2013年12月20日金曜日

The Behavioral and Neural Mechanisms Underlying the Tracking of Expertise

Erie D. Boorman, John P. O'Doherty, Ralph Adolphs, Antonio Rangel
Neuron, Volume 80, Issue 6, 1558-1571, 18 December 2013

「他者の賢さ(予測の正確さ)」をどうやって学習するか?「他者の予測が正解したか」と「他者の予測が自分の予測と一致したか」の情報をベイズ的に組み合わせて行う。
また、その学習は主に脳内のMentalizingネットワークで行われる。

Evaluating the abilities of others is fundamental for successful economic and social behavior. We investigated the computational and neurobiological basis of ability tracking by designing an fMRI task that required participants to use and update estimates of both people and algorithms’ expertise through observation of their predictions. Behaviorally, we find a model-based algorithm characterized subject predictions better than several alternative models. Notably, when the agent’s prediction was concordant rather than discordant with the subject’s own likely prediction, participants credited people more than algorithms for correct predictions and penalized them less for incorrect predictions. Neurally, many components of the mentalizing network—medial prefrontal cortex, anterior cingulate gyrus, temporoparietal junction, and precuneus—represented or updated expertise beliefs about both people and algorithms. Moreover, activity in lateral orbitofrontal and medial prefrontal cortex reflected behavioral differences in learning about people and algorithms. These findings provide basic insights into the neural basis of social learning.

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