We support boolean queries, use +,-,<,>,~,* to alter the weighting of terms
A collection of software tools for high dimensional brain imaging genomics. These tools are designed to perform comprehensive joint analysis of heterogeneous imaging genomics data. HDBIG-SR is an HDBIG toolkit for sparse regression while HDBIG-SCCA is an HDBIG toolkit for sparse association.
A multi-day event hosted by the Organization for Human Brain Mapping which features collaborative and open neuroscience projects in data analysis and methods development. Locations change annually.
A software package which performs high-dimensional warping of brain images. Standard voxel-based analysis can be applied to these tissue density maps, in order to examine regional volumetrics, effects of disease, or correlations with clinical measurements.
A user-friendly graphical-user-interface (GUI)-based toolbox (MATLAB) for comprehensive graph-theoretical analyses of brain connectivity, including network construction and characterization, statistical analysis on network topological measures, and interactive exploration of results.
A MATLAB toolbox for denoising task-based fMRI data. It derives noise regressors from voxels unrelated to the experimental paradigm and uses these regressors in a general linear model (GLM) analysis of the data. The technique only requires a design matrix indicating the experimental design and an fMRI dataset.
Software Matlab toolbox for directed functional connectivity analysis of fMRI BOLD signal from predefined regions of interest. It recovers true structure of connections and estimates weights attributed to each connection. Obtains patterns at group and individual levels.
An MRI resource which provides age-appropriate images of children. It includes an average, age-appropriate T1-weighted image, constructed from 130 typically developing children ages 6-to-10 and a set of 32 resting-state ICA components. These components were generated from 494 typically developing children, ages 6-to-10 years old, using the MELODIC ICA tool, bootstrapped with 1000 resamples. Both of these resources are described in detail in a manuscript submitted for publication.
A multivariate method for fMRI data analysis based on generalized canonical correlation analysis (gCCA) to maximize SPM reproducibility without adopting any model for the hemodynamic response or other temporal brain responses. For multiple subjects, gCCA explores a broad range of temporal responses in fMRI time-series space while maximizing the mean of correlation coefficients between the pair-wise spatial maps of the subjects.
A toolbox for a point-process derived GLM analysis of eye tracking data in Matlab. Data loading, model specification, fitting and review are organized into a sequence of events, each of which is handled by a separate module in the toolbox. The graphical interface was created using the Matlab graphical user interface development environment.
A functional connectivity analysis tool for near-infrared spectroscopy data. Its functions include preprocessing, quality control, FC calculation and network analysis.
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.
A project which aims to simplify the preparation of accurate electromagnetic head models for EEG forward modeling. It builds off of the seminal SimNIBS tool for electromagnetic field modelling of transcranial magnetic stimulation and transcranial direct current stimulation. Human skin, skull, cerebrospinal fluid, and brain meshing pipelines have been rewritten with Nipype to ease access parallel processing and to allow users to start/stop the workflows. Conductivity tensor mapping from diffusion-weighted imaging is also included.
A tool which offers a fast algorithm for computing myelin maps from multiecho T2 relaxation data using parallel computation with multicore CPUs and graphics processing units (GPUs). The tool also provides non-local spatial regularization to produce more accurate and reliable myelin maps for noisy T2 relaxation data.
An R package for descriptive (i.e., fixed-effects) multivariate analysis with singular value decomposition.
A toolbox developed for multi-channel time-frequency analysis of event related activity of EEG and MEG data. It provides tools for data analysis and visualization of the most commonly used measures of time-frequency transformed event related data as well as data decomposition through non-negative matrix and multi-way (tensor) factorization. The decompositions provided can accommodate additional dimensions like subjects, conditions or repeats and as such they are perfected for group analysis. The toolbox enables tracking of phase locked activity from one channel-time-frequency instance to another as well as tools for artifact rejection in the time-frequency domain.
A spatial normalization and atlas construction toolkit designed to support the manipulation of diffusion-tensor images (DTI) with special cares taken to respect the tensorial nature of the data. It implements a registration algorithm that drives the alignment of white matter tracts by matching the orientation of the underlying fiber bundle at each voxel.
A Matlab implementation for efficient permutation testing by using matrix completion.
A longitudinal study of late-life depression at Duke University. There are 281 depressed subjects and 154 controls included. An MR scan of each subject was obtained every 2 years for up to 8 years (total of 1093 scans). Clinical assessments occurred more frequently and consists of a battery of psychiatric tests, including several depression-specific tests.
A Matlab package which contains six denoising filters and a noise estimation method for 4D DWI. The package includes nonlocal means, local PCA and Oracle DCT methods. Based on image redundancy and/or sparsity, the proposed filters provide efficient denoising while preserving fine structures.
A tool for visualizing displacement fields estimated in association with image registration. Based on the displacement vector field, a mesh is generated for visualization. The mesh can be color mapped with the jacobian determinant at each point for better localization of regions that undergo compression or expansion. Other key features include: view synchronization, adjustable mesh resolution, and conversion from deformation and HAMMER displacement fields.