Debian Science Project
Summary
Cognitive neuroscience
Debian Science packages for Cognitive Neuroscience

This metapackage will install Debian packages which might be useful for scientists doing cognitive neuroscience research. This comprises the full research process from conducting psychophysical experiments, over data acquisition and analysis, to visualization and typesetting of scientific results.

The selection of packages is targeting the application of analysis techniques. Methods developers are referred to the science-statistics, science-imageanalysis, science-numericalcomputation, med-imaging, and med-imaging-dev metapackages for a variety of additional software that might be useful in the context of cognitive neuroscience.

Description

For a better overview of the project's availability as a Debian package, each head row has a color code according to this scheme:

If you discover a project which looks like a good candidate for Debian Science to you, or if you have prepared an unofficial Debian package, please do not hesitate to send a description of that project to the Debian Science mailing list

Links to other tasks

Debian Science Cognitive neuroscience packages

Official Debian packages with high relevance

Amide
software for Medical Imaging
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AMIDE: (Amide's a Medical Imaging Data Examiner) AMIDE is a tool for viewing and analyzing medical image data sets. It's capabilities include the simultaneous handling of multiple data sets imported from a variety of file formats, image fusion, 3D region of interest drawing and analysis, volume rendering, and rigid body alignments.

Amide imports most clinical DICOM files (using the DCMTK library).

Please cite: Andreas Markus Loening and Sanjiv Sam Gambhir: AMIDE: A Free Software Tool for Multimodality Medical Image Analysis. (PubMed) Molecular Imaging 2(3):131-7 (2003)
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Caret
Computerized Anatomical Reconstruction and Editing Toolkit
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This software allows for creating, viewing and manipulating surface reconstructions of the cerebral and cerebellar cortex, viewing volumes and for displaying experimental data on the surfaces and volumes. While Caret is primarily a GUI application with 'caret_command' there is also a versatile command line tool, that allows access to a substantial proportion of Caret's functionality.

Caret can download and use stereotaxic atlases (human, monkey, mouse and rat) from an open online database.

Some functionality of Caret is only available when additional data files, provided by the caret-data package, are available. This includes:

  • Map volumes to surface via PALS atlas
  • Multi-resolution morphing
  • Projection of foci via PALS atlas
  • Surface-based registration
  • Surface flattening

Currently the caret-data package is only available from the NeuroDebian repository. Please see http://neuro.debian.net for more information.

Please cite: David C. Van Essen, Heather A. Drury, James Dickson, John Harwell, Donna Hanlon and Charles H. Anderson: An Integrated Software Suite for Surface-based Analyses of Cerebral Cortex. (PubMed,eprint) Journal of American Medical Informatics Association 8(5):443-459 (2001)
Dicom3tools
DICOM medical image files manipulation and conversion tools
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Command line utilities for creating, modifying, dumping and validating files of DICOM attributes. Support conversion of some proprietary medical image formats to DICOM. Can handle older ACR/NEMA format data, and some proprietary versions of that such as SPI.

Dicomnifti
converts DICOM files into the NIfTI format
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The dinifti program converts MRI images stored in DICOM format to NIfTI format. The NIfTI format is thought to be the new standard image format for medical imaging and can be used with for example with FSL, AFNI, SPM, Caret or Freesurfer.

dinifti converts single files, but also supports fully automatic batch conversions of complete dicomdirs. Additionally, converted NIfTI files can be properly named, using image series information from the DICOM files.

Fslview
viewer for (f)MRI and DTI data
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This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data.

FSLView is part of FSL.

