Package: ants Version: 1.9.2+svn680.dfsg-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 38588 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libinsighttoolkit3.18, libstdc++6 (>= 4.4.0) Suggests: fsl, gridengine-client Homepage: http://www.picsl.upenn.edu/ANTS/ Priority: extra Section: science Filename: pool/main/a/ants/ants_1.9.2+svn680.dfsg-1~nd+1_amd64.deb Size: 11489378 SHA256: 04bf6bcd6e4086fe1b677c11a1a6faacfd44aff2a25e4c164c86e589da9dbf3f SHA1: e1a3c31c88a4c486517224d74d741c0d6b7f0c8c MD5sum: d74a87fe90bcd30e081a421a362c3020 Description: advanced normalization tools for brain and image analysis Advanced Normalization Tools (ANTS) is an ITK-based suite of normalization, segmentation and template-building tools for quantitative morphometric analysis. 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). Package: arno-iptables-firewall Version: 1.9.2.k-3~sid.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 844 Depends: iptables (>= 1.2.11), gawk, debconf (>= 1.3.22) | cdebconf (>= 0.43), debconf (>= 0.5) | debconf-2.0, iproute Recommends: lynx, dnsutils Homepage: http://rocky.eld.leidenuniv.nl/ Priority: optional Section: net Filename: pool/main/a/arno-iptables-firewall/arno-iptables-firewall_1.9.2.k-3~sid.nd1_all.deb Size: 132466 SHA256: f27127b8c1dc917c0286a9387f8fa457376ded10b07a5908485636c27a2a14ff SHA1: 696de58c79bec6fd3efa3cf7dbbeecaa18d1ea8e MD5sum: da7a5641d17921fad83cbb534f2ebb22 Description: single- and multi-homed firewall script with DSL/ADSL support Unlike other lean iptables frontends in Debian, arno-iptables-firewall will setup and load a secure, restrictive firewall by just asking a few question. This includes configuring internal networks for internet access via NAT and potential network services (e.g. http or ssh). . However, it is in no way restricted to this simple setup. Some catch words of additional features, that can be enabled in the well documented configuration file are: DSL/ADSL, Port forwarding, DMZ's, portscan detection, MAC address filtering. Package: biosig-tools Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 656 Depends: libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/biosig-tools_0.94.2+svn2552-1~pre1~nd+1_amd64.deb Size: 252988 SHA256: 5f7badd9121560f7eddc72cd2ab31fbe3b3a25df204583eabd91fbe2821f3097 SHA1: 2c82c269d1137b2f3369b8a9b0cc3dcc7977f42a MD5sum: 33a8bb49e17c96ca6cd403574650d36d Description: format conversion tools for biomedical data formats Based on BioSig library, this package provides command line tools, such as * save2gdf: converter between different file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF, BDF, CWFB. save2gdf can be also used to upload or retrieve data from a bscs server. TODO... Extend? ship client/server? Package: caret-data Version: 5.6~dfsg.1-1 Architecture: all Maintainer: Michael Hanke Installed-Size: 236780 Homepage: http://brainmap.wustl.edu/caret Priority: optional Section: science Filename: pool/main/c/caret-data/caret-data_5.6~dfsg.1-1_all.deb Size: 175205418 MD5sum: e5f41497554088124975dfc27ba6378b Description: common data files for Caret This package provides online help, tutorials and atlas datasets for Caret. Package: cython Version: 0.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4924 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python2.6, libc6 (>= 2.3) Suggests: gcc Homepage: http://cython.org/ Priority: optional Section: python Filename: pool/main/c/cython/cython_0.13-1~nd+1_amd64.deb Size: 1331846 SHA256: 340cb1e470f0ab638c1749452199ae2f2516fac9a8152e5c5c8c15124e2fd662 SHA1: a348afb03c532dea466aab9a642a95188e3e222d MD5sum: 8dfc10b6cf44d65866b45a1880d617e1 Description: C-Extensions for Python Cython is a language that makes writing C extensions for the Python language as easy as Python itself. Cython is based on the well-known Pyrex, but supports more cutting edge functionality and optimizations. . The Cython language is very close to the Python language, but Cython additionally supports calling C functions and declaring C types on variables and class attributes. This allows the compiler to generate very efficient C code from Cython code. . This makes Cython the ideal language for wrapping for external C libraries, and for fast C modules that speed up the execution of Python code. Python-Version: 2.5, 2.6 Package: cython-dbg Source: cython Version: 0.13-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10552 Depends: python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), libc6 (>= 2.3), cython (= 0.13-1~nd+1) Suggests: gcc Homepage: http://cython.org/ Priority: extra Section: debug Filename: pool/main/c/cython/cython-dbg_0.13-1~nd+1_amd64.deb Size: 3422252 SHA256: 3a8617e19420cda0a3d5f6c4d52e5d4503fa1d1606355ddb7f9f8b2140fc2548 SHA1: 995dcdf86f109c46c013af8da69b15a78b6a7faf MD5sum: 6ddc22d8e8982d79f4c6d9df3fde309a Description: C-Extensions for Python (Debug Build of Cython) This package contains Cython libraries built against versions of Python configured with --pydebug. Python-Version: 2.5, 2.6 Package: gdf-tools Source: libgdf Version: 0.1.0~svn31-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 156 Depends: libboost-filesystem1.42.0 (>= 1.42.0-1), libboost-program-options1.42.0 (>= 1.42.0-1), libboost-system1.42.0 (>= 1.42.0-1), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: utils Filename: pool/main/libg/libgdf/gdf-tools_0.1.0~svn31-1~nd+1_amd64.deb Size: 38738 SHA256: d9461ada68b55570d32f3742fb1594da32fb36d2b04f22cac77b3d8ad9464da6 SHA1: 7724993a3a67a65b4dbbab3deb4afff87f07fe1a MD5sum: a9a215d4771144b004f33c078135371e Description: IO library for the GDF -- helper tools GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the tool shipped with the library (gdf_merger). Package: itksnap Version: 2.1.4-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 8652 Depends: libc6 (>= 2.2.5), libfltk1.1 (>= 1.1.8~rc1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libinsighttoolkit3.18, libstdc++6 (>= 4.4.0), libvtk5.4 Homepage: http://www.itksnap.org Priority: extra Section: science Filename: pool/main/i/itksnap/itksnap_2.1.4-1~nd+1_amd64.deb Size: 3707206 SHA256: