Vincent J Schmithorst1. 1. Pediatric Neuroimaging Research Consortium, Children's Hospital Medical Center, Cincinnati, Ohio, USA. Vince.Schmithorst@cchmc.org
Abstract
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.
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.