Higher‐order contrast functions improve performance of independent component analysis of fMRI data

Purpose

To evaluate the performance of different contrast functions used in Independent Component Analysis (ICA) of functional magnetic resonance imaging (fMRI) data at low signal‐to‐noise ratio (SNR), present in fMRI paradigms such as resting‐state acquisitions.

Materials and Methods

Metrics were defined to estimate both the accuracy and robustness of contrast functions under varying source distributions. Simulations were performed to compare the performance of lower‐order (such as ln cosh) to higher‐order (such as kurtosis) contrast functions using Laplacian source distributions corrupted with Gaussian noise. The ln cosh and kurtosis contrast functions were also compared using resting‐state fMRI data from 10 normal adult volunteers.

Results

Higher‐order contrast functions provided superior performance compared to lower‐order contrast functions in the evaluation of metrics and via the simulations in the presence of a significant amount of noise. The performance of kurtosis was not statistically significantly different from that of a theoretically optimized contrast function. The choice of contrast function was found to result in substantial (R < 0.9) differences in 40% of the components found from the resting‐state fMRI data.

Conclusion

The use of higher‐order contrast functions, such as kurtosis, may provide superior performance in ICA analysis of fMRI data with low SNR. J. Magn. Reson. Imaging 2009;29:242–249. © 2008 Wiley‐Liss, Inc.