a5235e27b947aa260b096b3b82285b952f7f35e8c8d958c3a79b8c088f28a58d SHA1: 9bcc48493198a6ad51d718cedf479313fa4ee623 MD5sum: 5cd6e353618e15542bf48e3fa86b4663 Description: semi-automatic segmentation of structures in 3D images 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 Package: libbiosig-dev Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1612 Depends: libbiosig0 (= 0.94.2+svn2552-1~pre1~nd+1) Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.94.2+svn2552-1~pre1~nd+1_amd64.deb Size: 379236 SHA256: a665a5bffeb961942abc2518740d909e8e592e1736cb1a500dac23647d8aeaa4 SHA1: bee2618edd742effb4ee6f2fdad32fb02825be18 MD5sum: 176ffc6caba0fbe1cae4cfac54b7a85d Description: I/O library for biomedical data - development files BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://hci.tugraz.at/schloegl/biosig/TESTED . . This package provides header files and static library. Package: libbiosig0 Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 888 Depends: libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: libs Filename: pool/main/b/biosig4c++/libbiosig0_0.94.2+svn2552-1~pre1~nd+1_amd64.deb Size: 302784 SHA256: 57d7d418db3653ca09682b35be21af90975f48cb25afc466133815f097e85c51 SHA1: 08d26dcd7091dd7e4ab2c7e2e7d7284ebd3ec8b5 MD5sum: 13e05b4b127db507b8b723cf25c63185 Description: I/O library for biomedical data - dynamic library BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://hci.tugraz.at/schloegl/biosig/TESTED . . This package provides dynamic library. Package: libbiosig0-dbg Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 712 Depends: libbiosig0 (= 0.94.2+svn2552-1~pre1~nd+1) Homepage: http://biosig.sf.net/ Priority: extra Section: debug Filename: pool/main/b/biosig4c++/libbiosig0-dbg_0.94.2+svn2552-1~pre1~nd+1_amd64.deb Size: 171850 SHA256: 07de31c3e4cfd4eea206acaae5a87c2ce1f054a4368aba0656cbac646b219f78 SHA1: cab06bda102c936f43eb512bf6c84ef56edda6fb MD5sum: 1142ba816c57d618b673d1847fde8715 Description: I/O library for biomedical data - debug symbols BioSig is a library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://hci.tugraz.at/schloegl/biosig/TESTED . . This package provides debug symbols. Package: libgdf-dev Source: libgdf Version: 0.1.0~svn31-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 164 Depends: libgdf0 (= 0.1.0~svn31-1~nd+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libdevel Filename: pool/main/libg/libgdf/libgdf-dev_0.1.0~svn31-1~nd+1_amd64.deb Size: 17216 SHA256: e20ce0ea93944b1e428a698a8283dc8ab4de8ece7284b81ed483a50ec5a95aab SHA1: 20e7965c57e31cdb47306f55c308106261d2db3f MD5sum: 9f5124168f5c9464911734134ae971a6 Description: IO library for the GDF -- development library GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides the header files and static library. Package: libgdf0 Source: libgdf Version: 0.1.0~svn31-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 356 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: libs Filename: pool/main/libg/libgdf/libgdf0_0.1.0~svn31-1~nd+1_amd64.deb Size: 101630 SHA256: c00dd5ef6448eb182c34ad0535ed2d86e3c296a32fafa6df3fe20c685ca03978 SHA1: 79b9c1924966e8465c4df7f34594a9f068000c9f MD5sum: c100b075caeba98543ca73bb2443c52a Description: IO library for the GDF (general dataformat for biosignals) GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package contains the shared library. Package: libgdf0-dbg Source: libgdf Version: 0.1.0~svn31-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4040 Depends: libgdf0 (= 0.1.0~svn31-1~nd+1) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: debug Filename: pool/main/libg/libgdf/libgdf0-dbg_0.1.0~svn31-1~nd+1_amd64.deb Size: 1073680 SHA256: 77508794bac631166785098d3625a05cc3d8ee19911cbe879f9523b8bd2e6382 SHA1: 640999a3d8da9fa14c7d5908c6f026559e0109ad MD5sum: 4569de3f93c36b1c04ca299b99f647a7 Description: IO library for the GDF -- debug symbols GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides debug symbols. Package: libjs-jquery Version: 1.2.6-1~apsy.0 Architecture: all Recommends: javascript-common Conflicts: jquery Replaces: jquery Installed-Size: 240 Maintainer: Debian Javascript Maintainers Source: jquery Priority: optional Section: web Filename: pool/main/j/jquery/libjs-jquery_1.2.6-1~apsy.0_all.deb Size: 65238 SHA256: fa858cf809b1885439cfb0d6e8ba64021a732b2e9b8493027f5d767973268d22 SHA1: 19177bbdd00962ac018ffa081149840aa7bbc469 MD5sum: 6dc346b0c5ffacbdf0e63f00d1f18485 Description: JavaScript library for dynamic web applications jQuery is a fast, concise, JavaScript Library that simplifies how you traverse HTML documents, handle events, perform animations, and add Ajax interactions to your web pages. jQuery is designed to change the way that you write JavaScript. Package: libodin-dev Source: odin Version: 1.8.1-2~sid.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 21016 Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.1-2~sid.nd1_amd64.deb Size: 4198702 SHA256: 7c95a47eff2385fd30f2f25a4a2eb96a311502434e9fa3359e1d8b325a018cc5 SHA1: 8421c56b808b02c555cfea79c7f9b10d3364aa27 MD5sum: ca84aa498b3cd88d7e207da7c7867927 Description: static libraries and header for ODIN sequences This package provides static libraries and headers of the ODIN libraries odindata, adinpara, odinqt, odinseq and tjutils. They are required for building magnetic resonance imaging (MRI) sequences with ODIN. Package: matlab-dev Source: matlab Version: 0.0.12~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 44 Depends: neurodebian-popularity-contest Priority: optional Section: devel Filename: pool/main/m/matlab/matlab-dev_0.0.12~nd+1_all.deb Size: 3210 SHA256: 49cef13970e9a6a528d168c6771894c83dfd7e6445a7b1593d6edf4cc837f3d5 SHA1: df41bb316cdecac652327921732644a07a2bb4f4 MD5sum: b8537d3d832981b80365f4f8d54b6191 Description: helpers for packages building Matlab toolboxes Analogous to Octave a Makefile snippet is provided that configures the locations for architecture independent M-files, binary MEX-extensions, and there corresponding sources. This package can be used as a build-dependency by other packages shipping Matlab toolboxes. Package: mitools Source: odin Version: 1.8.1-2~sid.