Simulates the dynamics of large-scale brain networks with biologically realistic connectivity. The Virtual Brain uses tractographic data (DTI/DSI) to generate connectivity matrices and build cortical and subcortical brain networks. The connectivity matrix defines the connection strengths and time delays via signal transmission between all network nodes. Various neural mass models are available in the repertoire of The Virtual Brain and define the dynamics of a network node. Together, the neural mass models at the network nodes and the connectivity matrix define the Virtual Brain. The Virtual Brain simulates and generates the time courses of various forms of neural activity including Local Field Potentials (LFP) and firing rate, as well as brain imaging data such as EEG, MEG and BOLD activations as observed in fMRI.
Generates a large database of mappings between neural and cognitive states. Neurosynth uses text mining, meta-analysis and machine learning techniques. It can automatically conduct large-scale, high-quality neuroimaging metaanalyses, address long-standing inferential problems in the neuroimaging literature, and support accurate ‘decoding’ of broad cognitive states from brain activity in both entire studies and individual human subjects.
Offers a platform able to simulate functional magnetic resonance imaging (fMRI) datasets. SimTB aims to facilitate the testing of several analytic method thanks to a model of spatiotemporal separability. The application can be run through both a graphic or a command line interface according to the users’ needs. The program contains several functionalities such as a multiple visualization of parameters and tissue maps or an automated source matching between simulated and estimated spatial maps (SMs) derived from an analysis.
Provides an application for brain activation explorer. BAX is a toolbox that integrates a graphical user interface (GUI) to assist users with the specification of input parameters and the visualization of results. It can be used for the dynamic analysis of fMRI datasets. This application uses the general linear model as the basis of the analysis. It can also be used to perform correlation analysis.
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