SimTB, a simulation toolbox for fMRI data under a model of spatiotemporal separability. We introduce SimTB, a MATLAB toolbox designed to simulate functional magnetic resonance imaging (fMRI) datasets under a model of spatiotemporal separability. The toolbox meets the increasing need of the fMRI community to more comprehensively understand the effects of complex processing strategies by providing a ground truth that estimation methods may be compared against. SimTB captures the fundamental structure of real data, but data generation is fully parameterized and fully controlled by the user, allowing for accurate and precise comparisons. The toolbox offers a wealth of options regarding the number and configuration of spatial sources, implementation of experimental paradigms, inclusion of tissue-specific properties, addition of noise and head movement, and much more. A straightforward data generation method and short computation time (3–10 seconds for each dataset) allow a practitioner to simulate and analyze many datasets to potentially understand a problem from many angles. Beginning MATLAB users can use the SimTB graphical user interface (GUI) to design and execute simulations while experienced users can write batch scripts to automate and customize this process. The toolbox is freely available at http://mialab.mrn.org/software together with sample scripts and tutorials.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Boukouvalas, Zois; Levin-Schwartz, Yuri; Calhoun, Vince D.; Adalı, Tülay: Sparsity and independence: balancing two objectives in optimization for source separation with application to fMRI analysis (2018)
- Peró-Cebollero, Maribel; Guàrdia-Olmos, Joan; Mancho-Fora, Núria: A systematic review of simulation procedures for fMRI connectivity studies (2018)
- Warnick, Ryan; Guindani, Michele; Erhardt, Erik; Allen, Elena; Calhoun, Vince; Vannucci, Marina: A Bayesian approach for estimating dynamic functional network connectivity in fMRI data (2018)
- Calhoun, Vince D.; Allen, Elena: Extracting intrinsic functional networks with feature-based group independent component analysis (2013)