4.7 Article

Decisions under uncertainty: Probabilistic context influences activation of prefrontal and parietal cortices

期刊

JOURNAL OF NEUROSCIENCE
卷 25, 期 13, 页码 3304-3311

出版社

SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.5070-04.2005

关键词

decision making; uncertainty; risk; fMRI; executive function; response selection

资金

  1. NIDA NIH HHS [DA-16214] Funding Source: Medline
  2. NINDS NIH HHS [NS-41328, R01 NS050329, NS-50329, P01 NS041328] Funding Source: Medline

向作者/读者索取更多资源

Many decisions are made under uncertainty; that is, with limited information about their potential consequences. Previous neuroimaging studies of decision making have implicated regions of the medial frontal lobe in processes related to the resolution of uncertainty. However, a different set of regions in dorsal prefrontal and posterior parietal cortices has been reported to be critical for selection of actions to unexpected or unpredicted stimuli within a sequence. In the current study, we induced uncertainty using a novel task that required subjects to base their decisions on a binary sequence of eight stimuli so that uncertainty changed dynamically over time (from 20 to 50%), depending on which stimuli were presented. Activation within prefrontal, parietal, and insular cortices increased with increasing uncertainty. In contrast, within medial frontal regions, as well as motor and visual cortices, activation did not increase with increasing uncertainty. We conclude that the brain response to uncertainty depends on the demands of the experimental task. When uncertainty depends on learned associations between stimuli and responses, as in previous studies, it modulates activation in the medial frontal lobes. However, when uncertainty develops over short time scales as information is accumulated toward a decision, dorsal prefrontal and posterior parietal contributions are critical for its resolution. The distinction between neural mechanisms subserving different forms of uncertainty resolution provides an important constraint for neuroeconomic models of decision making.

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