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Low Frequency Fluctuation Component Analysis in Active Stimulation fMRI Paradigm  

Na, Sung-Min (Department of Medical and Biological Engineering, Kyungpook National University)
Park, Hyun-Jung (Jeju National University College of Veterinary Medicine)
Chang, Yong-Min (Department of Medical and Biological Engineering, Kyungpook National University)
Publication Information
Investigative Magnetic Resonance Imaging / v.14, no.2, 2010 , pp. 115-120 More about this Journal
Abstract
Purpose : To separate and evaluate the low frequency spontaneous fluctuation BOLD signals from the functional magnetic resonance imaging data using sensorimotor active task. Materials and Methods : Twenty female archery players and twenty three control subjects were included in this study. Finger-tapping task consisted of three cycles of right finger tapping, with a subsequent 30 second rest. Blood oxygenation level-dependent (BOLD) data were collected using $T2^*$-weighted echo planar imaging at a 3.0 T scanner. A 3-D FSPGR T1-weighted images were used for structural reference. Image processing and statistical analyses were performed using SPM5 for active finger-tapping task and GIFT program was used for statistical analyses of low frequency spontaneous fluctuation BOLD signal. Results : Both groups showed the activation in the left primary motor cortex and supplemental motor area and in the right cerebellum for right finger-tapping task. ICA analysis using GIFT revealed independent components corresponding to contralateral and ipsilateral sensorimotor network and cognitive-related neural network. Conclusion : The current study demonstrated that the low frequency spontaneous fluctuation BOLD signals can be separated from the fMRI data using finger tapping paradigm. Also, it was found that these independent components correspond to spontaneous and coherent neural activity in the primary sensorimotor network and in the motor-cognitive network.
Keywords
fMRI; Active paradigm; Spontaneous fluctuation; ICA;
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