Package: afni Version: 0.20091204~dfsg.1-1~sid.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 26236 Depends: afni-common (= 0.20091204~dfsg.1-1~sid.nd1), tcsh, gifsicle, libjpeg-progs, freeglut3, lesstif2 (>= 1:0.94.4), libc6 (>= 2.7), libexpat1 (>= 1.95.8), libf2c2, 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), libnetcdf4, libnifti1 (>> 1.1.0-2), libsm6, libvolpack1, libx11-6 (>= 0), libxext6, libxi6, libxmu6, libxt6, zlib1g (>= 1:1.1.4) Recommends: nifti-bin, bzip2, ffmpeg Homepage: http://afni.nimh.nih.gov Priority: extra Section: science Filename: pool/main/a/afni/afni_0.20091204~dfsg.1-1~sid.nd1_amd64.deb Size: 10590780 SHA256: ea98780ab91f46013161f63e19fd200265add8fcd8106923b1587a5027f77d87 SHA1: 6b8179f729a628fc800991411072ef7c8f91dafc MD5sum: 266d8807e1e0de7cc5fcea9e73d78517 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 easily usable in combination with FSL and Freesurfer. Package: afni-common Source: afni Version: 0.20091204~dfsg.1-1~sid.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 5312 Depends: python, tcsh Homepage: http://afni.nimh.nih.gov Priority: extra Section: science Filename: pool/main/a/afni/afni-common_0.20091204~dfsg.1-1~sid.nd1_all.deb Size: 3059784 SHA256: c6aa440d13844e7c064abd0b990e163b0e1c1301e4450915fd02bc6e82c4730a SHA1: ae5e4b4b3ff9bd79391a109ad9d8eabae304455d MD5sum: 79fb5dd80e6c9dd06be2dca53e285925 Description: miscellaneous scripts and data files for AFNI This package provides the required architecture independent parts of AFNI. Package: afni-dev Source: afni Version: 0.20091204~dfsg.1-1~sid.nd1 Architecture: amd64 Maintainer: Michael Hanke Installed-Size: 14720 Homepage: http://afni.nimh.nih.gov Priority: extra Section: science Filename: pool/main/a/afni/afni-dev_0.20091204~dfsg.1-1~sid.nd1_amd64.deb Size: 3733432 SHA256: 7548a19393f2d36384f92c7ef1c6f4d7f1c5625b518500ce94cc7a7d16ca3edb SHA1: 31422e50e686dbcc4b08e0577113917046b94622 MD5sum: 323c1a7480a13b43aa2253ee1cac6516 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 packages provides the necessary libraries and header files for AFNI plugin development. Package: ants Version: 1.9+svn532-2~sid.nd1 Architecture: amd64 Maintainer: Yaroslav Halchenko Installed-Size: 39120 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+svn532-2~sid.nd1_amd64.deb Size: 11581024 SHA256: 39ae8835d8059070fb863f339b99799df244c59c81c704a24ecab5db85c6e578 SHA1: 8926987ff54646b330ce68be8955257c79e93c78 MD5sum: 39434c34166c32dd1e9b2430f10e85db 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: 0.94.1+svn2521-1~pre0~sid.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 648 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_0.94.1+svn2521-1~pre0~sid.nd1_amd64.deb Size: 247832 SHA256: 032d540b4a09c1761a9667be32d1fc55d5b65ab3f7d69ce89b08a699803e6e14 SHA1: d5e4189b81b33fc8c5983c6a9b775fc0872cabb7 MD5sum: 806ad98f597dd50ac0067bbc0ad19204 Description: format conversion tools for biomedical data formats Based on libbiosig4c++ 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: libbiosig-dev Source: biosig4c++ Version: 0.94.1+svn2521-1~pre0~sid.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1600 Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.94.1+svn2521-1~pre0~sid.nd1_amd64.deb Size: 373322 SHA256: 4a8218ab218fa68fcccd9388eab5ab8fc845dd435d414b71d28a702385b884fa SHA1: 30e91a9da1087056baa15f8a2c6353e240b760bc MD5sum: 24c7b6bec4a775d1595a22c0eeb410b8 Description: library for accessing files in biomedical data formats 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: 0.94.1+svn2521-1~pre0~sid.