Please cite: S.M. Smith, M. Jenkinson, M.W. Woolrich, C.F. Beckmann, T.E.J. Behrens, H. Johansen-Berg, P.R. Bannister, M. De Luca, I. Drobnjak, D.E. Flitney, R. Niazy, J. Saunders, J. Vickers, Y. Zhang, N. De Stefano, J.M. Brady and P.M. Matthews: Advances in functional and structural MR image analysis and implementation as FSL. (PubMed) NeuroImage 23:208-219 (2004)
Itksnap
semi-automatic segmentation of structures in 3D images
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SNAP provides semi-automatic segmentation of structures in medical images (e.g. magnetic resonance images of the brain) using active contour methods, as well as manual delineation and image navigation. Noteworthy features are:

  • Linked cursor for seamless 3D navigation
  • Manual segmentation in three orthogonal planes at once
  • Support for many different 3D image formats, including NIfTI
  • Support for concurrent, linked viewing and segmentation of multiple images
  • Limited support for color images (e.g., diffusion tensor maps)
  • 3D cut-plane tool for fast post-processing of segmentation results
Please cite: Paul A. Yushkevich, Joseph Piven, Heather Cody Hazlett, Rachel Gimpel Smith, Sean Ho, James C. Gee and Guido Gerig: User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability. Neuroimage 31:1116-1128 (2006)
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Lipsia
analysis suite for MRI and fMRI data
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Leipzig Image Processing and Statistical Inference Algorithms (LIPSIA)

This is a software package for the data processing and evaluation of functional magnetic resonance images. The analysis of fMRI data comprises various aspects including filtering, spatial transformation, statistical evaluation as well as segmentation and visualization. All these aspects are covered by LIPSIA. For the statistical evaluation, a number of well established and peer-reviewed algorithms were implemented in LIPSIA that allow an efficient and user-friendly processing of fMRI data sets. As the amount of data that must be handled is enormous, an important aspect in the development of LIPSIA was the efficiency of the software implementation.

LIPSIA operates exclusively on data in the VISTA data format. However, the package contains converters for medical image data in iBruker, ANALYZE and NIfTI format -- converting VISTA images into NIfTI files is also supported.

Please cite: Gabriele Lohmann, Karsten Müller, Volker Bosch, Heiko Mentzel, Sven Hessler, Lin Chen, S. Zysset, D. Yves von Cramon: Lipsia—a new software system for the evaluation of functional magnetic resonance images of the human brain. (2001)
Medcon
Medical Image (DICOM, ECAT, ...) conversion tool
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This project stands for Medical Image Conversion. Released under the (L)GPL, it comes with the full C-source code of the library, a flexible command line utility and a neat graphical front-end using the GTK+ toolkit. The currently supported formats are: Acr/Nema 2.0, Analyze (SPM), DICOM 3.0, InterFile 3.3 and PNG.

The program also allows one to read unsupported files without compression, to print pixel values or to extract/reorder specified images. It is possible to retrieve the raw binary/ascii image arrays or to write PNG for desktop applications.

This is the command line tool for batch processing.

Minc-tools
MNI medical image format tools
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This package contains tools to manipulate MINC files.

The Minc file format is a highly flexible medical image file format built on top of the NetCDF generalized data format. The format is simple, self-describing, extensible, portable and N-dimensional, with programming interfaces for both low-level data access and high-level volume manipulation. On top of the libraries is a suite of generic image-file manipulation tools. The format, libraries and tools are designed for use in a medical-imaging research environment: they are simple and powerful and make no attempt to provide a pretty interface to users.

Mriconvert
medical image file conversion utility
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MRIConvert is a medical image file conversion utility that converts DICOM files to NIfTI 1.1, Analyze 7.5, SPM99/Analyze, BrainVoyager, and MetaImage volume formats.

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Mricron
magnetic resonance image conversion, viewing and analysis
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This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change).

In addition to 'mricron', this package also provides 'dcm2nii' that supports converting DICOM and PAR/REC images into the NIfTI format, and 'npm' for non-parametric data analysis.

Please cite: Chris Rorden, Hans-Otto Karnath, Leonardo Bonilha: Improving lesion-symptom mapping. (2007)
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Nifti-bin
tools shipped with the NIfTI library
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Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images.

This package provides the tools that are shipped with the library (nifti_tool, nifti_stats and nifti1_test).

Nifti2dicom
convert 3D medical images to DICOM 2D series
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Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS.

This package includes the command line tools.

