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http://www.nitrc.org/projects/bash-rs-fcmri

THIS RESOURCE IS NO LONGER IN SERVICE, documented July 23, 2015. Of note: most functions have been integrated in 1000 Functional Connectomes Project (www.nitrc.org/projects/fcon_1000). This package is not updated, thus please visit 1000 Functional Connectomes Project site and download relevant bash scripts. BASH Scripts for a resting-state functional MRI study. The functions include seed-based correlation analysis, amplitude analysis and independent component analysis. Note: this tool is just a plug-in for FSL, AFNI and FreeSurfer. Thus, you need have them before you use BASH4RfMRI.

Proper citation: BASH4RfMRI (RRID:SCR_005970) Copy   

•   Source: SciCrunch Registry

http://www.ncbcs.org/biositemaps/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 27,2023. Biositemaps represent a mechanism for computational biologists and bio-informaticians to openly broadcast and retrieve meta-data about biomedical data, tools and services (i.e., biomedical resources) over the Internet. All Institutions with an interest in biomedical research can publish a biositemap.rdf file on their Internet site. The technology, developed by the Biositemaps Working Group of the NIH Roadmap National Centers of Biomedical Computing (NCBC), addresses (i) locating, (ii) querying, (iii) composing or combining, and (iv) mining biomedical resources. Each site which intends to contribute to the inventory instantiates a file on its Internet site biositemap.rdf which conforms to a defined RDF schema and uses concepts from the Biomedical Resource Ontology to describe the resources. Each biositemap.rdf file is simply a list of controlled metadata about resources (software tools, databases, material resources) that your organization uses or believes are important to biomedical research. The key enabling technologies are the Information Model (IM) which is the list of metadata fields about each resource (resource_name, description, contact_person, resource_type,...) and the Biomedical Resource Ontology (BRO) which is a controlled terminology for the resource_typeand which is used to improve the sensitivity and specificity of web searches. Biositemaps blend the features of Sitemaps (enabling efficient web-content exploration) and RSS Feeds (a mechanism for wide and effective news dissemination). As a hybrid between Sitemaps and RSS feeds, the Biositemap infrastructure facilitates a decentralized, portable, extensible and computationally tractable generation and consumption of meta-data about existent, revised and new resources for biomedical computation. Web browsers, crawlers and robots can discover, accumulate, process, integrate and deliver Biositemaps content to (human or machine) users in a variety of graphical, tabular, computational formats. Biositemaps content allows such web browsers to pool resource-associated metadata from disparate and diverse sites and present it to the user in an integrated fashion. The Biositemaps protocol provides clues, information and directives for all Biositemap web harvesters that point to the existence and content of such biomedical resources at different sites.

Proper citation: Biositemaps (RRID:SCR_001976) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/rft_fdr/

So far there is a lack for Random Field Theory (RFT) -based multiple comparison correction for surfaces generated in Freesurfer software package. This set of Matlab-based functions can be used for that purpose. They are based on Worsley?s SurfStat toolbox. You also need to have installed Freesurfer software package and included the Freesurfer?s matlab subdirectory in the Matlab?s search path. In addition, this tool implements the RFT-FDR hierarchical correction that can be used for optimizing the amount of smoothing in cortical thickness analyses (Neuroimage 52, 158-171).

Proper citation: RFT FDR (RRID:SCR_002533) Copy   

•   Source: SciCrunch Registry

http://surfer.nmr.mgh.harvard.edu/fswiki/Tracula

Software tool developed for automatically reconstructing a set of major white matter pathways in the brain from diffusion weighted images using probabilistic tractography. This method utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual intervention with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. The trac-all script is used to preprocess raw diffusion data (correcting for eddy current distortion and B0 field inhomogenities), register them to common spaces, model and reconstruct major white matter pathways (included in the atlas) without any manual intervention. trac-all may be used to execute all the above steps or parts of it depending on the dataset and user''''s preference for analyzing diffusion data. Alternatively, scripts exist to execute chunks of each processing pipeline, and individual commands may be run to execute a single processing step. To explore all the options in running trac-all please refer to the trac-all wiki. In order to use this script to reconstruct tracts in Diffusion images, all the subjects in the dataset must have Freesurfer Recons.

Proper citation: TRACULA (RRID:SCR_013152) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/tehran/

Data set of addiction studies compiled by the NeuroImaging and Analysis Group (NIAG).

Proper citation: NIAG Addiction Data (RRID:SCR_015523) Copy   

•   Source: SciCrunch Registry

https://github.com/howisonlab/softcite-dataset

Gold standard dataset of software mentions in research publications. Provides dataset of annotated software mentions from full text academic literature in biomedicine and economics directly converted from published PDFs with reproducible infrastructure. Includes provenance, and is formatted for immediately usefulness in NLP. Useful for supervised learning at scale.

Proper citation: SoftCite (RRID:SCR_024411) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/cta_toolbox

A Matlab tool to perform statistical analysis on cortical thickness signals on brain surfaces obtained from Freesurfer. It is used for multi-resolutional analysis of such cortical thickness signals and detecting group differences. It is based on the Spectral Graph Wavelet Transform (SGWT) toolbox and provides plug and play methods for deriving Wavelet Multiscale Descriptor (WMD), cortical thickness smoothing using SGWT, Multivariate General Linear Model (MGLM), and False Discovery Rate (FDR).

