2011年11月11日金曜日

Hedging your bets by learning reward correlations in the human brain.

Wunderlich K, Symmonds M, Bossaerts P, Dolan RJ.
Neuron. 2011 Sep 22;71(6):1141-52. Epub 2011 Sep 21.

適切なポートフォリオ選択をするには「各資産(変動)の相関」を考慮する必要がある(資産AとBの価値は連動する、とか)。人間は相関を試行錯誤によって学習でき、学習された相関はInsula、学習信号(相関予測誤差)はACCにコードされている。

Human subjects are proficient at tracking the mean and variance of rewards and updating these via prediction errors. Here, we addressed whether humans can also learn about higher-order relationships between distinct environmental outcomes, a defining ecological feature of contexts where multiple sources of rewards are available. By manipulating the degree to which distinct outcomes are correlated, we show that subjects implemented an explicit model-based strategy to learn the associated outcome correlations and were adept in using that information to dynamically adjust their choices in a task that required a minimization of outcome variance. Importantly, the experimentally generated outcome correlations were explicitly represented neuronally in right midinsula with a learning prediction error signal expressed in rostral anterior cingulate cortex. Thus, our data show that the human brain represents higher-order correlation structures between rewards, a core adaptive ability whose immediate benefit is optimized sampling.

0 件のコメント:

コメントを投稿