The Reward-Complexity Trade-off in Schizophrenia.
The Reward-Complexity Trade-off in Schizophrenia.
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DOI：
10.5334/cpsy.71
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发表时间：
2021-01-01
期刊：
影响因子：
--
通讯作者：
Lai, Lucy
中科院分区：
文献类型：
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作者：
Gershman, Samuel J;Lai, Lucy
动作选择需要一个将世界状态映射到动作分布的策略。指定策略所需的内存量（策略复杂性）随着策略的状态依赖性而增加。如果策略复杂性存在容量限制，那么在奖励和复杂性之间也将存在权衡，因为为了满足容量约束，需要牺牲一些奖励。本文以经验为基础，对精神分裂症患者和健康对照者的奖励和复杂性之间的权衡进行了表征。精神分裂症患者平均采用较低的复杂性策略，与健康对照组相比，这些策略更强烈地偏离最佳奖励-复杂性权衡曲线。然而，健康对照组也偏离了最佳权衡曲线，两组似乎都位于相同的经验权衡曲线上。我们解释这些发现使用成本敏感的演员批评模型。我们的经验和理论研究结果揭示了精神分裂症的认知努力异常。
Action selection requires a policy that maps states of the world to a distribution over actions. The amount of memory needed to specify the policy (the policy complexity) increases with the state-dependence of the policy. If there is a capacity limit for policy complexity, then there will also be a trade-off between reward and complexity, since some reward will need to be sacrificed in order to satisfy the capacity constraint. This paper empirically characterizes the trade-off between reward and complexity for both schizophrenia patients and healthy controls. Schizophrenia patients adopt lower complexity policies on average, and these policies are more strongly biased away from the optimal reward-complexity trade-off curve compared to healthy controls. However, healthy controls are also biased away from the optimal trade-off curve, and both groups appear to lie on the same empirical trade-off curve. We explain these findings using a cost-sensitive actor-critic model. Our empirical and theoretical results shed new light on cognitive effort abnormalities in schizophrenia.