Openmeeg-tools
openmeeg library -- command line tools
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OpenMEEG consists of state-of-the art solvers for forward problems in the field of MEG and EEG. Solvers are based on the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. OpenMEEG can compute four types of lead fields (EEG, MEG, Internal Potential and Electrical Impedence Tomography).

This package provides command line interface to openmeeg functionality.

Please cite: Alexandre Gramfort, Théodore Papadopoulo, Emmanuel Olivi and Maureen Clerc: OpenMEEG: opensource software for quasistatic bioelectromagnetics. (PubMed,eprint) BioMedical Engineering OnLine 9:45 (2010)
Openwalnut-qt4
Multi-modal medical and brain data visualization tool.
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OpenWalnut is a tool for multi-modal medical and brain data visualization. Its universality allows it to be easily extended and used in a large variety of application cases. It is both, a tool for the scientific user and a powerful framework for the visualization researcher. Besides others, it is able to load NIfTI data, VTK line data and RIFF-format CNT/AVR-files. OpenWalnut provides many standard visualization tools like line integral convolution (LIC), isosurface-extraction, glyph-rendering or interactive fiber-data exploration. The powerful framework of OpenWalnut allows researchers and power-users to easily extend the functionality to their specific needs.

This package contains the QT4 GUI for OpenWalnut.

Praat
program for speech analysis and synthesis
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According to its authors, praat is "doing phonetics by computer". Through its graphical interface, several speech analysis functionalities are available: spectrograms, cochleograms, and pitch and formant extraction. Articulatory synthesis, as well as synthesis from pitch, formant, and intensity are also available. Other features are segmentation, labelling using the phonetic alphabet, and computation of statistics. Praat is configurable and extensible through its own scripting language and has provisions for communicating with other programs.

Please cite: Paul Boersma: Praat, a system for doing phonetics by computer. Glot International 5(9/10):341-345 (2001)
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Psignifit
Fitting and testing hypotheses about psychometric functions
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Psignifit allows fitting of psychometric functions to datasets while maintaining full control over a large number of parameters. Data can either be read from text files or passed through a pipe.

Psignifit performs the calculation of confidence intervals as well as goodness-of-fit tests.

This is the command line version.

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Python-dicom
DICOM medical file reading and writing (Python 2)
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pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects.

pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files.

This package installs the module for Python 2.

Python-dipy
Python library for the analysis of diffusion MRI datasets
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DIPY is a software project for computational neuroanatomy. It focuses on diffusion magnetic resonance imaging (dMRI) analysis and tractography but also contains implementations of other computational imaging methods such as denoising and registration that are applicable to the greater medical imaging and image processing communities. Additionally, DIPY is an international project which brings together scientists across labs and countries to share their state-of-the-art code and expertise in the same codebase, accelerating scientific research in medical imaging.

Here are some of the highlights:

  • Reconstruction algorithms: CSD, DSI, GQI, DTI, DKI, QBI, SHORE and MAPMRI
  • Fiber tracking algorithms: deterministic and probabilistic
  • Native linear and nonlinear registration of images
  • Fast operations on streamlines (selection, resampling, registration)
  • Tractography segmentation and clustering
  • Many image operations, e.g., reslicing or denoising with NLMEANS
  • Estimation of distances/correspondences between streamlines and connectivity matrices
  • Interactive visualization of streamlines in the space of images
Please cite: Eleftherios Garyfallidis, Matthew Brett, Vassilis Tsiaras, George Vogiatzis and Ian Nimmo-Smith: Identification of corresponding tracks in diffusion MRI tractographies. (eprint) Proc. Intl. Soc. Mag. Reson. Med. 18 (2010)
Python-mvpa2
multivariate pattern analysis with Python v. 2
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PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun).

While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets.

This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package.

The package is enhanced by the following packages: python-mdp python-sklearn
Python-nibabel
Python bindings to various neuroimaging data formats
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NiBabel provides read and write access to some common medical and neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI, NIfTI1, MINC, as well as PAR/REC. The various image format classes give full or selective access to header (meta) information and access to the image data is made available via NumPy arrays. NiBabel is the successor of PyNIfTI.

