Allows users to work about magnetic resonance imaging (MRI) brain imaging data. FSL can realize functional magnetic resonance imaging (FMRI) analysis (brain extraction, smoothing, statistics, registration). This tool can analyze a wide range of MR modalities (task FMRI, resting FMRI, ASL, diffusion, structure), and can be easily scripted and run over computing clusters.
Assists in identifying and selecting the region of interest (ROI). In AFNI, the resting-state functional magnetic resonance imaging (rsfMRI) echo-planar image (EPI) preprocessing sequence consists of several steps: (1) alignment of EPI centers to a standard atlas; (2) elimination of the first two EPIs; (3) outlier detection; (4) application of time-shift correction; (5) alignment of each EPI to the least motion distorted volume; or (6) alignment to the anatomical image and nonlinear warp to a standard space.
Applies classifier-based analysis techniques to functional magnetic resonance imaging (fMRI) datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine-learning packages. It provides a collection of common algorithms and processing steps that can be combined. The software code is tested to be portable across multiple platforms.
Allows users to investigate relationships between brain networks. The FNC Toolbox is a Matlab software that extends the analysis run by the GIFT toolbox. The application is able to compute Granger Causality or the highest correlated lag between components from a GIFT output file. It was tested for the identification of pairs of independent components that are showing changes in temporal correlation between healthy controls and schizophrenic patients.
Processes and investigates large anatomical and functional magnetic resonance imaging (MRI) data sets. AnalyzeFMRI can be used for temporal and spatial independent component (IC) analysis. It aims to study the intrinsic structure of data and alleviate the need for explicit a priori about the neural responses. This tool supports the computation of contiguous clusters of locations in a 3D array.
Evaluates states, input and parameters of stochastic continuous-discrete state-space models. SCKS is a toolbox that consists of two main algorithms: square-root Cubature Kalman Filter and square-root Rauch-Tang-Striebel smoother (SCKF-SCKS). The application can be applied to the inversion of any nonlinear continuous dynamic model that is formulated with stochastic differential equation and is especially designed for the assessment of the underlying neuronal signal.
Provides a method for multivariate functional Magnetic Resonance Imaging (fMRI) data decoding. Time-domain decoding is an application which allows for decoding with smaller inter-stimuli intervals (ISIs). It is also flexible to hemodynamic response functions (HRFs) variations. The method is modular in nature, with weakly coupled spatial and temporal steps, and offers interpretability in the time domain.
Reduces significantly the effort required to construct specifically tailored, interactive applications for medical image analysis. MITK allows an easy combination of algorithms developed by ITK with visualizations created by VTK and extends these two toolkits with those features, which are outside the scope of both. It adds support for complex interactions with multiple states as well as undo-capabilities, a very important prerequisite for convenient user interfaces.
Interfaces with existing software for analysis of neuroimaging data and comparative development of algorithms. Nipype is an open-source, community-developed, Python-based software package that consists of three components: (1) interfaces to external tools providing a unified way for setting inputs, executing, and retrieving outputs; (2) a workflow engine for creating analysis pipelines; and (3) plug-ins that execute workflows either locally or in a distributed processing environment.
Furnishes a collection of resting-state functional magnetic resonance imaging (RS-fMRI) analyses. REST can divide a whole brain 4D dataset into several smaller 4D datasets and then, rebuilds the whole brain 4D dataset. Using this strategy, this tool is able to deal with datasets of over 1000-time points on most personal computers. It implements calculation methods such as functional connectivity.
Allows users to classify depressed patients and healthy controls based on functional magnetic resonance imaging (fMRI) data. The SCoRS classification can be applied to two problems: discriminating tasks and discriminating groups. This software is able to identify core brain regions associated with psychiatry diseases, such as Anterior Cingulate and Basal Ganglia.
Represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights.
Allows researchers to carry out automated analysis of human grid cell codes in functional magnetic resonance imaging (fMRI) data. The GridCAT performs all analyses, from estimation and fitting of the grid code in the general linear model, to the generation of grid code metrics and plots. It provides a graphical user interface for researchers less comfortable with programming; researchers confident with programming, however, can edit the open-source code accompanying the GridCAT to implement their own analysis pipelines.
Offers a method for applying regularized kernel canonical correlation analysis (CCA) between several datasets. Pyrcca is an open source software that displays a cross-validation method for hyperparameter selection. The application can run the CCA with and without regularization and kernelization. It can be used to quantify similarity in datasets, analyze timeseries data and predict novel data by using cross-dataset mapping.
Assists users in functional magnetic resonance imaging (fMRI) research. IclinfMRI consists of a five-modules program able to perform interactive rs-fMRI mapping and visualization of sites with potential NVU in fMRI results. Besides, the application includes utilities to convert DICOM files towards the NIfti format and to lastly export the analyzed images as a series of files. Results can be exploited into a surgical navigation system with application on presurgical fMRI planning.
Characterizing the role in overall brain activation of spatially scaled periodic patterns with given temporal recurrence rates. 4D FFT Toolbox is a Matlab software that focuses on the computation of is the spatiotemporal spectral profile (STSP). The application is able to distinguish populations of interest among large balanced multi-site resting functional magnetic resonance imaging (fMRI) dataset. It was tested on a dataset of fMRI data including schizophrenia patients and healthy controls.
