Package: afni Version: 0.20130912~dfsg.1-2~nd13.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 33488 Depends: neurodebian-popularity-contest, afni-common (= 0.20130912~dfsg.1-2~nd13.04+1), tcsh, gifsicle, libjpeg-progs, freeglut3, libc6 (>= 2.15), libf2c2, libgiftiio0, libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libglw1-mesa | libglw1, libgomp1 (>= 4.2.1), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libice6 (>= 1:1.0.0), libmotif4, libnetcdfc7, libnifti2, libsm6, libvolpack1, libx11-6, libxext6, libxmu6, libxt6, xmhtml1, zlib1g (>= 1:1.1.4) Recommends: nifti-bin, bzip2, ffmpeg, netpbm, qhull-bin Suggests: r-base Homepage: http://afni.nimh.nih.gov Priority: extra Section: contrib/science Filename: pool/contrib/a/afni/afni_0.20130912~dfsg.1-2~nd13.04+1_amd64.deb Size: 13772426 SHA256: dcefdbfd0b9dd183670407ad7444e8479405bbf79f71165523b493c6dfe22199 SHA1: 23622fc56a48e4b6aad7614399fa40f1e29f48b0 MD5sum: 67c570fa368a7acaa08a504cceb24e88 Description: toolkit for analyzing and visualizing functional MRI data 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. Package: afni-common Source: afni Version: 0.20130912~dfsg.1-2~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10159 Depends: neurodebian-popularity-contest, python, tcsh Recommends: python-mdp, python-nibabel, afni-atlases Homepage: http://afni.nimh.nih.gov Priority: extra Section: contrib/science Filename: pool/contrib/a/afni/afni-common_0.20130912~dfsg.1-2~nd13.04+1_all.deb Size: 6439676 SHA256: 70e52dc646ed034c9c759a3b24e73c6c9611bba58b5d219024f2fb61f7260c35 SHA1: 281898f013a6791aa5116ad0b0304478e4c203e8 MD5sum: bfe9a4cf60ceca185d693c156f9e8aa1 Description: miscellaneous scripts and data files for AFNI 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). . This package provides the required architecture independent parts of AFNI. Package: afni-dbg Source: afni Version: 0.20130912~dfsg.1-2~nd13.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 84069 Depends: neurodebian-popularity-contest Homepage: http://afni.nimh.nih.gov Priority: extra Section: contrib/science Filename: pool/contrib/a/afni/afni-dbg_0.20130912~dfsg.1-2~nd13.04+1_amd64.deb Size: 26355328 SHA256: 6c2df9fd07604414f0060f60d4a7a936bca27a3ee8ece0e531f119d0560aeb3a SHA1: 6071c7229933202dbdfa1aa96082103014976c69 MD5sum: 25beaa86cb4867da40411d741f977f4e Description: debug symbols for AFNI 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). . This package provides debug symbols which could be useful to troubleshoot and report problems with AFNI. Package: afni-dev Source: afni Version: 0.20130912~dfsg.1-2~nd13.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 17548 Depends: neurodebian-popularity-contest Homepage: http://afni.nimh.nih.gov Priority: extra Section: contrib/science Filename: pool/contrib/a/afni/afni-dev_0.20130912~dfsg.1-2~nd13.04+1_amd64.deb Size: 4613764 SHA256: ad037af2a3684512e3ebae194a9109a743cda9ea20acf8ba1105c29ab5bf382e SHA1: 3c94e6a7d3ccc94099ff3f76df600c0da862167f MD5sum: 1014f4d44e33a74137085f7c777e31ea Description: header and static libraries for AFNI plugin development 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). . This package provides the necessary libraries and header files for AFNI plugin development. Package: fsl-5.0-complete Source: fslmeta Version: 5.0.5-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 29 Depends: fsl-5.0-core (>= 5.0.5-1~nd13.04+1~), fsl-5.0-doc (>= 5.0.5-1~nd13.04+1~), fsl-atlases (>= 5.0~), fslview, fsl-possum-data (>= 5.0~), fsl-first-data (>= 5.0~) Homepage: http://www.fmrib.ox.ac.uk/fsl/ Priority: optional Section: contrib/science Filename: pool/contrib/f/fslmeta/fsl-5.0-complete_5.0.5-1~nd13.04+1_all.deb