Huijin Song1, Jeehye Seo1, Seonguk Jin1, Moon Han1, Moonjung Hwang2, Yongmin Chang1, 3, Kyung Jin Suh4
1Medical & Biological Engineering, Kyungpook National University, Daegu, Korea; 2GE healthcare, Seoul, Korea; 3Molecular medicine, Kyungpook National University, Daegu, Korea; 4Radiology, School of Medicine, Dongguk University, Gyungju, Korea
In the last decades, a few studies showed that the independent component (IC), which extracted from task based fMRI data by independent component analysis (ICA) method, is very similar with the task-evoked brain network. However, previous researchers did not attempt to identify other ICs possibly reflecting brain networks, which were implicitly associated with the task. Therefore, in this study, we aimed to identify not only IC reflecting motor network but also ICs reflecting neural network implicitly involved with alternative finger tapping task using ICA. Furthermore, we also investigated the relation between the temporal patterns of identified ICs and the hemodynamic response of finger tapping task to evaluate the possible difference in the temporal patterns of identified ICs between welders with chronic manganese exposure and healthy controls. Based on our finding that ICA could identify not only IC reflecting motor network but also ICs reflecting neural network implicitly involved with alternative finger tapping task. In addition, the strong correlation of IC reflecting WM with hemodynamic response of alternative finger tapping task suggest that welders required more WM resource for successful complex motor task due to WM deficit.