National Yang-Ming University -- Shih-Wei Wu Assistant professor
Shih-Wei Wu Assistant professor

Wu Lab
image Shih-Wei Wu Assistant professor
swwu@ym.edu.tw
Tel : 886-2-28267000 ext. 6125

Ph.D., 2008, Experimental psychology, New York University
Postdoctoral fellow, 2008-2010, Division of Humanities and Social Sciences, California Institute of Technology
>> Link ˇGhomepages.nyu.edu/~sww214
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I am interested in how organisms make decisions and the neural computations performed to guide this process. The central approach I have been using to investigate these problems is to develop mathematical models that could quantitatively predict people's choice behavior and the underlying computations carried out when making decisions. This approach is powerful in the sense that (1) the models provide predictions at both the neural and behavioral level, (2) a wide range of decision problems could be investigated under the same mathematical framework and (3) we could further study how decision process might differ between different domains (economic, perceptual, or motor) by comparing actual performance to model prediction.

We have been investigating how people make motor decisions in the presence of risk and uncertainty (e.g. a tennis player trying to decide where the opponent is going to serve), and how economic decision-making might differ from motor decisions (e.g. whether to buy stocks v.s whether to swing at a coming baseball). My collaborators (Larry Maloney and Mauricio Delgado) and I have shown that people differ in how they use and distort probability information between economic decision-making and motor decision-making (Wu et al. 2009). Recently, we have also begun to use functional magnetic resonance imaging (fMRI) to investigate networks in the brain involved in representing probability information under different decision domains (Wu et al.,2011).

Another focus of my research has been to investigate how decision makers integrate information from the past and present to make decisions. This is a classical problem in many disciplines, including statistics, economics, psychology, and neuroscience. Using fMRI, we seek to address where in the brain is involved in performing such integration and whether BOLD signals in those areas are parametrically encoding optimal computations predicted by Bayesian decision theory.
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image Wu, S.-W., Trommershauser, J., Maloney, L. T., & Landy, M. S. (2006). Limits to human movement planning in tasks with asymmetric gain landscapes. Journal of Vision, 6, 53-63.
image Dean, M., Wu, S-W., & Maloney, L. T. (2007). Trading off speed and accuracy in rapid, goal-directed movements. Journal of Vision, 7(5):10, 1-12.
image Wu, S-W., Delgado, M. R. & Maloney, L. T. (2009). Economic decision-making compared with an equivalent motor task. Proceedings of the National Academy of Sciences USA, 106(15): 6088-93.
image Wu, S-W., Dal Martello, M. F. & Maloney, L. T. (2009). Suboptimal allocation of time in sequential movements. PLoS ONE 4(12): e8228. doi:10.1371/journal.pone.0008228.
image Zhang, H., Wu, S-W., & Maloney, L. T. (2010). Planning multiple movements within a fixed time limit: The cost of constrained time allocation in a visuo-motor task. Journal of Vision, 10(6), 1-17.
image Wu, S-W., Delgado, M. R. and Maloney, L. T. (2011). The neural correlates of subjective utility of monetary outcome and probability weight in economic and in motor decision under risk. Journal of Neuroscience,31(24),8822-8831.


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