Proper citation: Wisconsin Cortical Thickness Analysis (CTA) Toolbox (RRID:SCR_014180) Copy   

•   Source: SciCrunch Registry

http://pysurfer.github.com

Software Python tool for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi powerful visualization engine with interface for working with MRI and MEG data. PySurfer offers command-line interface designed to broadly replicate Freesurfer program as well as Python library for writing scripts to explore complex datasets.

Proper citation: PySurfer (RRID:SCR_002524) Copy   

•   Source: SciCrunch Registry

https://voxelmorph.net

Software tool for joint surface based registration and atlas construction of brain geometry and function.Cortical registration framework that jointly models mismatch between geometry and function while simultaneously learning unbiased population specific atlas.

Proper citation: JOSA (RRID:SCR_024756) Copy   

•   Source: SciCrunch Registry

http://www.harvard.edu/

Institution of higher education in the United States. Private Ivy League research university in Cambridge, Massachusetts.

Proper citation: Harvard University; Cambridge; United States (RRID:SCR_011273) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/

Software repository for comparing structural (MRI) and functional neuroimaging (fMRI, PET, EEG, MEG) software tools and resources. NITRC collects and points to standardized information about structural or functional neuroimaging tool or resource.

Proper citation: NeuroImaging Tools and Resources Collaboratory (NITRC) (RRID:SCR_003430) Copy   

•   Source: SciCrunch Registry

https://github.com/automaticanalysis/automaticanalysis

Integration framework for major open source packages in neuroimaging including SPM, FSL, FreeSurfer, EEGLAB, and Fieldtrip. Efficient neuroimaging workflows and parallel processing using Matlab and XML. Addresses challenges of processing multimodal datasets, like combining anatomy, functional MRI, diffusion, and EEG, to yield integrated views of brain. Allows to design, execute, and share pipelines utilizing multiple open source packages. Supports parallelized execution to address challenges of large cohort studies and provides quality control offering group statistics and reporting facilities to help identify outlier subjects and erroneous processing steps.

Proper citation: Automatic Analysis (RRID:SCR_003560) Copy   

•   Source: SciCrunch Registry

https://github.com/VisionandCognition/NHP-Freesurfer

Software tool as guide to process NHP anatomical MRI data with adapted version of Freesurfer to generate surfaces and flatmaps.

Proper citation: NHP Freesurfer (RRID:SCR_021814) Copy   

•   Source: SciCrunch Registry

http://sccn.ucsd.edu/fmrlab/index.html

A Matlab toolbox for fMRI data analysis using Independent Component Analysis (ICA). It provides an integrated environment to manage, process and analyze fMRI data in a single framework so that users can complete the analysis without switching between software. In addition, it provides an interactive Matlab graphic user interface (GUI). All the necessary processes to apply ICA to fMRI data and review its results can be run from the graphic interface. The FMRLAB processing flow is straightforward. Custom analyses can be performed with Matlab scripts using the FMRLAB functions and data structure. Since fMRI data analysis is a complex enterprise, including digital image processing, statistical analysis and data visualization, an integrated framework combining processing elements is desired eagerly by users in the neuroimaging community. Recently, large number of software tools for data analysis and visualization have been developed for this purpose. However, most of these tools use model-based statistical methods which assume that the users know the hemodynamic response (HR) for their paradigm in advance and can specify a reasonable HR model. Often, however, accurate or reasonable response HR models are unavailable. An alternative data-driven method, infomax ICA (McKeown et al., 1998), does not require that an a priori HR model, instead deriving HRs of spatially independent components of the entire data set from the higher-order statistics of the data themselves. FMRLAB is a toolbox running under Matlab containing necessary components for data-driven fMRI data analysis using the highly reliable infomax ICA algorithm (Bell & Sejnowski, 1995), normalized (Amari, 1999), extended (Lee, Girolami and Sejnowski, 1999) and automated by Makeig et al. FMRLAB has been developed under Matlab 6.1 running on Red Hat Linux. FMRLAB Features * Graphic user interface * Flexible data importing * Interactive data plotting * Computationally efficient * Defined FMRI data structure * Independent component browser * Smooth, transparent component exporting and spatial normalization process * Interface with other software for further analysis or visualization. * SPM-style component plots (MIP, 2-D slice overlay and 3-D)

Proper citation: FMRLAB (RRID:SCR_005164) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/freesurf_r/

A software package which contains tools for doing group analysis of FreeSurfer surface data using the general linear model in R (lm). Results can be rendered in FreeSurfer freeview or AFNI SUMA. Plots for selected vertices can be rendered in R with ggplot2.

Proper citation: freesurfR (RRID:SCR_014110) Copy   

•   Source: SciCrunch Registry

http://www.debian.org

Debian is Linux distribution composed of free and open source software, developed by community supported Debian Project, which was established by Ian Murdock on August 16, 1993.Debian comes with over 59000 packages (precompiled software that is bundled up in nice format for easy installation on your machine), package manager (APT), and other utilities that make it possible to manage thousands of packages on thousands of computers as easily as installing single application.

Proper citation: Debian (RRID:SCR_006638) Copy   

•   Source: SciCrunch Registry