This package also provides a commandline tools:

  • dicomfs - FUSE filesystem on top of a directory with DICOMs
  • nib-ls - 'ls' for neuroimaging files
  • parrec2nii - for conversion of PAR/REC to NIfTI images
Python-nipy
Analysis of structural and functional neuroimaging data
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NiPy is a Python-based framework for the analysis of structural and functional neuroimaging data. It provides functionality for

  • General linear model (GLM) statistical analysis
  • Combined slice time correction and motion correction
  • General image registration routines with flexible cost functions, optimizers and re-sampling schemes
  • Image segmentation
  • Basic visualization of results in 2D and 3D
  • Basic time series diagnostics
  • Clustering and activation pattern analysis across subjects
  • Reproducibility analysis for group studies
Python-nipype
Neuroimaging data analysis pipelines in Python
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Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia).

Please cite: SS Ghosh, C Burns, D Clark, K Gorgolewski, YO Halchenko, C Madison, R Tungaraza and KJ Millman: Nipype: Opensource platform for unified and replicable interaction with existing neuroimaging tools (eprint) 16th Annual Meeting of the Organization for Human Brain Mapping :106 (2010)
Python-nitime
timeseries analysis for neuroscience data (nitime)
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Nitime is a Python module for time-series analysis of data from neuroscience experiments. It contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code.

Python-pyepl
module for coding psychology experiments in Python
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PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments.

It provides

  • presentation: both visual and auditory stimuli
  • responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped
  • sync-pulsing: synchronizing your behavioral task with external acquisition hardware
  • flexibility of encoding various experiments due to the use of Python as a description language
  • fast execution of critical points due to the calls to linked compiled libraries

This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime)

This package provides PyEPL for supported versions of Python.

The package is enhanced by the following packages: python-pyoptical
Please cite: Aaron S. Geller, Ian K. Schleifer, Per B. Sederberg, Joshua Jacobs, Michael J. Kahana: PyEPL: A cross-platform experiment-programming library. (2007)
Python-pypsignifit
psychometric analysis of psychophysics data in Python
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Psignifit allows fitting of psychometric functions to datasets while maintaining full control over a large number of parameters. Psignifit performs the calculation of confidence intervals as well as goodness-of-fit tests. In addition it offers:

  • full Bayesian treatment of psychometric functions including Bayesian model selection and goodness of fit assessment
  • identification of influential observations and outlier detection
  • flexible shape definition of the psychometric function

This package provides the Python bindings.

Python-pyxnat
Interface to access neuroimaging data on XNAT servers
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pyxnat is a simple 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. It features:

  • resources browsing capabilities
  • read and write access to resources
  • complex searches
  • disk-caching of requested files and resources
Python-statsmodels
Python module for the estimation of statistical models
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statsmodels Python module provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for six distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem.

Qnifti2dicom
convert 3D medical images to DICOM 2D series (gui)
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Nifti2Dicom is a convertion tool that converts 3D NIfTI files (and other formats supported by ITK, including Analyze, MetaImage Nrrd and VTK) to DICOM. Unlike other conversion tools, it can import a DICOM file that is used to import the patient and study DICOM tags, and allows you to edit the accession number and other DICOM tags, in order to create a valid DICOM that can be imported in a PACS.

This package contains the Qt4 GUI.

Slicer
software package for visualization and image analysis - main application
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Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks.

3D Slicer main application.

Please cite: Steven Pieper, Michael Halle, Ron Kikinis: 3D SLICER. (2004)
Voxbo
processing, statistical analysis, and display of brain imaging data
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This is a toolkit for analysis of functional neuroimaging (chiefly fMRI) experiments and voxel-based lesion-behavior mapping. VoxBo supports the modified GLM (for autocorrelated data), as well as the standard GLM for non-autocorrelated data. The toolkit is designed to be interoperable with AFNI, FSL, SPM and others.