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 880 Depends: libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1) Homepage: http://biosig.sf.net/ Priority: extra Section: libs Filename: pool/main/b/biosig4c++/libbiosig0_0.94.1+svn2521-1~pre0~sid.nd1_amd64.deb Size: 297572 SHA256: a3b0cce8a079e226403f940dba1abe9486238ffca8325bd09d77f0a8d10b811b SHA1: e62e20d5e9e986dfc795ffc9894cbaf7111b25a5 MD5sum: bd5aa6fe96a77b03b2be193466b21492 Description: library for accessing files in biomedical data formats 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: 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: 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: mni-colin27-minc Source: mni-colin27 Version: 1.1-1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 12064 Homepage: http://packages.bic.mni.mcgill.ca/tgz/ Priority: extra Section: science Filename: pool/main/m/mni-colin27/mni-colin27-minc_1.1-1_all.deb Size: 12274320 SHA256: 53c6b97ed6d4182fd4da2502377bc1f32de4a816952eab6037e8791d85828fd0 SHA1: 467a57c00040530e387ed1183815d8591b32b2e6 MD5sum: 1ea73688b743b36778bee148076ebd4d Description: Talairach stereotaxic space template This template MRI volume was created from 27 T1-weighted MRI scans of a single individual that have been transformed into the Talairach stereotaxic space. The anatomical image is complemented by a brain and a head mask. All images are in 1x1x1 mm resolution. . This package provides the template in MINC format. Package: mni-colin27-nifti Source: mni-colin27 Version: 1.1-1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 11748 Homepage: http://packages.bic.mni.mcgill.ca/tgz/ Priority: extra Section: science Filename: pool/main/m/mni-colin27/mni-colin27-nifti_1.1-1_all.deb Size: 11952134 SHA256: 73bbe01f4f42fe966fc9308b46cedca16cda981da0492975afaaa9f731bf5581 SHA1: e1fa1c293312ea699493d2158efe70dd6649840e MD5sum: b9228cbbbd551e91de94f28d8f4da2ea Description: Talairach stereotaxic space template This template MRI volume was created from 27 T1-weighted MRI scans of a single individual that have been transformed into the Talairach stereotaxic space. The anatomical image is complemented by a brain and a head mask. All images are in 1x1x1 mm resolution. . This package provides the template in NIfTI format. Package: mni-icbm152-nlin-2009a Source: mni-icbm152-nlin Version: 0.20090623.1-1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 120332 Homepage: http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 Priority: extra Section: science Filename: pool/main/m/mni-icbm152-nlin/mni-icbm152-nlin-2009a_0.20090623.1-1_all.deb Size: 122770998 SHA256: d1cab63c136b6898ce133ae0ac5309b77ac11774317e4710a3c567689bc64435 SHA1: 3c310421152cc482d8d99dca51d3c0145dab6553 MD5sum: dc79aa787955aa03e0d60c98cc5c3da3 Description: MNI stereotaxic space human brain template This is an unbiased standard magnetic resonance imaging template volume for the normal human population. It has been created by the Montreal Neurological Institute (MNI) using anatomical data from the International Consortium for Brain Mapping (ICBM). . The package provides a 1x1x1 mm resolution template (hemissphere-symetric and asymetric non-linearily co-registered versions), including T1w, T2w, PDw modalities, T2 relaxometry, and tissue probability maps. In addition, it contains a lobe atlas, and masks for brain, eyes and face. . The template is similar to the one in the mni-icbm152-nlin-2009c package. However, the sampling of the ICBM data is different and here intensity inhomogeneity correction was performed by N3 version 1.10.1, leading to different tissue probability maps. Package: mni-icbm152-nlin-2009b Source: mni-icbm152-nlin Version: 0.20090623.1-1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 722392 Homepage: http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 Priority: extra Section: science Filename: pool/main/m/mni-icbm152-nlin/mni-icbm152-nlin-2009b_0.20090623.1-1_all.deb Size: 739142896 SHA256: d00b100f1a65e1e3909adddd1f9a9d3fb4c717ced6f425089a276b64780cd13d SHA1: 5d4b4d340be14ed062a5e96bc43af33d2fd9ec40 MD5sum: 0e906ff84b016a127d7cc1ecf03dfbef Description: MNI stereotaxic space human brain template This is an unbiased standard magnetic resonance imaging template volume for the normal human population. It has been created by the Montreal Neurological Institute (MNI) using anatomical data from the International Consortium for Brain Mapping (ICBM). . The package provides a 0.5x0.5x0.5 mm resolution template (hemissphere-symetric and asymetric non-linearily