Package: afni Version: 0.20140908~dfsg.1-1~nd13.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 36898 Depends: neurodebian-popularity-contest, afni-common (= 0.20140908~dfsg.1-1~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_0.20140908~dfsg.1-1~nd13.04+1_amd64.deb Size: 15180450 SHA256: 54218eda89e81ccfdc18daacc0451481bd41dbd72d785d68753fd42f08110dc3 SHA1: e06309d6bd4457bfe573be229c4a37d92f4da5b8 MD5sum: 9971c7d82dcd0b24ba4fc364372cd5f7 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: 0.20140908~dfsg.1-1~nd13.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 11375 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_0.20140908~dfsg.1-1~nd13.04+1_all.deb Size: 7488072 SHA256: 9a8050f81124dd6d4f2d70d3ae03935908361e8c511f75b74920f896eb94a76c SHA1: a25691b8858a0ebec428e723b0ad1b07a6e71bdc MD5sum: ecc30f71a830a4206ba7fe77fbc54e27 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: 0.20140908~dfsg.1-1~nd13.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 93738 Depends: neurodebian-popularity-contest Homepage: http://afni.nimh.nih.gov Priority: extra Section: contrib/science Filename: pool/contrib/a/afni/afni-dbg_0.20140908~dfsg.1-1~nd13.04+1_amd64.deb Size: 29055780 SHA256: 630e25cf9ed5f8ec9d2114c6e1dc5d69d761e7c82f12832a7d940f608f115dff SHA1: 46ba5db170ab42062a36428f0275e9911318d08d MD5sum: 3ef7054ad5030d8b02f7f7aadf549982 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: 0.20140908~dfsg.1-1~nd13.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 18555 Depends: neurodebian-popularity-contest Homepage: http://afni.nimh.nih.gov Priority: extra Section: contrib/science Filename: pool/contrib/a/afni/afni-dev_0.20140908~dfsg.1-1~nd13.04+1_amd64.deb Size: 4860510 SHA256: cb049f0e02accb5fc03efddf52e6a3f26be44c0761d0c62cc8d572a62e982e69 SHA1: 5e19f77d00517bee074d7c60d366882a430dceab MD5sum: d1fc517e76ce54a1e1ee83e9f5c48030 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.