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 7100 Depends: libblitz0ldbl (>= 0.9), libc6 (>= 2.3.2), libdcmtk1 (>= 3.5.4), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libnifti1 (>> 1.1.0-2), liboil0.3 (>= 0.3.10), libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.4.0), libvia0, libvtk5.4, zlib1g (>= 1:1.1.4), dcmtk Recommends: grace Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/mitools_1.8.1-2~sid.nd1_amd64.deb Size: 2438996 SHA256: 1490445744b92fd868bcdd708acc68d538591a1add3dab7d5a4c797674da7d3c SHA1: a866a3fc54472b2500da32e21a9346202f1469fc MD5sum: 3f726319ab05321791c9a27097508604 Description: view, convert and perform basic maths with medical image datasets The three contained tools micalc, miconv and miview are handy command-line utilities for converting, manipulating and viewing medical image data in various formats (DICOM, NIfTI, PNG, binary data, ...). Package: mricron Version: 0.20101102.1~dfsg.1-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 15624 Depends: libatk1.0-0 (>= 1.29.3), libc6 (>= 2.2.5), libcairo2 (>= 1.2.4), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.8.0), libpango1.0-0 (>= 1.14.0), libx11-6, mricron-data Suggests: mricron-doc Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20101102.1~dfsg.1-1~nd+1_amd64.deb Size: 4864922 SHA256: 86e21d89b5d4409c373b90ac5ae7e7c67685802b3bb67aa4d23c748e7e48b75a SHA1: d5bd8b1089f94769542728669c67ae50cf5b9ab1 MD5sum: d1e5a2cbcab35b38dd90da96379f07ed Description: magnetic resonance image conversion, viewing and analysis 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. Package: mricron-data Source: mricron Version: 0.20101102.1~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1852 Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20101102.1~dfsg.1-1~nd+1_all.deb Size: 1665748 SHA256: fbbd06044b00a09b0797feda9bb4f3dbe8efa305380d3dfd974b7df11920599d SHA1: fdecd28e935671338aa2c5104d2819475b1a0f4f MD5sum: 5c5053032ec6aa65ac35d4a5d7086a96 Description: data files for MRIcron 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). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20101102.1~dfsg.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1220 Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20101102.1~dfsg.1-1~nd+1_all.deb Size: 737360 SHA256: ebae0128cc36c8060fccb24609eb960d946a9de4ef3157f0e65d1eaf96aeef35 SHA1: 6d8c0a2054f62c790f8cbaa7c48ac1d70e74a888 MD5sum: d53ff217364a20faf63f6456a1b27751 Description: data files for MRIcron 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). . This package provides documentation for MRIcron in HTML format. Package: neurodebian-desktop Source: neurodebian Version: 0.21~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 332 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.21~nd+1_all.deb Size: 111304 SHA256: 976c9a6bc5cfbe9f4f3e950e1b4693da25f4fc9ee4bb90ef904bb32180b125f1 SHA1: dc4233c0d4ffff41ec86951ec9c24f1d37f18bf1 MD5sum: 0744c2961726d671fa7b7539dc3c1bee Description: neuroscience research environment This package contains NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring most popular neuroscience tools automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.21~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4328 Depends: devscripts, cowbuilder, python, neurodebian-keyring Recommends: virtualbox-ose, virtualbox-ose-fuse, zerofree Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.21~nd+1_all.deb Size: 3767282 SHA256: 3aed048534d702ea9bc423b751ef8ba5fab43856026d7b83d3f5e5cdf8accdaa SHA1: 3f1ae6dd57b49e556b4201b0467f8bd19157c421 MD5sum: dffabcea03087c6009c58ff3c50483f6 Description: NeuroDebian development tools neuro.debian.net sphinx website sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-guest-additions Source: neurodebian Version: 0.21~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 232 Pre-Depends: virtualbox-ose-guest-utils, virtualbox-ose-guest-x11, virtualbox-ose-guest-dkms Depends: sudo, neurodebian-desktop, gdm, update-manager-gnome, update-notifier Recommends: chromium-browser Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-guest-additions_0.21~nd+1_all.deb Size: 10214 SHA256: 2dd64bf6fd70d00b3b8b43baf9d415aa9de5a1f24f5cf8b7e4a138e42298c0c8 SHA1: 870f9332f755c4e0196606cd949171ed7fe18097 MD5sum: 20c123db135cb5183c2f751f55d3a11f Description: NeuroDebian guest additions (DO NOT INSTALL OUTSIDE VIRTUALBOX) This package configures a Debian installation as a guest operating system in a VirtualBox-based virtual machine for NeuroDebian. . DO NOT install this package unless you know what you are doing! For example, installation of this package relaxes several security mechanisms. Package: neurodebian-keyring Source: neurodebian Version: 0.21~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 56 Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-keyring_0.21~nd+1_all.deb Size: 4068 SHA256: 3ec996d4b9f4d0fc468634a505c1ca197496c13705422e3e17236bf3c3c38a9b SHA1: 753a1bc9352cee824671ab85f11724bf7fb6f9b1 MD5sum: bba95ad977b09de2f0d30604d8ef809c Description: GnuPG archive keys of the NeuroDebian archive The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.21~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.21~nd+1_all.deb Size: 3226 SHA256: ca974e2d36c91b927feaec7a16bee0e2a2003f69816909993893e5eb49a7f5a0 SHA1: 76100352bafee5f5f33581a20f1fc9eb30d93c5a MD5sum: 981b3eb54bf5cf1088d4e4d4f221e300 Description: Helper for NeuroDebian popularity contest submissions This package is a complement to a generic popularity-contest package to enable submission of usage statistics to NeuroDebian in addition to the submissions to the underlying distribution (e.g. Debian or Ubuntu) popcon server. . It has an effect only if you have decided to participate in the Popularity Contest. . Your participation in popcon is important for following reasons: - Popular packages receive more attention from developers, bugs are fixed faster and updates are provided quicker. - Assure that we do not drop support for a previous release of Debian or Ubuntu while are active users. - User statistics could be used by upstream research software developers to acquire funding for continued development. . You can always enable or disable your participation in popcon by running 'dpkg-reconfigure popularity-contest' as root. Package: octave-biosig Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1612 Depends: libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.3), libhdf5-serial-1.8.4 | libhdf5-1.8.4, liblapack3gf | liblapack.so.3gf | libatlas3gf-base, libncurses5 (>= 5.7+20100313), libreadline6 (>= 6.0), libstdc++6 (>= 4.2.