期刊
NEUROIMAGE
卷 45, 期 4, 页码 1329-1338出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2008.12.074
关键词
Local information; Pattern classification; Posterior parietal cortex; Value
资金
- US National Institute of Mental Health [NIMH-70685]
- US National Institute of Neurological Disease and Stroke [NINDS-41328]
For effective decision making, individuals must be able to form subjective values from many types of information. Yet, the neural mechanisms that underlie potential differences in value computation across different decision scenarios are incompletely understood. Here, we used functional magnetic resonance imaging (fMRI), in conjunction with the machine learning technique of support vector machines (SVM), to identify brain regions that contain unique local information associated with different types of valuation. We used a combinatoric approach that evaluated the unique contributions of different brain regions to model generalization strength. Local voxel patterns in left posterior parietal cortex contained unique information differentiating probabilistic and intertemporal valuation, a result that was not accessible using standard fMRI analyses. We conclude that the early valuation phases for these reward types differ on a. ne spatial scale, suggesting the existence of computational topographies along the value construction pathway. (C) 2009 Elsevier Inc. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据