCrunch Registry

http://nif.nimh.nih.gov/

Neurophysiology imaging core facility that provides anatomical and functional MRI scanning for researchers in the National Institute of Mental Health (NIMH), the National Eye Institute (NEI), and the National Institute for Neurological Disorders and Stroke (NINDS). The shared intramural resource centers on a cutting-edge 4.7T vertical bore scanner dedicated to imaging of nonhuman primates.

Proper citation: Neurophysiology Imaging Facility (RRID:SCR_004080) Copy   

•   Source: SciCrunch Registry

http://www.chibi.ubc.ca/WhiteText/

Freely available corpus of manually annotated brain region mentions created to facilitate text mining of neuroscience literature. The corpus contains 1,377 abstracts with 18,242 brain region annotations. Interannotator agreement was evaluated for a subset of the documents, and was 90.7% and 96.7% for strict and lenient matching respectively. We observed a large vocabulary of over 6,000 unique brain region terms and 17,000 words. For automatic extraction of brain region mentions we evaluated simple dictionary methods and complex natural language processing techniques. The dictionary methods based on neuroanatomical lexicons recalled 36% of the mentions with 57% precision. The best performance was achieved using a conditional random field (CRF) with a rich feature set. Features were based on morphological, lexical, syntactic and contextual information. The CRF recalled 76% of mentions at 81% precision, by counting partial matches recall and precision increase to 86% and 92% respectively. We suspect a large amount of error is due to coordinating conjunctions, previously unseen words and brain regions of less commonly studied organisms. We found context windows, lemmatization and abbreviation expansion to be the most informative techniques. We encourage you to test new methods and applications of the dataset. Please contact us if you do, we would like to hear about and link to your work. The abstracts are from PubMed/Medline, specifically The Journal of Comparative Neurology.

Proper citation: Automated recognition of brain region mentions in neuroscience literature. (RRID:SCR_002731) Copy   

•   Source: SciCrunch Registry

http://www.mri-resource.kennedykrieger.org/

Biomedical technology research center that provides expertise for the design of quantitative magnetic resonance imaging (MRI) and spectroscopy (MRS) data acquisition and processing technologies that facilitate the biomedical research of a large community of clinicians and neuroscientists in Maryland and throughout the USA. These methods allow noninvasive assessment of changes in brain anatomy as well as in tissue metabolite levels, physiology, and brain functioning while the brain is changing size during early development and during neurodegeneration, i.e. the changing brain throughout the life span. The Kirby Center has 3 Tesla and 7 Tesla state of the art scanners equipped with parallel imaging (8, 16, and 32-channel receive coils) and multi-transmit capabilities. CIS has an IBM supercomputer that is part of a national supercomputing infrastructure. Resources fall into the following categories: * MRI facilities, image acquisition, and processing * Computing facilities and image analysis * Novel statistical methods for functional brain imaging * Translating laboratory discoveries to patient treatment

Proper citation: National Resource for Quantitative Functional MRI (RRID:SCR_006716) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/scicrunch/data/source/nlx_154697-8/search?q=*

A data set of connectivity statements from BAMS, CoCoMac, BrainMaps, Connectome Wiki, the Hippocampal-Parahippocampal Table of Temporal-Lobe.com, and Avian Brain Circuitry Database. The data set lists which brain sites connectivity is to and from, the organism connectivity is mapped in, and journal references.

Proper citation: Integrated Nervous System Connectivity (RRID:SCR_006391) Copy   

•   Source: SciCrunch Registry