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_0.94.2+svn2552-1~pre1~nd+1_amd64.deb Size: 591786 SHA256: a08849d3235b48df56398e08469139cb2d3918f2b3644375f962b017cd09de85 SHA1: 25e750cd72227396e0cdde8689986b67b9c07051 MD5sum: 2b5a943b2af6af706742a56f42be29aa Description: Octave bindings for BioSig library This package provides Octave bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: octave-gdf Source: libgdf Version: 0.1.0~svn31-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 384 Depends: octave3.2 (>= 3.2.4), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libgdf0, libstdc++6 (>= 4.4.0) Homepage: http://sourceforge.net/projects/libgdf Priority: extra Section: science Filename: pool/main/libg/libgdf/octave-gdf_0.1.0~svn31-1~nd+1_amd64.deb Size: 130784 SHA256: 5a75c356a6302d3f754cafb80dcf3ac7af121653efb6d6e7e6f610e3f055613d SHA1: 91756625598d37c5533a7c545e04a425fe9833c2 MD5sum: 8f35369d1ad13bbfb7970d18e3d9e3b8 Description: IO library for the GDF -- Octave interface GDF (General Dataformat for Biosignals) is intended to provide a generic storage for biosignals, such as EEG, ECG, MEG etc. . This package provides Octave bindings for libgdf. . HIGHLY EXPERIMENTAL -- USE AT YOUR OWN RISK. Package: odin Version: 1.8.1-2~sid.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 4124 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk5.4, mitools (= 1.8.1-2~sid.nd1), libodin-dev, libgsl0-dev, libc6-dev | libc-dev, g++, libblas-dev | libatlas-base-dev, xterm | x-terminal-emulator, gdb Recommends: liboil0.3-dev | liboil-dev, libdcmtk1-dev Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/odin_1.8.1-2~sid.nd1_amd64.deb Size: 1571906 SHA256: 4a0dc4cef73caf8d308df2f65815560bd1a922c3878915f65cd634893dc648ee SHA1: 56adeb26583834f6034cf12e028ea58d4f491796 MD5sum: dbee20ccd8b613879ac610cc048e7a9d Description: develop, simulate and run magnetic resonance sequences ODIN is a framework for magnetic resonance imaging (MRI). It covers the whole toolchain of MRI, from low-level data acquisition to image reconstruction. In particular, it aims at rapid prototyping of MRI sequences. The sequences can be programmed using a high-level, object oriented, C++ programming interface. It provides advanced sequence analysis tools, such as interactive plotting of k-space trajectories, a user interface for a fast compile-link-test cycle and a powerful MRI simulator which supports different virtual samples. For fast and flexible image reconstruction, ODIN contains a highly customizable, multi-threaded data-processing framework. Package: openelectrophy Version: 0.0.svn143-1~sid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 92 Depends: python, python-pyssdh (= 0.0.svn143-1~sid.nd1) Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: science Filename: pool/main/o/openelectrophy/openelectrophy_0.0.svn143-1~sid.nd1_all.deb Size: 34360 SHA256: 15e2e7aefc8b1af85c120f648897950db56fb71fe5999c5a3ca51b1c70bc0fb4 SHA1: 84e8c88b4d56f44c987808ba5c54b1799a0403ee MD5sum: 0eaf72ffeedd568782315315e95b4dfe Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy GUI. Package: psychopy Version: 1.63.00+git8-g46ee897.dfsg-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4344 Depends: neurodebian-popularity-contest, python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, python-scipy, libavbin0 Suggests: python-iolabs, python-pyepl Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.63.00+git8-g46ee897.dfsg-1~nd+1_all.deb Size: 2343970 SHA256: ab97d8a2b19f0de320137e2f5697582041cc984f2207edf572819b0e0842b24b SHA1: b17b19e323fbe640f5995b010123c5f2258f22ac MD5sum: 14223b6200332e97aef051ff934f8f08 Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features - High-level powerful scripting language (Python) - Simple syntax - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.5, 2.6 Package: python-biosig Source: biosig4c++ Version: 0.94.2+svn2552-1~pre1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1036 Depends: libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: python Filename: pool/main/b/biosig4c++/python-biosig_0.94.2+svn2552-1~pre1~nd+1_amd64.deb Size: 336484 SHA256: d16e46d429d49a85ea7d657a4800b9288e837bec4028cee3f89be63f3a0f838a SHA1: e4fdb1c6369ea5d55952069bd441fcf685549b96 MD5sum: 533e6d46ba4d62668ff1a35da7236396 Description: Python bindings for BioSig library This package provides Python bindings for BioSig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF. Package: python-brian Source: brian Version: 1.2.2~svn2229-1~pre1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1736 Depends: python (>= 2.6), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0), python-brian-lib (>= 1.2.2~svn2229-1~pre1~nd+1), python-matplotlib (>= 0.90.1), python-scipy (>= 0.7.0) Recommends: python-sympy Suggests: python-brian-doc, python-nose Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian_1.2.2~svn2229-1~pre1~nd+1_all.deb Size: 296628 SHA256: e608814a47785d3b62f5deac63a911f52423ddf1c6f392eba2f965e9d7592827 SHA1: ad5b21cdb83c99d9738585146522337f108ae7df MD5sum: 0bdc6a766e3a092468149a7faad25a72 Description: simulator for spiking neural networks Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include: - a system for specifying quantities with physical dimensions - exact numerical integration for linear differential equations - Euler, Runge-Kutta and exponential Euler integration for nonlinear differential equations - synaptic connections with delays - short-term and long-term plasticity (spike-timing dependent plasticity) - a library of standard model components, including integrate-and-fire equations, synapses and ionic currents - a toolbox for automatically