SimTB, a simulation toolbox for fMRI data under a model of spatiotemporal separability

被引:161
作者
Erhardt, Erik B. [1 ,2 ]
Allen, Elena A. [2 ]
Wei, Yonghua [1 ]
Eichele, Tom [3 ,5 ]
Calhoun, Vince D. [2 ,4 ]
机构
[1] Univ New Mexico, Dept Math & Stat, Albuquerque, NM 87131 USA
[2] Mind Res Network, Albuquerque, NM USA
[3] Univ Bergen, Dept Biol & Med Psychol, Bergen, Norway
[4] Univ New Mexico, Dept Elect & Comp Engn, Albuquerque, NM 87131 USA
[5] Haukeland Hosp, Dept Neurol, Clin Neurophysiol Sect, N-5021 Bergen, Norway
基金
美国国家科学基金会;
关键词
Simulation; fMRI; Group analysis; INDEPENDENT COMPONENT ANALYSIS; FUNCTIONAL CONNECTIVITY; BLOOD-FLOW; BRAIN; NETWORKS; MOTION; ALGORITHMS; DIMENSIONALITY; ACTIVATION; NOISE;
D O I
10.1016/j.neuroimage.2011.11.088
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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.mm.org/software together with sample scripts and tutorials. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码:4160 / 4167
页数:8
相关论文
共 50 条
[11]  
Bullmore ET, 2001, HUM BRAIN MAPP, V12, P61, DOI 10.1002/1097-0193(200102)12:2<61::AID-HBM1004>3.0.CO
[12]  
2-W
[13]   Dynamics of blood flow and oxygenation changes during brain activation: The balloon model [J].
Buxton, RB ;
Wong, EC ;
Frank, LR .
MAGNETIC RESONANCE IN MEDICINE, 1998, 39 (06) :855-864
[14]   A model for the coupling between cerebral blood flow and oxygen metabolism during neural stimulation [J].
Buxton, RB ;
Frank, LR .
JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM, 1997, 17 (01) :64-72
[15]   A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data [J].
Calhoun, Vince D. ;
Liu, Jingyu ;
Adali, Tuelay .
NEUROIMAGE, 2009, 45 (01) :S163-S172
[16]   Performance of blind source separation algorithms for fMRI analysis using a group ICA method [J].
Correa, Nicolle ;
Adali, Tulay ;
Calhoun, Vince D. .
MAGNETIC RESONANCE IMAGING, 2007, 25 (05) :684-694
[17]   An empirical comparison of SPM preprocessing parameters to the analysis of fMRI data [J].
Della-Maggiore, V ;
Chan, W ;
Peres-Neto, PR ;
McIntosh, AR .
NEUROIMAGE, 2002, 17 (01) :19-28
[18]   A quantitative comparison of functional MRI cluster analysis [J].
Dimitriadou, E ;
Barth, M ;
Windischberger, C ;
Hornik, K ;
Moser, E .
ARTIFICIAL INTELLIGENCE IN MEDICINE, 2004, 31 (01) :57-71
[19]   Development of a functional magnetic resonance imaging simulator for modeling realistic rigid-body motion artifacts [J].
Drobnjak, Ivana ;
Gavaghan, David ;
Suli, Endre ;
Pitt-Francis, Joe ;
Jenkinson, Mark .
MAGNETIC RESONANCE IN MEDICINE, 2006, 56 (02) :364-380
[20]   Comparison of Multi-Subject ICA Methods for Analysis of fMRI Data [J].
Erhardt, Erik Barry ;
Rachakonda, Srinivas ;
Bedrick, Edward J. ;
Allen, Elena A. ;
Adali, Tuelay ;
Calhoun, Vince D. .
HUMAN BRAIN MAPPING, 2011, 32 (12) :2075-2095