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http://neuro.debian.net/

Collection based on a collaborative effort of popular neuroscience research software for the Debian operating system as well as Ubuntu and other derivatives. Popular packages include AFNI, FSL, PyMVPA and many others. It contains both unofficial or prospective packages which are not (yet) available from the main Debian archive, as well as backported or simply rebuilt packages also available elsewhere. A listing of current and planned projects is available if you want to get involved. The main goal of the project is to provide a versatile and convenient environment for neuroscientific research that is based on open-source software. To this end, the project offers a package repository that complements the main Debian (and Ubuntu) archive. NeuroDebian is not yet another Linux distribution, but rather an effort inside the Debian project itself. Software packages are fully integrated into the Debian system and from there will eventually migrate into Ubuntu as well. With NeuroDebian, installing and updating neuroscience software is no different from any other part of the operating system. Maintaining a research software environment becomes as easy as installing an editor. There is also virtual machine to test NeuroDebian on Windows or Mac OS. If you want to see your software packaged for Debian, please drop them a note.

Proper citation: neurodebian (RRID:SCR_004401) Copy   

•   Source: SciCrunch Registry

http://hippocampome.org

A curated knowledge base of the circuitry of the hippocampus of normal adult, or adolescent, rodents at the mesoscopic level of neuronal types. Knowledge concerning dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex is distilled from published evidence and is continuously updated as new information becomes available. Each reported neuronal property is documented with a pointer to, and excerpt from, relevant published evidence, such as citation quotes or illustrations. Please note: This is an alpha-testing site. The content is still being vetted for accuracy and has not yet undergone peer-review. As such, it may contain inaccuracies and should not (yet) be trusted as a scholarly resource. The content does not yet appear uniformly across all combinations of browsers and screen resolutions.

Proper citation: Hippocampome.org (RRID:SCR_009023) Copy   

•   Source: SciCrunch Registry

https://imagej.net/

Open source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.

Proper citation: ImageJ (RRID:SCR_003070) Copy   

•   Source: SciCrunch Registry

http://elastix.isi.uu.nl/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023. Software toolbox for rigid and nonrigid registration of images. elastix is open source software, based on the well-known Insight Segmentation and Registration Toolkit (ITK). The software consists of a collection of algorithms that are commonly used to solve (medical) image registration problems. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. A command-line interface enables automated processing of large numbers of data sets, by means of scripting. A paper describing elastix contains more details: S. Klein, M. Staring, K. Murphy, M.A. Viergever, J.P.W. Pluim, elastix: a toolbox for intensity based medical image registration,; IEEE Transactions on Medical Imaging, vol. 29, no. 1, pp. 196 - 205, January 2010., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: elastix (RRID:SCR_009619) Copy   

•   Source: SciCrunch Registry

http://www.brain.org.au/software/mrtrix/

A set of tools to perform diffusion-weighted MRI white matter tractography in the presence of crossing fibres, using Constrained Spherical Deconvolution (Tournier et al.. 2004; Tournier et al. 2007), and a probabilisitic streamlines algorithm (e.g. Behrens et al., 2003; Parker et al., 2003). These applications have been written from scratch in C++, using the functionality provided by the GNU Scientific Library, and gtkmm. The software is currently capable of handling DICOM, NIfTI and AnalyseAVW image formats, amongst others. Installation * Unix/Linux * Microsoft Windows * Mac Os X, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: MRtrix (RRID:SCR_006971) Copy   

•   Source: SciCrunch Registry

https://dipy.org/

Software Python package for analyzing diffusion data. Software library for analysis of diffusion MRI data.

Proper citation: Dipy (RRID:SCR_000029) Copy   

•   Source: SciCrunch Registry

http://neuralensemble.org/trac/OpenElectrophy

Software Python module for electrophysiology data analysis.

Proper citation: OpenElectrophy (RRID:SCR_000819) Copy   

•   Source: SciCrunch Registry

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

Software Python library that relies on the REST API provided by the XNAT platform since its 1.4 version. XNAT is an extensible database for neuroimaging data. The main objective is to ease communications with an XNAT server to plug-in external tools or python scripts to process the data.

Proper citation: pyxnat (RRID:SCR_002574) Copy   

•   Source: SciCrunch Registry

http://www.paraview.org/

Open source, multi platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities. ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data.

Proper citation: ParaView (RRID:SCR_002516) Copy   

•   Source: SciCrunch Registry

http://www.xnat.org

Software platform designed to facilitate common management and productivity tasks for neuroimaging and associated data.

Proper citation: XNAT - The Extensible Neuroimaging Archive Toolkit (RRID:SCR_003048) Copy   

•   Source: SciCrunch Registry

https://bioimagesuiteweb.github.io/webapp/index.html

Web applications for analysis of multimodal/multispecies neuroimaging data. Image analysis software package. Has facilities for DTI and fMRI processing. Capabilities for both neuro/cardiac and abdominal image analysis and visualization. Many packages are extensible, and provide functionality for image visualization and registration, surface editing, cardiac 4D multi-slice editing, diffusion tensor image processing, mouse segmentation and registration, and much more. Can be intergrated with other biomedical image processing software, such as FSL, AFNI, and SPM.