fitting spiking neuron models to electrophysiological recordings Package: python-brian-doc Source: brian Version: 1.2.2~svn2229-1~pre1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4004 Depends: libjs-jquery Suggests: python-brian Homepage: http://www.briansimulator.org/ Priority: extra Section: doc Filename: pool/main/b/brian/python-brian-doc_1.2.2~svn2229-1~pre1~nd+1_all.deb Size: 860504 SHA256: 87886ed8fa1c0979869d7acbddf87e2838ad681c01b04acd0caec1f1b4e177be SHA1: 04d54f281eea05cba252a9c2be29c0991beb34f1 MD5sum: 7ff0300a28d9b66e3c95f6e3ef4777d9 Description: simulator for spiking neural networks - documentation Brian is a clock-driven simulator for spiking neural networks. . This package provides user's manual (in HTML and PDF formats), examples and demos. Package: python-brian-lib Source: brian Version: 1.2.2~svn2229-1~pre1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 216 Depends: python (<< 2.7), python (>= 2.6), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0), libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.4.0) Homepage: http://www.briansimulator.org/ Priority: extra Section: python Filename: pool/main/b/brian/python-brian-lib_1.2.2~svn2229-1~pre1~nd+1_amd64.deb Size: 53956 SHA256: daed9e56acb00a15bd6221e39e30a5f83894d6ccb698ec03d9672aa9ec0b6cd8 SHA1: e0963b116537eeac55a57354f7683f1542816d4f MD5sum: 4349f57462127dc3ebfcf22ed31cba0b Description: simulator for spiking neural networks -- extensions Brian is a clock-driven simulator for spiking neural networks. . This package provides Python binary extensions. Package: python-dicom Source: pydicom Version: 0.9.5~rc1-1~sid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1864 Depends: python (>= 2.5), python-support (>= 0.90.0) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://code.google.com/p/pydicom/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.5~rc1-1~sid.nd1_all.deb Size: 372936 SHA256: e3abd85463e1a311df3588f4ac4b582da1e712e6d0b14cf6a5f87a5d92247862 SHA1: af591e04e34defa29892d5c1398a11de56d08191 MD5sum: 5546527ef55fde4ae81bc8bd50cb1ee0 Description: DICOM medical file reading and writing 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. Package: python-griddata Source: griddata Version: 0.1.2-1~sid.apsy1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 264 Depends: libc6 (>= 2.7-1), python (<< 2.6), python (>= 2.4), python-support (>= 0.7.1), python-numpy, python-numpy-ext Recommends: python-matplotlib Provides: python2.4-griddata, python2.5-griddata Homepage: http://code.google.com/p/griddata-python/ Priority: optional Section: python Filename: pool/main/g/griddata/python-griddata_0.1.2-1~sid.apsy1_amd64.deb Size: 72084 SHA256: 17869327b4ac23591a2f5c0c64b6b5e3d774204b64e55c5c328d620b1792dbef SHA1: 53e5eb8db403feb625fa80c5ad05de6ecc49bc4b MD5sum: f165543d0b0f631f3243e5f9969a8f11 Description: Python function to interpolate irregularly spaced data to a grid This module provides a single function, 'griddata', that fits a surface to nonuniformly spaced data points. It behaves basically like its equivalent in Matlab. Python-Version: 2.4, 2.5 Package: python-joblib Source: joblib Version: 0.4.6-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 244 Depends: python, python-support (>= 0.90.0) Recommends: python-numpy, python-nose, python-simplejson Homepage: http://packages.python.org/joblib/ Priority: optional Section: python Filename: pool/main/j/joblib/python-joblib_0.4.6-1~nd+1_all.deb Size: 38672 SHA256: c5bb30de24d7ae7b7ad6dec8c9f2fffbe7a327ba3e42164cdc903041e230c711 SHA1: 86a83704d8e03bbe6e60bd5138f957438bdba4ff MD5sum: 855225f4071e1fe4697007ef8214de54 Description: tools to provide lightweight pipelining in Python Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers: - transparent disk-caching of the output values and lazy re-evaluation (memoize pattern) - easy simple parallel computing - logging and tracing of the execution . Joblib is optimized to be fast and robust in particular on large, long-running functions and has specific optimizations for numpy arrays. Package: python-mvpa Source: pymvpa Version: 0.4.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4152 Depends: python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, python-mvpa-lib (>= 0.4.5-1~nd+1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy, python-mvpa-doc Provides: python2.5-mvpa, python2.6-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.5-1~nd+1_all.deb Size: 2167538 SHA256: ef59abd523cb2a25602db157335858c76be23a860ce1cbc69acccae734da943e SHA1: da884e0fa1249e3f8d9f248b4bf9af485cc2533c MD5sum: 066f06deebccb91dc35dafa463d1400b Description: multivariate pattern analysis with Python Python module to ease pattern classification analyses of large datasets. 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, GNB, 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. Python-Version: 2.5, 2.6 Package: python-mvpa-doc Source: pymvpa Version: 0.4.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 41052 Depends: libjs-jquery Suggests: python-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa/python-mvpa-doc_0.4.5-1~nd+1_all.deb Size: 9067604 SHA256: cf0b284af9f9414dc02204ac31625343d80f2b96644fbd718863bc506a8f60f6 SHA1: 7ad38563e0ceedd361e1c42c2b4ecc569d56a9d7 MD5sum: c2e96d3144191dfd8a181b7192052d74 Description: documentation and examples for PyMVPA PyMVPA documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation * BibTeX references file . Additionally, all example scripts shipped with the PyMVPA sources are included. Package: python-mvpa-lib Source: pymvpa Version: 0.4.5-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 304 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm2, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Provides: python2.5-mvpa-lib, python2.6-mvpa-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa-lib_0.4.5-1~nd+1_amd64.deb Size: 70014 SHA256: 6a33bff70c2b3266a205fc2a08fe9f319eca15cfbe625f1af19dae74e3f8b8e1 SHA1: 59cd49331b103a9317ed87a01dee9b271c81e204 MD5sum: 4682edfb8db73ea7a9ca2dc1b5b2fb30 Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. Python-Version: 2.5, 2.6 Package: python-mvpa-snapshot Source: pymvpa-snapshot Version: 0.5.0.dev+783+gde39-1~sid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 4432 Depends: python (>= 2.4), python-support (>= 0.90.0), python2.6, python-numpy, python-mvpa-snapshot-lib (>= 0.5.0.dev+783+gde39-1~sid.nd1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-scikits-openopt, python-rpy, python-mvpa-doc Conflicts: python-mvpa Provides: python2.5-mvpa-snapshot, python2.6-mvpa-snapshot Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa-snapshot/python-mvpa-snapshot_0.5.0.dev+783+gde39-1~sid.nd1_all.deb Size: 2225766 SHA256: 11d984831fbf38243f7886014f8f40aa3094c3841a4ed3966896888a4c42adf7 SHA1: 0059c6b5352a7034086efed13ec93f3c78526a41 MD5sum: f884a7cf433a74b2acbf5b9fb2fc36e6 Description: multivariate pattern analysis with Python Python module to ease pattern classification analyses of large datasets. 