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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   

•   Source: SciCrunch Registry

http://www.jeiglesias.com

An automatic whole-brain extraction tool for T1-weighted MRI data (commonly known as skull stripping). Whole-brain segmentation is often the first component in neuroimage pipelines and therefore, its robustness is critical for the overall performance of the system. Many methods have been proposed in the literature, but they often: * work well on certain datasets but fail on others. * require case-specific parameter tuning ROBEX aims for robust skull-stripping across datasets with no parameter settings. It fits a triangular mesh, constrained by a shape model, to the probabilistic output of a supervised brain boundary classifier. Because the shape model cannot perfectly accommodate unseen cases, a small free deformation is subsequently allowed. The deformation is optimized using graph cuts.

Proper citation: ROBEX (RRID:SCR_002534) Copy   

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http://www.kumc.edu/instruction/medicine/anatomy/histoweb/nervous/nervous.htm

Histology atlas of different parts of the nervous system that corresponds with the laboratory exercises of the Cell & Tissue Biology course of the School of Medicine of the University of Kansas. Succinct explanations of the tissues to guide the first-year medical student in the use of their microscope is provided and subsequently serves as a permanent histology resource for all medical students and physicians. Sections of the brain that are included are: * Spinal Cord * Central Canal * White Matter * Gray Matter * Dorsal Root Ganglion * Cerebellum * Cerebrum * Astrocytes * Nerve * Node of Ranvier * Pacinian Corpuscle

Proper citation: HistoWeb: Nervous System (RRID:SCR_002369) Copy   

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http://www.behav.org/abcd/abcd.php

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 21, 2017.

Database developed for storing, retrieving and cross-referencing neuroscience information about the connectivity of the avian brain. It contains entries about the new and old terminology of the areas and their hierarchy and data on connections between brain regions, as well as a functional keyword system linked to brain regions and connections.

Proper citation: Avian Brain Circuitry Database (RRID:SCR_002401) Copy   

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http://www.cognitorium.com/

THIS RESOURCE IS NO LONGER IN SERVICE, documented October 28, 2015. Interactive, informative and educational community platform dedicated to cognitive science or the multidisciplinary exploration of the mind. This online platform, will help gather and link information providing a thorough and reliable source of information for students and professionals in the field, as well as help bridge the gap between academia and the society. Due to the multidisciplinary nature of cognitive science, the work is becoming increasingly specialized. Therefore to keep an eye on the bigger picture, it seems necessary to bring the discoveries of various disciplines together in one place, look at their similarities and differences and discuss them for future directions.

Proper citation: Cognitorium (RRID:SCR_000098) Copy   

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http://www.loni.usc.edu/Software/LOVE

A versatile 1D, 2D and 3D data viewer geared for cross-platform visualization of stereotactic brain data. It is a 3-D viewer that allows volumetric data display and manipulation of axial, sagittal and coronal views. It reads Analyze, Raw-binary and NetCDF volumetric data, as well as, Multi-Contour Files (MCF), LWO/LWS surfaces, atlas hierarchical brain-region labelings ( Brain Trees). It is a portable Java-based software, which only requires a Java interpreter and a 64 MB of RAM memory to run on any computer architecture. LONI_Viz allows the user to interactively overlay and browse through several data volumes, zoom in and out in the axial, sagittal and coronal views, and reports the intensities and the stereo-tactic voxel and world coordinates of the data. Expert users can use LONI_Viz to delineate structures of interest, e.g., sulcal curves, on the 3 cardinal projections of the data. These curves then may be use to reconstruct surfaces representing the topological boundaries of cortical and sub-cortical regions of interest. The 3D features of the package include a SurfaceViewer and a full real-time VolumeRenderer. These allow the user to view the relative positions of different anatomical or functional regions which are not co-planar in any of the axial, sagittal or coronal 2D projection planes. The interactive part of LONI_Viz features a region drawing module used for manual delineation of regions of interest. A series of 2D contours describing the boundary of a region in projection planes (axial, sagittal or coronal) could be used to reconstruct the surface-representation of the 3D outer shell of the region. The latter could then be resliced in directions complementary to the drawing-direction and these complementary contours could be loaded in all tree cardinal views. In addition the surface object could be displayed using the SurfaceViewer. A pre-loading data crop and sub-sampling module allows the user to load and view practically data of any size. This is especially important when viewing cryotome, histological or stained data-sets which may reach 1GB (109 bytes) in size. The user could overlay several pre-registered volumes, change intensity colors and ranges and the inter-volume opacities to visually inspect similarities and differences between the different subjects/modalities. Several image-processing aids provide histogram plotting, image-smoothing, etc. Specific Features: * Region description DataBase * Moleculo-genetic database * Brain anatomical data viewer * BrainMapper tool * Surface (LightWave objects/scenes) and Volume rendering tools * Interactive Contour Drawing tool Implementation Issues: * Applet vs. Application - the software is available as both an applet and a standalone application. The former could be used to browse data from within the LONI database, however, it imposes restrictions on file-size, Internet connection and network-bandwidth and client/server file access. The later requires a local install and configuration of the LONI_Viz software * Extendable object-oriented code (Java), computer architecture independent * Complete online software documentation is available at http://www.loni.ucla.edu/LONI_Viz and a Java-Class documentation is available at http://www.loni.ucla.edu/~dinov/LONI_Vis.dir/doc/LONI_Viz_Java_Docs.html