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Xmedcon
Medical Image (DICOM, ECAT, ...) conversion tool (GUI)
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This project stands for Medical Image Conversion. Released under the (L)GPL, it comes with the full C-source code of the library, a flexible command line utility and a neat graphical front-end using the GTK+ toolkit. The currently supported formats are: Acr/Nema 2.0, Analyze (SPM), DICOM 3.0, InterFile 3.3 and PNG.

The program also allows one to read unsupported files without compression, to print pixel values or to extract/reorder specified images. It is possible to retrieve the raw binary/ascii image arrays or to write PNG for desktop applications.

This is the program version for X based on GTK+. Processes only one file at a time.

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Official Debian packages with lower relevance

Connectomeviewer
Interactive Analysis and Visualization for MR Connectomics
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The Connectome Viewer is a extensible, scriptable, pythonic research environment for visualization and (network) analysis in neuroimaging and connectomics.

Employing the Connectome File Format, diverse data types such as networks, surfaces, volumes, tracks and metadata are handled and integrated. The Connectome Viewer is part of the MR Connectome Toolkit.

Please cite: Gerhard S, Daducci A, Lemkaddem A, Meuli R, Thiran J-P and Hagmann P: The Connectome Viewer Toolkit: An open source framework to manage, analyze, and visualize connectomes. (2011)
Science-psychophysics
Debian Science packages for Psychophysics
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This metapackage will install Debian packages which might be useful for carrying out any experiment relating physical stimuli and their psychological effects.

The selection of packages is targeting software for stimuli delivery. For additional software related to the analysis of the acquired data refer to science-neuroscience-cognitive, med-imaging depending on the domain of application. Additionally look into science-bci since those often provide a complete loop frameworks including stimuli delivery.

Science-typesetting
Debian Science typesetting packages
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This metapackage will install Debian Science packages related to typesetting. You might also be interested in the use::typesetting debtag.

Debian packages in contrib or non-free

Fsl
transitional dummy package
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The only purpose of this package is to enable upgrades to the new 'fsl-core' package which replaces 'fsl'. This package can safely be removed.

Users aiming to perform a complete FSL installation (including all data components) are advised to install the 'fsl-complete' package from NeuroDebian.

Please cite: Mark Jenkinson, Christian F. Beckmann, Timothy E. J. Behrens, Mark W. Woolrich and Stephen M. Smith: FSL. (PubMed) NeuroImage 62(2):782-790 (2012)

Packaging has started and developers might try the packaging code in VCS

Afni - wnpp
toolkit for analyzing and visualizing functional MRI data
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AFNI is an environment for processing and displaying functional MRI data. It provides a complete analysis toolchain, including 3D cortical surface models, and mapping of volumetric data (SUMA).

In addition to its own format, AFNI understands the NIfTI format and is therefore integrates easily with FSL and FreeSurfer.

Please cite: Robert W. Cox: AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. (PubMed,eprint) Computers and Biomedical Research 29(3):162-73. (1996)
Bioimagesuite
integrated image analysis software suite
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BioImage Suite has extensive capabilities for both neuro/cardiac and abdominal image analysis and state of the art visualization. Many packages are available that are highly 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. It can be integrated with other biomedical image processing software, such as FSL and SPM. This site provides information, downloads, documentation, and other resources for users of the software.

BioImage Suite was developed at Yale University and has been extensively used at different labs at Yale since 2004.

Please cite: X. Papademetris, M. Jackowski, N. Rajeevan, R. T. Constable and L. Staib: BioImage Suite: An integrated medical image analysis suite. (eprint) Insight Journal (2005)
Remark of Debian Science team: How to work together with upstream

There is a forum at BioImage Suite site for discussion of compiling it from source and packaging issues at http://research.yale.edu/bioimagesuite/forum/index.php?board=12.0

Debruijn
De Bruijn cycle generator
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Stimulus counter-balance is important for many experimental designs. This command-line software creates De Bruijn cycles, which are pseudo-random sequences with arbitrary levels of counterbalance. "Path-guided" de Bruijn cycles may also be created. These sequences encode a hypothesized neural modulation at specified temporal frequencies, and have enhanced detection power for BOLD fMRI experiments.

