Higher-order contrast functions improve performance of independent component analysis of fMRI data
1Pediatric Neuroimaging Research Consortium, Children's Hospital Medical Center, Cincinnati, Ohio, USA. Vince.Schmithorst@cchmc.org
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.