Proper citation: BioImage Suite (RRID:SCR_002986) Copy   

•   Source: SciCrunch Registry

http://martinos.org/mne/

Software suite for processing magnetoencephalography and electroencephalography data. Open source Python software for exploring, visualizing, and analyzing human neurophysiological data including MEG, EEG, sEEG, ECoG . Implements all functionality of MNE Matlab tools in Python and extends capabilities of MNE Matlab tools to, e.g., frequency-domain and time-frequency analyses and non-parametric statistics.

Proper citation: MNE software (RRID:SCR_005972) Copy   

•   Source: SciCrunch Registry

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

A native Java-based imaging processing environment similar to the ITK/VTK paradigm. Initially developed as an extension to MIPAV (CIT, NIH, Bethesda, MD), the JIST processing infrastructure provides automated GUI generation for application plug-ins, graphical layout tools, and command line interfaces. This repository maintains the current multi-institutional JIST development tree and is recommended for public use and extension. JIST was originally developed at IACL and MedIC (Johns Hopkins University) and is now also supported by MASI (Vanderbilt University).

Proper citation: JIST: Java Image Science Toolkit (RRID:SCR_008887) Copy   

•   Source: SciCrunch Registry

http://www.imagevis3d.org/

A new volume rendering program developed by the NIH/NCRR Center for Integrative Biomedical Computing (CIBC). The main design goals of ImageVis3D are: simplicity, scalability, and interactivity. Simplicity is achieved with a new user interface that gives an unprecedented level of flexibility (as shown in the images). Scalability and interactivity for ImageVis3D mean that both on a notebook computer as well as on a high end graphics workstation, the user can interactively explore terabyte sized data sets. Finally, the open source nature as well as the strict component-by-component design allow developers not only to extend ImageVis3D itself but also reuse parts of it, such as the rendering core. This rendering core, for instance, is planned to replace the volume rendering subsystems in many applications at the SCI Institute and with their collaborators.

Proper citation: ImageVis3D (RRID:SCR_009566) Copy   

•   Source: SciCrunch Registry

http://www.psychopy.org

Open source application to allow the presentation of stimuli and collection of data for a wide range of neuroscience, psychology and psychophysics experiments. It is intended as a free, powerful alternative to Presentation or e-Prime.

Proper citation: PsychoPy (RRID:SCR_006571) Copy   

•   Source: SciCrunch Registry

http://www.picsl.upenn.edu/ANTS/

Software package designed to enable researchers with advanced tools for brain and image mapping. Many of the ANTS registration tools are diffeomorphic*, but deformation (elastic and BSpline) transformations are available. Unique components of ANTS include multivariate similarity metrics, landmark guidance, the ability to use label images to guide the mapping and both greedy and space-time optimal implementations of diffeomorphisms. The symmetric normalization (SyN) strategy is a part of the ANTS toolkit as is directly manipulated free form deformation (DMFFD). *Diffeomorphism: a differentiable map with differentiable inverse. In general, these maps are generated by integrating a time-dependent velocity field. ANTS Applications: * Gray matter morphometry based on the jacobian and/or cortical thickness. * Group and single-subject optimal templates. * Multivariate DT + T1 brain templates and group studies. * Longitudinal brain mapping -- special similarity metric options. * Neonatal and pediatric brain segmentation. * Pediatric brain mapping. * T1 brain mapping guided by tractography and connectivity. * Diffusion tensor registration based on scalar or connectivity data. * Brain mapping in the presence of lesions. * Lung and pulmonary tree registration. * User-guided hippocampus labeling, also of sub-fields. * Group studies and statistical analysis of cortical thickness, white matter volume, diffusion tensor-derived metrics such as fractional anisotropy and mean diffusion.

Proper citation: ANTS - Advanced Normalization ToolS (RRID:SCR_004757) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/gsa-snp/

A tool for the gene-set (or pathway) analysis of a genome-wide association study result. It accepts a genome-wide list of SNPs and their association P-values. It summarizes the SNP P-values into nearby genes. The gene-by-gene summary results are then further summarized by gene-sets such as Gene Ontology, KEGG pathways, or user-created gene-sets. Various standardization and statistical tests can be performed and the resulting gene-sets that pass a significance level after multiple-testing correction are reported. The tool is written in Java and is available as a standalone version.

Proper citation: GSA-SNP (RRID:SCR_013109) Copy   

•   Source: SciCrunch Registry

https://as.nyu.edu/research-centers/cbi/resources/Software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software which converts DICOM images to NIfTI format.

Proper citation: dinifti (RRID:SCR_000303) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/a/brain.org.au/ctp/

Software package with functions that will help researchers plan how many subjects per group need to be included in an MRI-based cortical thickness study to ensure a thickness difference is detected. The package requires cortical thickness mapping and co-registration to be carried out using Freesurfer. The power analyses are implemented in the R software package., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: cortex (RRID:SCR_002467) Copy   

•   Source: SciCrunch Registry

https://pydicom.github.io/

Software Python package for working with DICOM files, made for inspecting and modifying DICOM data in an easy pythonic way. The modifications can be written again to a new file. As a pure python package, it should run anywhere python runs without any other requirements.

Proper citation: pydicom (RRID:SCR_002573) Copy   

•   Source: SciCrunch Registry