Proper citation: LONI Visualization Tool (RRID:SCR_000765) Copy   

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http://www.drugabuseresearchtraining.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on November 07, 2012. Decemeber 15, 2011 - Thank you for your interest in DrugAbuseResearchTraining.org. The site, courses, and resources are no longer available. Please send an email to inquiry (at) md-inc.com if you would like to be notified if the site or courses become available again. Introduction to Clinical Drug and Substance Abuse Research Methods is an online training program intended to introduce clinicians and substance abuse professionals to basic clinical research methods. The program is divided into four modules. Each module covers an entire topic and includes self-assessment questions, references, and online resources: * The Neurobiology of Drug Addiction * Biostatistics for Drug and Substance Abuse Research * Evaluating Drug and Substance Abuse Programs * Designing and Managing Drug and Substance Abuse Clinical Trials The learning objectives of this program are to help you: * Evaluate the benefits of alternative investigative approaches for answering important questions in drug abuse evaluation and treatment. * Define the proper levels of measurement and appropriate statistical methods for a clinical study. * Address common problems in data collection and analysis. * Anticipate key human subjects and ethical issues that arise in drug abuse studies. * Interpret findings from the drug abuse research literature and prepare a clinical research proposal. * Prepare research findings for internal distribution or publication in the peer reviewed literature. * Recognize drug addiction as a cyclical, chronic disease. * Understand and describe the brain circuits that are affected by addicting drugs, and explain to others the effects of major classes of addicting drugs on brain neurotransmitters. * Utilize new pharmacologic treatments to manage persons with drug addiction. Physicians can earn AMA PRA Category 1 Credit and purchase a high resolution printable electronic CME certificate(view sample); non-physicians can purchase high resolution printable electronic certificate of course participation that references AMA PRA Category 1 credit (view sample). This program does not offer printed certificates.

Proper citation: Online Education for the International Research Community: AboutIntroduction to Clinical Drug and Substance Abuse Research Methods (RRID:SCR_000802) Copy   

•   Source: SciCrunch Registry

http://zebrafishucl.org/zebrafishbrain#about-1

Collates and curates neuroanatomical data and information generated both in-house and by community to communicate current state of knowledge about neuroanatomical structures in developing zebrafish. Most of data come from high resolution confocal imaging of intact brains in which neuroanatomical structures are labelled by combinations of transgenes and antibodies. Community repository for image based data related to neuroanatomy of zebrafish.

Proper citation: Zebrafish Brain Atlas (RRID:SCR_000606) Copy   

•   Source: SciCrunch Registry

http://mbl.org

Collection of high resolution images and databases of brains from many genetically characterized strains of mice with aim to systematically map and characterize genes that modulate architecture of mammalian CNS. Includes detailed information on genomes of many strains of mice. Consists of images from approximately 800 brains and numerical data from just over 8000 mice. You can search MBL by strain, age, sex, body or brain weight. Images of slide collection are available at series of resolutions. Apple's QuickTime Plugin is required to view available MBL Movies.

