Knowing how much you don't know: a neural organization of uncertainty estimates

被引:214
|
作者
Bach, Dominik R. [1 ,2 ]
Dolan, Raymond J. [1 ,2 ]
机构
[1] UCL, Wellcome Trust Ctr Neuroimaging, London WC1N 3BG, England
[2] Univ Berlin, Berlin Sch Mind & Brain, D-10099 Berlin, Germany
基金
英国惠康基金; 瑞士国家科学基金会;
关键词
DECISION-MAKING; BAYESIAN INTEGRATION; PERCEPTUAL DECISION; STOCHASTIC RESONANCE; AMBIGUITY AVERSION; SHAPE INFORMATION; RISKY BUSINESS; REWARD VALUE; TEXTURE; HUMANS;
D O I
10.1038/nrn3289
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
How we estimate uncertainty is important in decision neuroscience and has wide-ranging implications in basic and clinical neuroscience, from computational models of optimality to ideas on psychopathological disorders including anxiety, depression and schizophrenia. Empirical research in neuroscience, which has been based on divergent theoretical assumptions, has focused on the fundamental question of how uncertainty is encoded in the brain and how it influences behaviour. Here, we integrate several theoretical concepts about uncertainty into a decision-making framework. We conclude that the currently available evidence indicates that distinct neural encoding (including summary statistic-type representations) of uncertainty occurs in distinct neural systems.
引用
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页码:572 / 586
页数:15
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