Please cite: Geoffrey Karl Aguirre, Marcelo Gomes Mattar and Lucía Magis-Weinberg: de Bruijn cycles for neural decoding. (PubMed,eprint) NeuroImage 56(3):1293-1300 (2011)
Freesurfer
analysis and visualization of functional brain imaging data
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FreeSurfer is a set of tools for analysis and visualization of structural and functional brain imaging data. It contains a fully automatic structural stream for processing cross sectional and longitudinal data.

FreeSurfer provides many anatomical analysis tools, including: representation of the cortical surface between white and gray matter, representation of the pial surface, segmentation of white matter from the rest of the brain, skull stripping, B1 bias field correction, nonlinear registration of the cortical surface of an individual with an sterotaxic atlas, labeling of regions of the cortical surface, statistical analysis of group morphometry differences, and labeling of subcortical brain structures, etc.

This package depends upon the latest version of freesurfer.

Please cite: A. M. Dale, B. Fischl and M. I. Sereno: Cortical surface-based analysis. I. Segmentation and surface reconstruction. (PubMed) Neuroimage 9(2):179-94 (1999)
Remark of Debian Science team: The 'tktools' (tkmedit, tksurfer and tkregister2) under the
 CorTechs license are not readily redistributable thus excluded.

Unofficial packages built by somebody else

Eeglab
toolbox for processing and visualization of electrophysiological data
Responsible: NeuroDebian Team
License: GPL-2+
Language: C, Matlab/Octave

EEGLAB is an interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data.

Please register by following this link if you are using eeglab.
Please cite: Delorme A and Makeig S: EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics (2004)
Mni-autoreg
MNI average brain (305 MRI) stereotaxic registration model
Responsible: Michael Hanke
License: no-free, but GPLed parts

This package provides a version of the MNI Average Brain (an average of 305 T1-weighted MRI scans, linearly transformed to Talairach space) specially adapted for use with the MNI Linear Registration Package.

  • average_305.mnc - a version of the average MRI that covers the whole brain (unlike the original Talairach atlas), sampled with 1mm cubic voxels
  • average_305_mask.mnc - a mask of the brain in average_305.mnc
  • average_305_headmask.mnc - another mask, required for nonlinear mode

Remark: Michael Hanke agreed to take over his stuff from mentors http://mentors.debian.net/cgi-bin/sponsor-pkglist?action=details;package=mni-autoreg and http://mentors.debian.net/cgi-bin/sponsor-pkglist?action=details;package=mni-autoreg-model to Debian Med svn and start group maintenance.

Mni-n3
MNI Non-parametric Non-uniformity Normalization
Responsible: Michael Hanke
License: BSDish

MNI Non-parametric Non-uniformity Normalization (N3). This package provides the 'nu_correct' tool for unsupervised correction of radio frequency (RF) field inhomogenities in MR volumes. Two packages are provided:

  • mni-n3 - provides 'nu_correct'
  • libebtks-dev - MNI support library with numerical types and algorithms

Remark: Michael Hanke agreed to take over his stuff from mentors http://mentors.debian.net/cgi-bin/sponsor-pkglist?action=details;package=mni-n3 to Debian Med svn and start group maintenance.

No known packages available but some record of interest (WNPP bug)

Fieldtrip - wnpp
toolbox for MEG and EEG analysis
License: GPL-2+
Debian package not available
Language: Matlab/Octave

The software includes algorithms for simple and advanced analysis of MEG and EEG data, such as time-frequency analysis, source reconstruction using dipoles, distributed sources and beamformers and non-parametric statistical testing. It supports the data formats of all major MEG systems (CTF, Neuromag, BTi) and of the most popular EEG systems, and new formats can be added easily. FieldTrip contains high-level functions that you can use to construct your own analysis protocols in Matlab. Furthermore, it easily allows developers to incorporate low-level algorithms for new EEG/MEG analysis methods.