Size: 3910 SHA256: 4569c5805929a22a2053d2afc2f1f4f2c74c6a6898b40289aa29c370cdeed021 SHA1: 74f2a216b7b84fac0f0a3d423e58e2f50d562e54 MD5sum: 5ffbeda258b081bdeb75138ee1812072 Description: metapackage for the entire FSL suite (tools and data) FSL is a comprehensive library of image analysis and statistical tools for fMRI, MRI and DTI brain imaging data. The suite consists of various command line tools, as well as simple GUIs for its core analysis pipelines. Among others, FSL offers implementations of standard GLM analysis, white matter tractography, tissue segmentation, affine and non-linear co-registration, and independent component analysis. . Installing this meta package yields a complete FSL 5.0 installation, including all tools and data packages. Package: fsl-complete Source: fslmeta Version: 5.0.5-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 29 Depends: fsl-5.0-complete Homepage: http://www.fmrib.ox.ac.uk/fsl/ Priority: optional Section: contrib/science Filename: pool/contrib/f/fslmeta/fsl-complete_5.0.5-1~nd13.04+1_all.deb Size: 3868 SHA256: 16916d76a96ddc8870d30c89c711ab545ce0b38a68259cdbb510825e457d42c3 SHA1: f6b32499e3a1ce38533329d81ec9f34c45ac94c0 MD5sum: 531aa6e912693aa87c4aee71d3001938 Description: metapackage for the entire FSL suite (tools and data) FSL is a comprehensive library of image analysis and statistical tools for fMRI, MRI and DTI brain imaging data. The suite consists of various command line tools, as well as simple GUIs for its core analysis pipelines. Among others, FSL offers implementations of standard GLM analysis, white matter tractography, tissue segmentation, affine and non-linear co-registration, and independent component analysis. . Installing this meta package yields a complete installation of the latest FSL version, including all tools and data packages. Package: matlab-eeglab11 Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 40738 Depends: neurodebian-popularity-contest, matlab-support Recommends: eeglab11-sampledata Priority: extra Section: contrib/science Filename: pool/contrib/e/eeglab11/matlab-eeglab11_11.0.0.0~b~dfsg.1-1~nd11.10+1+nd12.04+1+nd12.10+1+nd13.04+1_all.deb Size: 14149530 SHA256: 0de144efe450ff2baf847eeff10ce37d740ad1189698a02cfba344db10ed5f4d SHA1: e1ee1679e0bdad0a1045c72d6b32aebcfd911c7f MD5sum: 99945cbd31ef350ab1f4e1d5761069e5 Description: electrophysiological data analysis This is sofwware for processing continuous or event-related EEG or other physiological data. It is designed for use by both novice and expert users. In normal use, the EEGLAB graphic interface calls graphic functions via pop-up function windows. The EEGLAB history mechanism can save the resulting calls to disk for later incorporation into scripts. . This package provides EEGLAB to be used with Matlab. Note that this package depends on Matlab -- a commercial software that needs to be obtained and installed separately. Package: matlab-spm8 Source: spm8 Version: 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1164 Depends: neurodebian-popularity-contest, matlab-support, spm8-common (= 8.5236~dfsg.1-1~nd12.10+1+nd13.04+1), make Provides: spm, spm8 Priority: extra Section: contrib/science Filename: pool/contrib/s/spm8/matlab-spm8_8.5236~dfsg.1-1~nd12.10+1+nd13.04+1_all.deb Size: 232882 SHA256: 5b041edc07602d848038fed440c8d55dcebdeec49ba9605f79b8b3b148da63b0 SHA1: 114d10afaec3d3d3a1d91ab39c5ceec17f50c10a MD5sum: df5ef0a423d75110157b10a1ee41190a Description: analysis of brain imaging data sequences for Matlab 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 SPM to be used with Matlab. Note that this package depends on Matlab -- a commercial software that needs to be obtained and installed separately.