Package: afni Version: 0.20130830~dfsg.1-3~nd13.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 33264 Depends: neurodebian-popularity-contest, afni-common (= 0.20130830~dfsg.1-3~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_0.20130830~dfsg.1-3~nd13.04+1_amd64.deb Size: 13687732 SHA256: c9b8b94415dc39dfd9d20b1296c941c64dae937c948b85a94de2ce1c56ab2cd9 SHA1: 2ffc22ba5766319b0a59a5cca159e0e651370e9d MD5sum: bf197d7aac1f38fe9609792b95bc7dc8 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: 0.20130830~dfsg.1-3~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 10158 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_0.20130830~dfsg.1-3~nd13.04+1_all.deb Size: 6439176 SHA256: 9b9c40f2a6778b1c7898f7c798146bf03f885026f4cb2afb0741ee37630607fc SHA1: ea067e1ffdb259341022fefa54bcf08a7baa084b MD5sum: ada8320749d3a5539f6945b2b70e1798 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: 0.20130830~dfsg.1-3~nd13.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 83456 Depends: neurodebian-popularity-contest Homepage: http://afni.nimh.nih.gov Priority: extra Section: contrib/science Filename: pool/contrib/a/afni/afni-dbg_0.20130830~dfsg.1-3~nd13.04+1_amd64.deb Size: 26180804 SHA256: 347da8a92c7859651bef468f5b0e23c4969987676b45500250507407575f5c70 SHA1: 6713bd8099172764112cd1821cd16ce55c75653e MD5sum: 28e58a3c18ceca6b4793ae8b03b2978d 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: 0.20130830~dfsg.1-3~nd13.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 17513 Depends: neurodebian-popularity-contest Homepage: http://afni.nimh.nih.gov Priority: extra Section: contrib/science Filename: pool/contrib/a/afni/afni-dev_0.20130830~dfsg.1-3~nd13.04+1_amd64.deb Size: 4607174 SHA256: 5a0d5568e5bf3e99527a98628d84b31b69002d4b54b6b85a2f7ef9dd46ae4e10 SHA1: 910c6b95c73eca3e47534f9e24f2b5be557e55f3 MD5sum: c8df5cc1db005b86afcade3bd7ea852d 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: 5.0.4-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 26 Depends: fsl-5.0-core (>= 5.0.4-1~nd13.04+1~), fsl-5.0-doc (>= 5.0.4-1~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_5.0.4-1~nd13.04+1_all.deb Size: 2500 SHA256: 2f869daf0444f8b9d3d1f47184ccd863a1c5a5754dbc30fe2c3b65808b9e9f5c SHA1: c5f983106df0fe4540cec450ca9b60d0f67f7cf8 MD5sum: f6e023c701051f8cbd00531b2cb18b23 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: 5.0.4-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 26 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_5.0.4-1~nd13.04+1_all.deb Size: 2454 SHA256: 93ecdd3cd4605356c1e7bacd44582c4b75cba81ed21fa826eb6eecb091e248ce SHA1: 659095d9e279373e6d004319b5eaa004f6c5876b MD5sum: 23c4be5a5ceb38d9cf4ab834a464ce44 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.