Remark of Debian Science team: The NIMH distributes a "port" of fieldtrip to Octave (at

http://kurage.nimh.nih.gov/meglab/Meg/Software). It needs to be figured out whether this port can be incorporated into the official version, and to what degree it is complete. Packaging fieldtrip is required to complete the packaging of SPM8.

Pysurfer - wnpp
visualize Freesurfer's data in Python
Responsible: NeuroDebian Team
License: BSD-3
Debian package not available
Language: Python

This is a Python package for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi’s powerful visualization engine with a high-level interface for working with MRI and MEG data.

PySurfer offers both a command-line interface designed to broadly replicate Freesurfer’s Tksurfer program as well as a Python library for writing scripts to efficiently explore complex datasets.

Spm8 - wnpp
analysis of brain imaging data sequences
Responsible: NeuroDebian team
License: GPL-2+
Debian package not available

Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG.

Please register by following this link if you are using spm8.
Please cite: Karl J. Friston, John T. Ashburner, Stephen Kiebel, Thomas E. Nichols and William D. Penny: Statistical Parametric Mapping: The Analysis of Functional Brain Images.. (2007)
Remark of Debian Science team: This software is written for matlab, but initial tests indicate that

some (significant) portion of it might also work with octave. More tests are pending...

Xnat - wnpp
platform for data management and productivity tasks in neuroimaging
License: XNAT SLA
Debian package not available
Language: java

The primary functionality of XNAT is to provide a place to store and control access to neuroimaging data. This includes sophisticated user control, search and retrieval, and archiving capabilities. As open-source software, XNAT also supports a wide variety of research-based processing pipelines, and is able to link up with supercomputer processing power to dramatically shorten image processing time.

Please register by following this link if you are using xnat.
Please cite: Marcus, D.S., Olsen T., Ramaratnam M., and Buckner, R.L.: The Extensible Neuroimaging Archive Toolkit (XNAT): An informatics platform for managing, exploring, and sharing neuroimaging data. (2007)

No known packages available

Brainvisa
image processing factory for MR images
License: Free? (CeCill License)
Debian package not available

BrainVISA is a software, which embodies an image processing factory. A simple control panel allows the user to trigger some sequences of treatments on series of images. These treatments are performed by calls to command lines provided by different laboratories. These command lines, hence, are the building blocks on which are built the assembly lines of the factory. BrainVISA is distributed with a toolbox of building blocks dedicated to the segmentation of T1-weighted MR images. The product of the main assembly line made up from this toolbox is the following: grey/white classification for Voxel Based Morphometry, Meshes of each hemisphere surface for visualization purpose, Spherical meshes of each hemisphere white matter surface, a graph of the cortical folds, a labeling of the cortical folds according to a nomenclature of the main sulci.

Hid
database management system for clinical imaging
License: BSD, BIRN
Debian package not available
Language: java

The Human Imaging Database (HID) is an extensible database management system developed to handle the increasingly large and diverse datasets collected as part of the MBIRN and FBIRN collaboratories and throughout clinical imaging communities at large.

Please register by following this link if you are using hid.
Please cite: Keator, D.B.; Grethe, J.S.; Marcus, D.; Ozyurt, B.; Gadde, S.; Murphy, S.; Pieper, S.; Greve, D.;Notestine, R.; Bockholt, H.J.; Papadopoulos, P.: A National Human Neuroimaging Collaboratory Enabled By The Biomedical Informatics Research Network (BIRN) (2008)
Iqr
large-scale multi-level neuronal systems simulator
Responsible: NeuroDebian team
License: GPL-3+
Debian package not available

This graphical environment allows for designing large-scale multi-level neuronal systems that can control real-world devices, such as cameras and mobile robots, in real-time. iqr is an extensible framework with the ability to handle new, user-provided, neuron and synapse types, as well as custom interfaces to other hardware systems. iqr employes an XML-based format for system descriptions.

Please cite: Ulysses Bernardet, Paul F.M.J. Verschure: iqr: A tool for the construction of multi-level simulations of brain and behaviour.. (2010)
*Popularitycontest results: number of people who use this package regularly (number of people who upgraded this package recently) out of 200581