神经经济学家 Ian Krajbich (Ohio State 心理系与经济系助理教授) 来台访问， 12/19 在阳明大学神研所(10:10-11:30am)与台大经济系(1:45-3:15pm)各有一场演讲。 以下是演讲邀请函，欢迎大家参加。 Joseph xxxxxxxxxxxxxxxxx 我是分隔线 xxxxxxxxxxxxxxxxxxxx Dear Colleagues, The upcoming neuroeconomics colloquium series will feature Ian Krajbich, Assistant Professor in the Department of Psychology and Department of Economics at Ohio State University. Dr.Krajbich is a young neuroeconomist who studies decision-making using computational models and/or economic modelling, as well as neuroscience tools including eyetracking, fMRI, tDCS and brain-damaged patients. He has published in neuroscience journals including Science, PNAS, Psychological Science, Nature Neuroscience, Journal of Neuroscience, as well as economic journals including the American Economic Review: https://economics.osu.edu/people/krajbich http://faculty.psy.ohio-state.edu/krajbich/ Ian will give 2 public lectures. Please see below for more detailed information. Please do not hesitate to contact us if you wish to meet with Dr. Krajbich. Sincerely, 黄贞颖、王道一、郭文瑞、吴仕炜、叶俊毅 演讲一 Title: A Common Mechanism Underlying Value-based Decision Making (各种用价值来做的决策背後的共通机制) Date and Time: 12/19 (四) 10:10-11:30am Location: 阳明大学活动中心第三会议室 Abstract: People make numerous decisions every day including perceptual decisions like walking through a crowd, decisions over primary rewards like what to eat, and social decisions that require balancing own and others’ benefits. The unifying principles behind choices in various domains are, however, still not well understood. Mathematical models that describe choice behavior in specific contexts have provided important insights into the computations that may underlie decision making in the brain. However, a critical and largely unanswered question is whether these models generalize from one choice context to another. Here I show that a model adapted from the perceptual decision-making domain and estimated on choices over food rewards accurately predicts choices and reaction times in three independent sets of subjects making social decisions. The robustness of the model across domains provides strong evidence for a common decision-making process in perceptual, primary reward, and social decision making. I also provide evidence that visual attention is a critical variable in this process. 演讲二 Title: Benefits of Neuroeconomic Modeling: New Policy Interventions and Predictors of Preference (神经经济理论的价值：政策建议与偏好预测) Date and Time: 12/19 (四) 1:45-3:15pm Location: 台大经济系经研大楼二楼(社科院第2教室) Abstract: From its inception, neuroeconomics has promised to use knowledge from neuroscience and psychology to improve models of economic decision making. Here we deliver on this promise by introducing a biologically-plausible (drift-diffusion) model of decision making that is able to predict behavior, with fixed parameters, in random groups of individuals across very different tasks. The model also goes beyond the traditional economic approach because it is able to predict not only choices but reaction times as well. But why should economists care about modeling reaction times? For one, as predicted by the model, we consistently observe that people spend too much time on irrelevant choices for which they are nearly indifferent. In a world of time constraints, time spent on unimportant decisions represents an opportunity cost, namely time not spent on more important decisions. To help subjects overcome this inefficient allocation of time, we designed an intervention that puts a time limit on subjects’ choices. This simple intervention substantially improved subjects’ welfare in a time-constrained choice experiment. Second, the precise relationship between reaction times and choice probabilities implies that reaction times can be used to predict indifference points and the strength of preferences. We demonstrate this ability using data from an Ultimatum Game experiment. Overall, we show that better understanding the process by which people make decisions can explain the basis for stochastic choice behavior and help us do both normative and positive economics. --

※ 发信站: 批踢踢实业坊(ptt.cc) ◆ From: 140.112.25.135