Curator Dashboard

Software for source analysis and dipole localization in EEG and MEG research. BESA Research has been developed on the basis of 20 years experience in human brain research by Michael Scherg, University of Heidelberg, and Patrick Berg, University of Konstanz. BESA Research is a highly versatile and user-friendly Windows program with optimized tools and scripts to preprocess raw or averaged data for source analysis. All important aspects of source analysis are displayed in one window for immediate selection of a wide range of tools. BESA Research provides a variety of source analysis algorithms, a standardized realistic head model (FEM), and allows for fast and easy hypothesis testing and integration with MRI and fMRI.

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• SciCrunch
• 13 years ago - by Anonymous

Software tool (excecutable and source code in C and C++) to correct distortions in diffusion MR images that are generated by main magnetic field inhomogeneities and eddy current induced fields generated from the direction-dependent diffusion encoding

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• SciCrunch
• 13 years ago - by Anonymous

Dataset of structural MR images of 70 subjects collected during 2008-2010 across a wide range of ages. The dataset also contains resting state fMRI for most subjects. The structural images are T1 weighted, T2 weighted-FLAIR, 25 direction DTI, and the T1 mapping DESPOT [1] sequence. Reconstructed T1 maps for each subject are also available. The aquisition protocol was designed to study structural differences between young and older adults including both shape and intensity changes. Anonymized DICOM image sessions and processed images for each subject are available. The data is licensed under the Creative Commons Attribution License. It may be used freely for commercial, academic, or other use, as long as the original source is properly cited. http://www.bsl.ece.vt.edu/index.php?page=ara-dataset

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• SciCrunch
• 13 years ago - by Anonymous

A fully automated algorithm which works within SPM8 to segment the lateral ventricles from structural MRI images. The algorithm has been validated in infants, adults and patients with Alzheimer's disease (ICC>0.95). ALVIN is insensitive to different scanner sequences (ICC>0.99, 8 different sequences 1.5T and 3T) and sensitive to changes in ventricular volume. Processing time is approx 10mins per subject.

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• SciCrunch
• 13 years ago - by Anonymous

A completely automatic algorithm for artifact identification and removal in EEG data. ADJUST is based on Independent Component Analysis (ICA), a successful but unsupervised method for isolating artifacts from EEG recordings. ADJUST identifies artifacted ICA components by combining stereotyped artifact-specific spatial and temporal features. Features are optimised to capture blinks, eye movements and generic discontinuities. Once artifacted IC are identified, they can be simply removed from the data while leaving the activity due to neural sources almost unaffected.

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• SciCrunch
• 13 years ago - by Anonymous

An opensource software for image analysis, processing and visualization. It provides convenient visualization tools for 2D and 3D images and it is highly extensible through its own scripting language. At visualization level, AMILab includes a 2D/3D image viewer, a 3D polygon viewer based on OpenGL, a 2D Curve viewer to visualize 2D curves, histograms and color/opacity transfer functions, and a GPU-enabled raycasting script for Volume Rendering based on VTK. The software includes an automatic C++ wrapping system which permits fast development of new visualization tools and image processing algorithms. This wrapping system currently wraps about 200 classes from wxwidgets library and about 100 classes from VTK.

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• SciCrunch
• 13 years ago - by Anonymous

A command line program for image registration by using different methods including Thirion and diffeomorphic demons algorithms. The function takes in a template image and a target image along with other optional parameters and registers the template image onto the target image. The resultant deformation fields and metric values can be written to a file. The program uses the Insight Toolkit (www.ITK.org) for all the computations, and can operate on any of the image types supported by that library. This a an ITK based implementation of various forms of Thirion Demons based registration (including diffeomorphic demons registration originating from Tom Vercauteren at INRIA ).

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• SciCrunch
• 13 years ago - by Anonymous

Tools to make easier on using spm, pipedream, dti-tk, and other softwares to analyze t1 or dti images.

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• SciCrunch
• 13 years ago - by Anonymous

A data analysis environment for diffuse optical tomography (DOT) functional neuroimaging data. Developed to process data from steady-state time-series measurements, it allows for maximal flexibility in the number and positions of optodes. The central component is an application called NAVI. Features include: # An electronic ledger (records metadata for all data transformations). # Data conditioning (e.g., frequency-filtering, selection of data on the basis of signal-to-noise ratio.) # 2D or 3D image formation and display. # Interpretation: atlas-based mapping; automated anatomical labeling; GLM; data-driven methods (e.g., PCA, ICA); model-based (e.g., dynamic causal modeling) and data-driven (e.g., correlation) connectivity analysis. Another important component is the Brain Model Generator, which includes FEM meshes for all parts of the head accessible to DOT measurements. The user can input the numbers of optodes, and manually specify their locations or input tracking-system data.

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• SciCrunch
• 13 years ago - by Anonymous

A web tool for the identification of microRNAs and their isomiRs, as well as differential expression from NGS datasets.