Proper citation: Mouse Brain Library (RRID:SCR_001112) Copy   

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http://clarityresourcecenter.org/

Protocols and other training materials related to the CLARITY protocol, a technique for the transformation of intact tissue into a nanoporous hydrogel-hybridized form (crosslinked to a three-dimensional network of hydrophilic polymers) that is fully assembled but optically transparent and macromolecule-permeable.

Proper citation: Clarity resources (RRID:SCR_001387) Copy   

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http://kesm.cs.tamu.edu

A web-based, light-weight 3D volume viewer that serves large volumes (typically the whole brain) of high-resolution mouse brain images (~1.5 TB per brain, ~1 um resolution) from the Knife-Edge Scanning Microscope (KESM), invented by Bruce H. McCormick. Currently, KESMBA serves the following data sets: * Mouse: Whole-brain-scale Golgi (acquired 2008 spring): neuronal morphology: Choe et al. (2009) * Mouse: Whole-brain India Ink (acquired 2008 spring): vascular network: Choe et al. (2009); Mayerich et al. (2011); * Mouse: Whole-brain Golgi (acquired 2011 summer): neuronal morphology: Choe et al. (2011); Chung et al. (2011); * Mouse: Whole-brain Nissl (acquired 2009-2010 winter): somata (Choe et al. 2010) (Coming soon) They will ship you the full data set on a hard drive if you provide them with the hard drive and shipping cost.

Proper citation: KESM brain atlas (RRID:SCR_001559) Copy   

•   Source: SciCrunch Registry

http://library.med.utah.edu/kw/hyperbrain/

An online tutorial for human neuroanatomy designed as a supplement to textbook and class learning or as a lab substitute when human specimens, slides and models are not available. HyperBrain includes thousand of images and hundreds of linked illustrated glossary terms, as well as movies, quizzes and interactive animations. Last updated 2012.

Proper citation: HyperBrain (RRID:SCR_001595) Copy   

•   Source: SciCrunch Registry

https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FDT

Software toolbox for analysis of diffusion weighted images.

Proper citation: FMRIB's Diffusion Toolbox (RRID:SCR_024931) Copy   

•   Source: SciCrunch Registry

http://kymata-atlas.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. An online atlas of neural function, maintained by Cambridge University and the MRC Cognition and Brain Sciences Unit (CBSU).

Proper citation: Kymata Atlas (RRID:SCR_000269) Copy   

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http://www.cabiatl.com/mricro/anatomy/home.html

Annotated magnetic resonance brain images, both slices and surface views, normalized to Talairach space, along with annotations and a nice tutorial on image normalization. A viewer for MRI images (MRicro) is available and is described in a separate entry. Series of coronal, axial and sagittal brain slices along with some rendered volumes with major brain structures delineated. Slices are presented as static series with partial overlap of slices, so they are not suitable for 3d reconstruction. This neuroanatomy atlas shows regions on normalized MRI scans. Normalization is the process of warping a brain to match a standard size, orientation and shape of other brains. You can normalize MRI scans using programs like AIR, FLIRT or SPM. Once normalized, the overall shape of your MRI scan will approximately match those in this atlas. However, normalization preserves the unique sulcal features of each brain, so there will be some variation between your image and the images shown in this atlas. There is a great deal of individual variability even after normalization, so any atlas is only a rough guide to the shape and location of structures in an individuals brain. As I have noted before, secondary and tertiary sulci are not found in all individuals (Ono et al. 1990, Atlas of Cerebral Sulci). Another benefit of normalizing brains is it makes it easy to complete an accurate "scalp stripping" with brain extracting software (my MRIcro software implements Steve Smith's BET for this task). You can then create a useful volume rendering of the cortical surface. Typically, it is much easier to identify cortical sulci and gyri by looking at a rendered image of the brain's surface. This atlas shows you how to recognize these landmarks on a rendered MRI scan.

