Simulating complex fMRIlike sources
In order to test the performance of separation algorithms for complexvalued data, we generate a simulated complex fMRIlike set of components and mix them with a set of time courses to obtain a simulated fMRIlike dataset. The sources are generated based on the basic knowledge of the statistical characteristics of the underlying neuronal sources. A brief description on the properties of fMRI data is available here.We generate eight complexvalued spatial maps to simulate the fMRI sources and the corresponding time courses. The magnitudes of spatial maps and time courses of each components are as shown in the figure below. In an fMRI experiment, the phase difference induced by the task activation is typically less than pi/9 (see [1, 2]). Therefore, we keep the phase of each pixel uniformly distributed in the range [pi/18, pi/18]. The phase of each complexvalued time point is generated proportional to its magnitude, but is again restricted to a small range, which in our case is [pi/18, pi/18]. The spatial sources are arranged into onedimensional vectors and mixed by the corresponding time courses as the spatial ICA model for fMRI data. References:
 F. G. Hoogenrad, J. R. Reichenbach, E. M. Haacke, S. Lai, K.Kuppusamy, and M. Sprenger, ''In vivo measurement of changes in venousbloodoxygenation with high resolution functional MRI at .95 Tesla by measuring changes in susceptibility and velocity,'' Magn. Reson. Med., vol.39, pp. 97–107, 1998.
 V. D. Calhoun, T. Adali, G. D. Pearlson, P. C. M. van Zijl, and J. J. Pekar, "Independent component analysis of fMRI data in the complex domain," Magnetic Resonance in Medicine, vol. 48, issue 1, pp. 180192, July 2002.
Simulated complex fMRIlike sources: 
Magnitude images of the sources along with their time courses 
Publication in which this set of simulated sources has been utilized:
 W. Xiong, Y.O. Li, H. Li, T. Adali, and V. D. Calhoun, "On ICA of complexvalued fMRI: Advantages and order selection," in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing (ICASSP), Las Vegas, Nevada, April 2008. .
Resources:

Simulated complex fMRI dataset: Matlab code