Abstract
Brain functional activation of decision-making on fMRI experiment is seldom analyzed by data driven method to reveal the distinct brain functional network of decision-making. In this paper, a spatial independent component analysis (sICA) is presented to detect the functional network underlying decision-making by analyzing the unmixing matrices temporal components corresponding to spatial separated pattern. Our results show that ICA could separate various sub-functional activation networks to understand the neural mechanisms underlying decision-making, which mainly include functional network of conflict detection, cognitive and emotion.
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Acknowledgments
This work was supported by NSFC, 9082006 and 30770590, Key research project of science and technology of MOE (107097) and 863 Program No: 2008AA02Z4080.
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Duan, X., Chen, H., Pan, Z., Liao, W., Wang, D., Ding, J. (2011). ICA Analysis for Decision-Making Task on fMRI. In: Wang, R., Gu, F. (eds) Advances in Cognitive Neurodynamics (II). Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9695-1_62
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DOI: https://doi.org/10.1007/978-90-481-9695-1_62
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