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• SciCrunch
• 13 years ago - by Anonymous

Constrained Principal Component Analysis (CPCA) combines regression analysis and principal component analysis into a unified framework. This method derives images of functional neural networks from singular-value decomposition of BOLD signal time series, and allows derivation of images when the analyzed BOLD signal is constrained to the scans occurring in peristimulus time, using all other scans as baseline. CPCA provides allows (1) determination of multiple functional networks involved in a task, (2) estimation of the pattern of BOLD changes associated with each functional network over peristimulus time points, (3) quantification of the degree of interaction between these multiple functional networks, and (4) a statistical test of the degree to which experimental manipulations affect each functional network. fMRI CPCA provides all results in matlab.mat file format, as well as writing images in analyze format for all components, rotated and unrotated.

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• SciCrunch
• 13 years ago - by Anonymous

They demonstrate and provide R code that can classify between groups of fMRI scans based on functional network connectivity differences, requiring only 4 lines of code to be altered. In addition, they include a detailed article explaining the methods behind and motivations of this tool. This code can also be altered to perform connectivity analysis and classification using ROI based methods by reading in distance arrays previously created. They run Independent component analysis (ICA) on fMRI data to establish functional networks, measure the functional connectivity between these networks using the temporal cross-correlations between independent component to create a distance matrix and indicating the networking. Connectivity properties are used as a feature matrix for an SVM classifier. Collectively, this project provides and explains both methods and code to perform functional network connectivity and fMRI SVM classi?cation.

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• SciCrunch
• 13 years ago - by Anonymous

A Matlab toolbox that allows computation of task-related functional connectivity between multiple pairs of regions. Task-related functional connectivity is computed using the correlational psychophysiological interaction (cPPI) methodology described in Fornito et al. (2012) PNAS, 109: 12788-12793. The toolbox assumes that first-level design matrices have been specified and estimated using SPM5 or later. It takes as input these design matrices as well as user-extracted regional time courses and returns a matrix of pair-wise, task-related functional connectivity for each participant. The method is scalable to large networks comprising hundreds of regions and is well-suited to graph theoretic analyses and functional connectomics. One modifiable script, cPPI_master.m, can be used to run the analysis for an entire sample of participants.

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• SciCrunch
• 13 years ago - by Anonymous

About 1.2GB of anonymized imaging data of many different file formats used by the BRAINS suite of tools (BRAINSFit, GTRACT, BRAINS, BRAINSTracer... and others) as a common set of anonymized data for nightly regression testing.

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• SciCrunch
• 13 years ago - by Anonymous

Human DTI brain atlases have been generated at UNC-Chapel Hill for several age groups, by iterative joint deformable registration of training datasets into a single unbiased DTI average image. Atlases packages include an atlas DTI tensor image, atlas DTI property images (FA, MD, AD, RD), and single tensor tractography based fiber tracts of major tracts with related 3D planes for fiber profile information: genu, splenium, anterior and posterior limb of internal capsule, uncinate fasciculus.

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• SciCrunch
• 13 years ago - by Anonymous

The methodology and applications of task independent fluctuation measures including: connectivity maps of fMRI resting state scans, research using EEG/MEG/PET etc, methods to remove non-neural fluctuations, and applications to clinical populations.

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• SciCrunch
• 13 years ago - by Anonymous

While the traditional temporally concatenated Group ICA (TC-GICA) adopting three steps of PCA reduction, it could result in inconsistent and variable components when different subject orders were used, both for the group- and individual-level results. Such instability can further cause instable and thus unreliable statistical results. Subject Order-Independent Group ICA (SOI-GICA) aims to fix this problem by producing stable and reliable GICA results. For details please see the paper Subject Order-Independent Group ICA (SOI-GICA) for Functional MRI Data Analysis (Zhang et al., 2010, NeuroImage)(http://dx.doi.org/10.1016/j.neuroimage.2010.03.039). MICA is the toolbox inplemented SOI-GICA for convenience of usage.

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• SciCrunch
• 13 years ago - by Anonymous

Script which points browser to Nathan Kline Institute (NKI) Rockland Sample.

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• SciCrunch
• 13 years ago - by Anonymous

An open source implementation of a non-rigid groupwise registration method. This project is implemented by Serdar K Balci (serdar at csail.mit.edu) and supervised by Polina Golland and William M. Wells All metrics are implementing in a multi-threaded fashion. The algorithm will run faster on computers with multiple CPU''s.

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• SciCrunch
• 13 years ago - by Anonymous

Tool that associates localized white matter (WM) lesions with disruptions in gray matter connectivity as a step toward understanding the lesions? functional implications. A Tractogram Reference Set (TRS), i.e. collections of white matter fibers, is constructed from 73 normal healthy individuals and coregistered to a common space (MNI). The NeMo Tool uses the TRS to assess structural network disruption due to a particular WM lesion mask on a region and network-wise level. This tool is an easy way for researchers and clinicians to investigate changes in the structural brain network without having to perform tractography on their own normal data or on diseased/injured brains where the results may not represent the underlying physiology.

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• SciCrunch
• 13 years ago - by Anonymous