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 a development snaphot. The latest released version is provided by the python-mvpa package. Python-Version: 2.5, 2.6 Package: python-mvpa-snapshot-lib Source: pymvpa-snapshot Version: 0.5.0.dev+783+gde39-1~sid.nd1 Architecture: amd64 Maintainer: Experimental Psychology Maintainers Installed-Size: 300 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm2, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Conflicts: python-mvpa-lib Provides: python2.5-mvpa-snapshot-lib, python2.6-mvpa-snapshot-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa-snapshot/python-mvpa-snapshot-lib_0.5.0.dev+783+gde39-1~sid.nd1_amd64.deb Size: 68032 SHA256: d6cb1574f5ee90fbbd2a354a90deee5e27f9bff4c4f6cac3f758a4438bfc3ddb SHA1: 45bcfb39da3d1aa90eab05e208b36a13bab0046c MD5sum: 54aa9bd24f0cb6623745448bda9979ba Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snaphot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.5, 2.6 Package: python-nibabel Source: nibabel Version: 1.0.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2784 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-dicom Suggests: python-nibabel-doc Provides: python2.5-nibabel, python2.6-nibabel Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: python Filename: pool/main/n/nibabel/python-nibabel_1.0.0-1~nd+1_all.deb Size: 1061210 SHA256: 0505371d82e6a344e73ce30b5d1b7200f8a104bc3ebf561ddb5dbc4544f210f2 SHA1: 3bb315251ab12b46a378e1df67107d032fd81ced MD5sum: 7924017354df1fa9c4963e13ac694244 Description: Python bindings to various neuroimaging data formats This package 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 tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.5, 2.6 Package: python-nibabel-doc Source: nibabel Version: 1.0.0-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2724 Depends: libjs-jquery Homepage: http://nipy.sourceforge.net/nibabel Priority: extra Section: doc Filename: pool/main/n/nibabel/python-nibabel-doc_1.0.0-1~nd+1_all.deb Size: 404008 SHA256: bda2ded9fa849d866db78959a43e71862b9a66cb02b663d7612112aac2ac4da1 SHA1: 1462cfbd7f63745042f8522b354cf186c51b9b1b MD5sum: c403118f483919e980093dbedbcb8e0c Description: documentation for NiBabel 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 provides the documentation in HTML format. Package: python-nibabel-snapshot Source: nibabel-snapshot Version: 1.0.0.dev+137+gf1c6-1~sid.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 964 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, libjs-jquery, python-scipy Conflicts: python-nibabel Provides: python2.5-nibabel-snapshot, python2.6-nibabel-snapshot Homepage: http://nipy.sourceforge.net/nibabel Priority: optional Section: python Filename: pool/main/n/nibabel-snapshot/python-nibabel-snapshot_1.0.0.dev+137+gf1c6-1~sid.nd1_all.deb Size: 469776 SHA256: 674d6faa8c47cc5d2abded6bf10d56d3c7b2041b70390b254d6bed4fe0b89f92 SHA1: 1e06be036a09d6114c43bcccf080aa256f7c7a69 MD5sum: 26e58a8ca88e85dfba68eae891bdcdeb Description: Python bindings to various neuroimaging data formats Currently supported formats are: . * ANALYZE (including SPM2 and SPM99 variants) * MINC * NIfTI * PAR/REC . This package also provides a commandline tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.5, 2.6 Package: python-nipype Source: nipype Version: 0.3.3-1~sid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1752 Depends: python (>= 2.5), python-support (>= 0.90.0), python-scipy, python-simplejson, python-traits Recommends: python-nifti, ipython, python-nose, python-networkx Suggests: fsl, afni, lipsia, python-nipy Provides: python2.5-nipype, python2.6-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.3.3-1~sid.nd1_all.deb Size: 277514 SHA256: 368910b5558d3586e86bb6d919354e15c980d15156e87379ed5b6d92e9944637 SHA1: e8079a3aef6b6ea8822867bb23ea127d228e82c7 MD5sum: fb3c525781e1a4416582704f8041bd71 Description: Neuroimaging data analysis pipelines in Python 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). Package: python-nipype-doc Source: nipype Version: 0.3.3-1~sid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3640 Depends: libjs-jquery Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.3.3-1~sid.nd1_all.deb Size: 840650 SHA256: a2adc848d29e0eac4f7f7d1e323d06441cc7a2a947d1f608364e3a2a14c4bd8d SHA1: fd337addc385ad76b1a6f1e19b9eafea534a8a62 MD5sum: 2cbce98a7cd66dac74d132b310f68328 Description: Neuroimaging data analysis pipelines in Python -- documentation 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). . This package contains Nipype examples and documentation in various formats. Package: python-nitime Source: nitime Version: 0.