An open-source MATLAB toolbox with user-friendly graphical user interfaces, implementing both dynamic functional and effective connectivity for tracking brain dynamics from functional MRI. We provided two strategies for dynamic analysis: (1) the commonly utilized sliding-window analysis and (2) the flexible least squares based time-varying parameter regression strategy. The toolbox also implements multiple functional measures including seed-to-voxel analysis, region of interest (ROI)-to-ROI analysis, and voxel-to-voxel analysis.
Assists users to compare a collection of reference spectrum to other spectrum from one or more mzXml files. SpectrumFinder is a program that finds similarities between a tandem mass spectrometry (MS/MS) spectrum of reference and other MS/MS spectrums from the same instrument and the same biological sample. It searches similarities between MS/MS spectrums by using the "cosine similarity".
Serves for investigating inter-regional functional connectivity in event-related fMRI data. BASCO can be useful for slow event-related designs with trial duration longer than the repetition time (TR). This tool focuses on functional connectivity patterns related to specific experimental manipulations. This allows investigating task-related data from a network perspective using graph theory and beta-series correlations.
Facilitates the use of advanced deconvolution models and spline regression in event-related brain potentials (ERPs) research. Unfold is programmed in a modular fashion, meaning that intermediate analysis steps can be readily inspected and modified by the user if needed. It is also fully documented, designed to be modular, can employ regularization, can model both linear and nonlinear effects using spline regression,
Allows Markov Chain Monte Carlo (MCMC) sampling of population receptive field (pRF)/hemodynamic parameter distributions. QPrf is a Bayesian approach to joint estimation of pRF and hemodynamic parameters full posterior distributions using a forward signal generation model and MCMC sampling.
Allows to visualize perceptual and mental content from human brain activity. Deep image reconstruction is a method that merges visual features from several layers of a deep neural network (DNN). The algorithm translates the activity patterns into DNN features and sends those to a reconstruction algorithm. In addition, it can be combined with a deep generator network (DGN) to generate natural-looking images.
Offers a platform for comparing spatial activation. GIPC provides a graphic interface for comparing group spatial activations amongst different study groups as well as similarities of subjects in a targeted group. The application is able to determine the blood-oxygenation-level dependent (BOLD) correlations between the same voxel among all participants within a group. It was tested on a study comparing schizophrenics and healthy controls.
Hosts heterogeneous tools dedicated to neuroimaging research. BrainVISA aims to help researchers in developing new neuroimaging tools, sharing data and distributing software. It offers a way to define viewers which may use any visualization software. Thanks to its data management functions, the tool can define the data types handled by the software, associate key attributes for indexation, and filename patterns to make the link between the filesystem and the database schema.
Intends to analyze experimental data in time-series. Nitime is built around numerical algorithms, including coherency analysis, which provides analysis for time and spectral domains. It aims to help in manipulation of neuroscientific experiments data, from single-cell recordings to functional magnetic resonance imaging (fMRI). The software also includes objects to represent time-series, auxiliary objects with interface to the numerical machinery and eases common analysis tasks.
Investigates functional magnetic resonance imaging (fMRI) and diffusion tensor images (DTI) with graph analytical functions. MNET starts by defining unique and homogeneous nodes from the continuous medium of the cortex. It implements several visualization techniques, 3D-visualization containing edge weights, node degree, and time series plot of each node, colored adjacency matrices, and hierarchical edge bundle display.
Performs time delay analysis on functional imaging data. rapidtide provides a suite of python modules to find time lagged correlations between the voxelwise time series and other time series. This application identifies, quantifies and visualizes physiological noise signals transmitted by blood. It can serve as a method for quantifying hemodynamic parameters or as a means of removing them from data sets to improve the quality of functional magnetic resonance imaging (fMRI) data.
Highlights brain activity patterns. CCA-fMRI supplies a set of methods for investigating functional magnetic resonance imaging (fMRI) data by the use of canonical correlation analysis (CCA). This application first builds a low pass filter to then enables the comparison between a pre-computed activation pattern to the targeted filtered voxels in order to determine their effective level of activation. This software can be run through SPM2 and SPM5.
Allows detection of changes in brain activity from neuroimaging data. The SPM purpose is to analyze brain imaging data sequences. The analyzed sequences can be time-series from the same subject or a series of images from different cohorts.
Enables group inferences from functional magnetic resonance imaging (fMRI) data using Independent Component Analysis (ICA). GIFT implements several algorithms allowing independent component analysis and blind source separation of group (and single subject) functional magnetic resonance imaging data. The software can be used for running both single subject and single session analysis as well as group analysis.
Infers functional connectivity by analyzing the peak trains of spiking neuronal signals. ToolConnect implements correlation and information theory based core algorithms. It contains several modules in the windows form embodiment and allows the user to easily manipulate and analyze data, while providing computational efficiency and accuracy. This tool is able to return both numerical and graphical results. It has been designed to be adapted, modified and extended by the interested researchers.
Investigates resting-state functional magnetic resonance imaging (R-fMRI) data including those related to animals. DPABI is a set of functionalities including features for (i) head motion control; (ii) standardization to decrease sources of nuisance variation; (iii) test-retest (TRT) reliability; (iv) quality control; and (v) dedicated rat or monkey data analysis pipelines, coupled to an implementation of the DPARSF software. It also includes options for performing statistical analysis, an MRI viewer and several image utilities such as a converter a smoothing function.
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