Abstract
To make a quantitative comparison of temporal cluster analysis (TCA) and independent component analysis (ICA) techniques in detecting brain activation by using simulated data and in vivo event-related functional MRI (fMRI) experiments. A single-slice MRI image was replicated 150 times to simulate an fMRI time series. An event-related brain activation pattern with five different levels of intensity and Gaussian noise was superimposed on these images. Maximum contrast-to-noise ratio (CNR) of the signal change ranged from 1.0 to 2.0 by 0.25 increments. In vivo visual stimulation fMRI experiments were performed on a 1.9 T magnet. Six human volunteers participated in this study. All imaging data were analyzed using both TCA and ICA methods. Both simulated and in vivo data have shown that no statistically significant difference exists in the activation areas detected by both ICA and TCA techniques when CNR of fMRI signal is larger than 1.75. TCA and ICA techniques are comparable in generating functional brain maps in event-related fMRI experiments. Although ICA has richer features in exploring the spatial and temporal information of the functional images, the TCA method has advantages in its computational efficiency, repeatability, and readiness to average data from group subjects
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.