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 752 Depends: python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-nibabel, python-networkx Homepage: http://nipy.org/nitime Priority: extra Section: python Filename: pool/main/n/nitime/python-nitime_0.2-1~nd+1_all.deb Size: 312880 SHA256: fff965f4b8993e9afa6c2d83a2b3c6c0f56bcb14fb4b48b07703b0585bf5c660 SHA1: 526e3c73cf4a538774961aa82beb07919e7a079e MD5sum: f4bac61309b120a633cbcaa82004c050 Description: timeseries analysis for neuroscience data (nitime) 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. Package: python-nitime-doc Source: nitime Version: 0.2-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4056 Depends: libjs-jquery Suggests: python-nitime Homepage: http://nipy.org/nitime Priority: extra Section: doc Filename: pool/main/n/nitime/python-nitime-doc_0.2-1~nd+1_all.deb Size: 2631540 SHA256: 174f9035e1239f9831f477855dc231deb64ad0e9409dc6732456213b46eb8ca3 SHA1: bb9668391763b17e6885f33f52f8ee9e23ce03a4 MD5sum: 820475354de9de093251285e46f4f0d4 Description: timeseries analysis for neuroscience data (nitime) -- documentation Nitime is a Python module for time-series analysis of data from neuroscience experiments. . This package provides the documentation in HTML format. Package: python-pyoptical Source: pyoptical Version: 0.2-1~sid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 72 Depends: python-serial Enhances: psychopy, python-pyepl Homepage: http://github.com/esc/pyoptical Priority: extra Section: python Filename: pool/main/p/pyoptical/python-pyoptical_0.2-1~sid.nd1_all.deb Size: 6946 SHA256: 61b96afae4d2c43351ad598253b8b38fff6b0c2d99669f49f431b8d8678f89be SHA1: 8442b14c93a7d2c3718d78655dc85fef951bcfaf MD5sum: 1eaea3d3d51bcd440299d8aa65220111 Description: python interface to the CRS 'OptiCAL' photometer The 'OptiCAL' is a photometer that is produced by Cambridge Research Systems (CRS). This device is a standard tool for gamma-calibration of display devices in vision research. This package provides a free-software replacement for the Windows-software distributed by the manufacturer that allows querying an OptiCAL via a serial connection. pyoptical can be used as a library for third-party applications or as a standalone command line tool. Python-Version: 2.5, 2.6 Package: python-pyssdh Source: openelectrophy Version: 0.0.svn143-1~sid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 792 Depends: python-support (>= 0.90.0), python-numpy, python-scipy, python-qt4, python-mysqldb, python-matplotlib Recommends: g++ | c++-compiler, python-mdp Suggests: mysql-server Provides: python2.4-pyssdh, python2.5-pyssdh Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: python Filename: pool/main/o/openelectrophy/python-pyssdh_0.0.svn143-1~sid.nd1_all.deb Size: 119482 SHA256: 047337422d8c671d1ca38e938384c985fc1fac566d178123b6cb5ee4d1fccc51 SHA1: 2fb56ca17ad07ee58955caf8de17a4cd24d3d85a MD5sum: 1790628c9012a2ae40aff02998bd9c41 Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy Python module. Python-Version: 2.4, 2.5 Package: python-scikits-learn Source: scikit-learn Version: 0.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1112 Depends: python (>= 2.5), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0), python-scipy, python-scikits-learn-lib (>= 0.5-1~nd+1) Recommends: python-nose, python-psyco, python-matplotlib, python-joblib (>= 0.4.5) Suggests: python-dap, python-scikits-optimization, python-scikits-learn-doc Provides: python2.5-scikits-learn, python2.6-scikits-learn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn_0.5-1~nd+1_all.deb Size: 203456 SHA256: 58c467196d1137788a286ffb6d48b9ae3b9b2e22584baf87712e27a5544ffd48 SHA1: 5d612867c0a038af1f6bb8571bd067e553c2b504 MD5sum: 7ce3bb3fef42c063e45e673e49b36ec6 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Python-Version: 2.5, 2.6 Package: python-scikits-learn-doc Source: scikit-learn Version: 0.5-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 6392 Depends: libjs-jquery Suggests: python-scikits-learn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-scikits-learn-doc_0.5-1~nd+1_all.deb Size: 3201136 SHA256: 8350c31d9a0bb34541963174ff236e7af1fcfaaa746a32c7a08c03387ab7ad47 SHA1: e933290cd8548dcd3fafef6b6156db92ae1983c1 MD5sum: c11dc8c29cd24fa58cf8ce2566ca4b78 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-scikits-learn. Package: python-scikits-learn-lib Source: scikit-learn Version: 0.5-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1420 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), libsvm2, python (<< 2.7), python (>= 2.5), python-numpy (<< 1:1.5), python-numpy (>= 1:1.4.1), python-support (>= 0.90.0) Provides: python2.5-scikits-learn-lib, python2.6-scikits-learn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn-lib_0.5-1~nd+1_amd64.deb Size: 505284 SHA256: fc48655d91504fac46cec7b3a180e9f67055b3981c9e55cc30271e8d40a04d76 SHA1: bec4b270f510d79533ce376224024fd3e1b07b8a MD5sum: 47ad9266f898c50b2d499e50f23a6978 Description: low-level implementations and bindings for scikits-learn This is an add-on package for python-scikits-learn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Python-Version: 2.5, 2.6 Package: python-scikits-statsmodels Source: statsmodels Version: 0.2.0+bzr1990-1~sid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 9644 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy Recommends: python-matplotlib, python-nose, python-rpy Provides: python2.5-scikits-statsmodels, python2.6-scikits-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: optional Section: python Filename: pool/main/s/statsmodels/python-scikits-statsmodels_0.2.0+bzr1990-1~sid.nd1_all.deb Size: 1874480 SHA256: 1d5be1691f554290e8c195284ef8fbdffd1ef948df40cb4e42f23ed1ea454724 SHA1: 95f607c3b8e4ec04a0a3530abcc4d0f381decba7 MD5sum: 775433657571640365080d6f54bba54c Description: classes and functions for the estimation of statistical models scikits.statsmodels is a pure Python package that 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 avalable for each estimation problem. Python-Version: 2.5, 2.6 Package: python-scikits-statsmodels-doc Source: statsmodels Version: 0.2.0+bzr1990-1~sid.