Proper citation: Neuroanatomy Atlas (RRID:SCR_002402) Copy   

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http://www.emouseatlas.org

Detailed multidimensional digital multimodal atlas of C57BL/6J mouse nervous system with data and informatics pipeline that can automatically register, annotate, and visualize large scale neuroanatomical and connectivity data produced in histology, neuronal tract tracing, MR imaging, and genetic labeling. MAP2.0 interoperates with commonly used publicly available databases to bring together brain architecture, gene expression, and imaging information into single, simple interface.Resource to visualise mouse development, identify anatomical structures, determine developmental stage, and investigate gene expression in mouse embryo. eMouseAtlas portal page allows access to EMA Anatomy Atlas of Mouse Development and EMAGE database of gene expression.EMAGE is freely available, curated database of gene expression patterns generated by in situ techniques in developing mouse embryo. EMA, e-Mouse Atlas, is 3-D anatomical atlas of mouse embryo development including histology and includes EMAP ontology of anatomical structure, provides information about shape, gross anatomy and detailed histological structure of mouse, and framework into which information about gene function can be mapped.

Proper citation: eMouseAtlas (RRID:SCR_002981) Copy   

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http://udn.nichd.nih.gov/brainatlas_home.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 1, 2019. The first brain atlas for the common marmoset to be made available since a printed atlas by Stephan, Baron and Schwerdtfeger published in 1980. It is a combined histological and magnetic resonance imaging (MRI) atlas constructed from the brains of two adult female marmosets. Histological sections were processed from Nissl staining and digitized to produce an atlas in a large format that facilitates visualization of structures with significant detail. Naming of identifiable brain structures was performed utilizing current terminology. For the present atlas, an adult female was perfused through the heart with PBS followed by 10% formalin. The brain was then sent to Neuroscience Associates of Knoxville, TN, who prepared the brain for histological analysis. The brain was cut in the coronal (frontal) plane at 40 microns, every sixth section stained for Nissl granules with thionine and every seventh section stained for myelinated fibers with the Weil technique. The mounted sections were photographed at the NIH (Medical Arts and Photography Branch). The equipment used was a Nikon Multiphot optical bench with Zeiss Luminar 100 mm lens, and scanned with a Better Light 6100 scan back driven by Better Light Viewfinder 5.3 software. The final images were saved as arrays of 6000x8000 pixels in Adobe Photoshop 6.0. A scale in mm provided with these images permitted construction of the final Nissl atlas files with a horizontal and vertical scale. Some additional re-touching (brightness and contrast) was done with Adobe Photoshop Elements 2.0. The schematic (labeled) atlas plates were created from the Nissl images. The nomenclature came almost exclusively from brainmaps.org, where a rhesus monkey brain with structures labeled can be found. The labels for the MRI images were placed by M. R. Zametkin, under supervision from Dr. Newman.

Proper citation: Brain atlas of the common marmoset (RRID:SCR_005135) Copy   

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https://sourceforge.net/projects/bva-io/

Software package for interfacing the Brain Vision Analyser data files (load/save) for ongoing development of Matlab routines . This package is also compatible with the EEGLAB software, and may be uncompressed in the plugin folder of this software.

Proper citation: BVA import/export EEGLAB plugin (RRID:SCR_016333) Copy   

•   Source: SciCrunch Registry

https://github.com/DiedrichsenLab/DCBC/tree/v1.0.0

Software Python toolbox for brain parcellation evaluation.

Proper citation: DCBC toolbox (RRID:SCR_022176) Copy   

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https://www.nitrc.org/projects/rshrf

Software toolbox for resting state HRF estimation and deconvolution analysis. Matlab and Python toolbox that implements HRF estimation and deconvolution from resting state BOLD signal. Used to retrieve optimal lag between events and HRF onset, as well as HRF shape. Once that HRF has been retrieved for each voxel/vertex, it can be deconvolved from time series or one can map shape parameters everywhere in brain and use it as pathophysiological indicator. Input can be 2D GIfTI, 3D or 4D NIfTI images, but also on time series matrices/vectors. Output are three HRF shape parameters for each voxel/vertex, plus deconvolved time series, and number of retrieved pseudo events. All can be written back to GIfTI or NIfTI images.

Proper citation: Resting State Hemodynamic Response Function Retrieval and Deconvolution (RRID:SCR_023663) Copy   

•   Source: SciCrunch Registry