School of Psychology, The University of Sydney, Sydney, NSW 2006, Australia.
Behavioural Neuroscience Laboratory, Brain and Mind Research Institute, The University of Sydney, Sydney, NSW 2006, Australia.
Curr Biol. 2015 Apr 20;25(8):1074-9. doi: 10.1016/j.cub.2015.02.044. Epub 2015 Apr 9.
The capacity to extract causal knowledge from the environment allows us to predict future events and to use those predictions to decide on a course of action. Although evidence of such causal reasoning has long been described, recent evidence suggests that using predictive knowledge to guide decision-making in this way is predicated on reasoning about causes in two quite distinct ways: choosing an action can be based on the interaction between predictive information and the consequences of that action, or, alternatively, actions can be selected based on the consequences that they do not produce. The latter counterfactual reasoning is highly adaptive because it allows us to use information about both present and absent events to guide decision-making. Nevertheless, although there is now evidence to suggest that animals other than humans, including rats and birds, can engage in causal reasoning of one kind or another, there is currently no evidence that they use counterfactual reasoning to guide choice. To assess this question, we gave rats the opportunity to learn new action-outcome relationships, after which we probed the structure of this learning by presenting excitatory and inhibitory cues predicting that the specific outcomes of their actions would either occur or would not occur. Whereas the excitors biased choice toward the action delivering the predicted outcome, the inhibitory cues selectively elevated actions predicting the absence of the inhibited outcome, suggesting that rats encoded the counterfactual action-outcome mappings and were able to use them to guide choice.
从环境中提取因果知识的能力使我们能够预测未来的事件,并利用这些预测来决定行动方针。尽管这种因果推理的证据由来已久,但最近的证据表明,以这种方式利用预测知识来指导决策取决于以两种截然不同的方式推理原因:选择一个行动可以基于预测信息与该行动的后果之间的相互作用,或者,也可以根据行动不产生的后果来选择行动。这种反事实推理具有高度的适应性,因为它使我们能够利用关于当前和不存在事件的信息来指导决策。然而,尽管现在有证据表明,除了人类之外,包括老鼠和鸟类在内的其他动物也可以进行某种形式的因果推理,但目前没有证据表明它们使用反事实推理来指导选择。为了评估这个问题,我们让老鼠有机会学习新的行为-结果关系,然后通过呈现预测其行为特定结果将发生或不会发生的兴奋性和抑制性线索,来探测这种学习的结构。兴奋性线索使选择偏向于产生预测结果的行为,而抑制性线索则选择性地提高了预测抑制结果不存在的行为,这表明老鼠对反事实的行为-结果映射进行了编码,并能够利用这些映射来指导选择。