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 2184 Depends: libjs-jquery Suggests: python-scikits-statsmodels Homepage: http://statsmodels.sourceforge.net/ Priority: optional Section: doc Filename: pool/main/s/statsmodels/python-scikits-statsmodels-doc_0.2.0+bzr1990-1~sid.nd1_all.deb Size: 307526 SHA256: e87b964cce23b84e481622b0dd5b20db420f9da592f62f56b48372e1f162a76b SHA1: a5b070d9b9ea9046491c3efc92582ae85ccd7c95 MD5sum: f52b8e834c2a71aaf9541efd3bd7326b Description: documentation and examples for python-scikits-statsmodels This package contains HTML documentation and example scripts for python-scikits-statsmodels. Package: python-sphinx Source: sphinx Version: 1.0.1-1~nd+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 4580 Depends: python (>= 2.4), python-support (>= 0.90.0), python-docutils (>= 0.5), python-pygments (>= 0.8), python-jinja2 (>= 2.2), libjs-jquery Recommends: python (>= 2.6) | python-simplejson, python-imaging Suggests: jsmath Homepage: http://sphinx.pocoo.org/ Priority: optional Section: python Filename: pool/main/s/sphinx/python-sphinx_1.0.1-1~nd+1_all.deb Size: 1233522 SHA256: 9d2412a330c57af8bd8adff6703a5e3c70346a1b892e02a8bb18d751b374ccba SHA1: 5f994974763ed9fa89766248c7ff86510b9fe1b2 MD5sum: a7aa0438348ec0b070a3b32c8f566511 Description: tool for producing documentation for Python projects Sphinx is a tool for producing documentation for Python projects, using reStructuredText as markup language. . Sphinx features: * HTML, CHM, LaTeX output, * Cross-referencing source code, * Automatic indices, * Code highlighting, using Pygments, * Extensibility. Existing extensions: - automatic testing of code snippets, - including doctrings from Python modules. Package: r-noncran-psychofun Version: 0.5.0-1~sid.apsy0 Architecture: all Depends: r-base-core (>= 2.4.0) Installed-Size: 600 Maintainer: Experimental Psychology Maintainers Source: psychofun Priority: optional Section: math Filename: pool/main/p/psychofun/r-noncran-psychofun_0.5.0-1~sid.apsy0_all.deb Size: 70968 MD5sum: ad3d95b1a239fa17cae77a362e9f8639 Description: Bayesian Inference for Psychometric Functions The package provides routines for inference about the parameters of psychometric functions. It provides routines for maximum a posteriori estimation and Markov chain Monte Carlo sampling from the posterior over model parameters. . This package is in many ways the successor of the psignifit package. Package: sigviewer Version: 0.4.3+svn511-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1052 Depends: libbiosig0, libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libgdf0, libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.4.0) Homepage: http://sigviewer.sourceforge.net Priority: extra Section: science Filename: pool/main/s/sigviewer/sigviewer_0.4.3+svn511-1~nd+1_amd64.deb Size: 427974 SHA256: 0bd3d8acd9694a56b19cc85d081fafff1f0399b5f0071be208728d4d8d190089 SHA1: a47e71cbd39ce583994685ccf628af0159ddab8e MD5sum: 39ce81bc71270da7b1efc7cd14691c25 Description: GUI viewer for biosignals such as EEG, EMG, and ECG SigViewer is a viewing and scoring software for biomedical signal data. It relies on biosig4c++ library which supports a number of data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://hci.tugraz.at/schloegl/biosig/TESTED . . Besides displaying biosignals, SigViewer supports creating annotations to select artifacts or specific events. Package: spm8-common Source: spm8 Version: 8.4010~dfsg.1-3 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 21124 Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.4010~dfsg.1-3_all.deb Size: 10086746 SHA256: 420af58742ffd8d712777d84e1b5cab7f62ffa60cc53d3cac35747af68fd57c7 SHA1: 30c639e67be5083685f97306730b186ee4b2c063 MD5sum: 89daeb63df29035e31b49719d63eb4ba Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain 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 data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.4010~dfsg.1-3 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73316 Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.4010~dfsg.1-3_all.deb Size: 52168426 SHA256: a33f373c13f9142a6d423af68ff01331166451c04e51192472cc1736190706bf SHA1: 4b9731f75628adf68a2e892314976c892bf0e9cb MD5sum: e5f7efb634ddadfc7f5387d930f62872 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain 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 data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.4010~dfsg.1-3 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 11288 Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.4010~dfsg.1-3_all.deb Size: 10423480 SHA256: bc4fffabe5ca9a2080d9a2532ade99a53a6c634dddf0c74b2effb107c1c28bff SHA1: 24a099d5790918edb44830153cea6c45a2d6f206 MD5sum: 1bfc3e98c3e6d7026ceafa67d7182426 Description: manual for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain 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 data. . This package provides the SPM manual in PDF format. Package: svgtune Version: 0.1.0-2 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 64 Depends: python, python-lxml Suggests: inkscape Homepage: http://github.com/yarikoptic/svgtune Priority: optional Section: graphics Filename: pool/main/s/svgtune/svgtune_0.1.0-2_all.deb Size: 6680 SHA256: 69b4df1e0b4c247673265c7f5bb2b2ffe2209d783617bf7f6eadce86633f80e1 SHA1: bec339e4453c35a05a616deef6769a6f2ad2d00d MD5sum: ef6797498477a73f930ad9bc0db3ba73 Description: tool to generate a set of .svg files out of a single .svg file svgtune is just a little helper to generate a set of .svg files out of a single .svg file, by tuning respective groups/layers visibility, transparency or anything else. . It might come very handy for generation of incremental figures to be embedded into the presentation in any format which inkscape could render using original .svg file (e.g. pdf, png). Package: voxbo Version: 1.8.5~svn1222-1~nd+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 10000 Depends: neurodebian-popularity-contest, libc6 (>= 2.3.4), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libpng12-0 (>= 1.2.13-4), libqt4-network (>= 4:4.5.3), libqt4-qt3support (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.4.0), libx11-6, libxext6, libxi6, libxrender1, zlib1g (>= 1:1.1.4) Suggests: mni-colin27-nifti, matlab-spm8 Homepage: http://www.voxbo.org Priority: extra Section: science Filename: pool/main/v/voxbo/voxbo_1.8.5~svn1222-1~nd+1_amd64.deb Size: 3685048 SHA256: ede8949d07256360db46075ca46768824ea80619833a9a0af54c8e73245018b1 SHA1: d077f1bcf5ec100ef81257ba52f8d2bb56717534 MD5sum: b6e90c50aa7a9687556a66b8b940ea12 Description: processing, statistical analysis, and display of brain imaging data 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.