co-registered versions), including T1w, T2w, PDw modalities. Package: mni-icbm152-nlin-2009c Source: mni-icbm152-nlin Version: 0.20090623.1-1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 113888 Homepage: http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 Priority: extra Section: science Filename: pool/main/m/mni-icbm152-nlin/mni-icbm152-nlin-2009c_0.20090623.1-1_all.deb Size: 116182926 SHA256: 08c25ff6564fd6860d96bf32a182ce5922aaadd2b584850d82762aa9bb4fefd5 SHA1: f515a99b9edc7dfabfb058a21acbab12a2031c1a MD5sum: c1ec21de0bd62ab68c1d2a84655d4891 Description: MNI stereotaxic space human brain template This is an unbiased standard magnetic resonance imaging template volume for the normal human population. It has been created by the Montreal Neurological Institute (MNI) using anatomical data from the International Consortium for Brain Mapping (ICBM). . The package provides a 1x1x1 mm resolution template (hemissphere-symetric and asymetric non-linearily co-registered versions), including T1w, T2w, PDw modalities, and tissue probability maps. In addition, it contains a lobe atlas, and masks for brain, eyes and face. . The template is similar to the one in the mni-icbm152-nlin-2009a package. However, the sampling of the ICBM data is different and here intensity inhomogeneity correction was performed by N3 version 1.11, leading to different tissue probability maps. Package: octave-biosig Source: biosig4c++ Version: 0.94.1+svn2521-1~pre0~sid.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1596 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_0.94.1+svn2521-1~pre0~sid.nd1_amd64.deb Size: 581604 SHA256: d0601a74689a77560f0ba69e9bb5a2e18628b9841bb81fc4c5ab6277cac19a30 SHA1: 8eb9947ccc676580d2d61592bf99142bd5d05ab2 MD5sum: bec16a28d61dc2f6369b5671e35cde4c Description: Octave bindings for BioSig4C++ 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, EDlibbiosig4c++. 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: 1.62.01.dfsg-1~sid.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3124 Depends: 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_1.62.01.dfsg-1~sid.nd1_all.deb Size: 1393782 SHA256: 48c146abadb35e0a6346574f459ce8dff6493e8371d7a4c98cc2fb48a6992ffb SHA1: ef5b0e24cbae6f6fba904a9dd971817bf588152a MD5sum: 22744616b3e43ef5b3450b185748eb08 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: 0.94.1+svn2521-1~pre0~sid.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1028 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_0.94.1+svn2521-1~pre0~sid.nd1_amd64.deb Size: 331384 SHA256: c77852871285fe07a4b916b2d8a33633a70c9db980c103a2238ad39b9677fff1 SHA1: 4d7a7a817c5136cf103ab5b630918cb7fc9bbb32 MD5sum: 3f0dec9234bb1a8a759a720185f95622 Description: Python bindings for BioSig4C++ 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, EDlibbiosig4c++. 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-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-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-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-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: 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: 0.3.0+svn362-1~pre1~sid.nd1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 1484 Depends: libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), zlib1g (>= 1:1.1.4) Homepage: http://sigviewer.sourceforge.net Priority: extra Section: science Filename: pool/main/s/sigviewer/sigviewer_0.3.0+svn362-1~pre1~sid.nd1_amd64.deb Size: 608362 SHA256: f4fd7025903f1b937c03fc49cb193172e53794eda34fd9a5e45c4a7181d4fc1f SHA1: 47e3c498f16e720ee165d1b51300ce76bdd9c9e4 MD5sum: deef39f1f5e1e4ad17e2bdd900365c37 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: svgtune Version: 0.1.0-1~sid.nd1 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_0.1.0-1~sid.nd1_all.deb Size: 6746 SHA256: 7e2eef77f108ebbb53afb7238f1a87fb77f8e500267878f69eef8e5123bb4ddb SHA1: 8cb46ecfad1a596ec83d7c7fc635056ce54b86b9 MD5sum: a6c69c60a2d9de936346fdaf80e2f7bc 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).