Modeling the Retrieval of Counterfactual Thoughts
People often think about counterfactual possibilities to an event and imagine how it could have been otherwise. The study of how this occurs is central to many areas of cognitive psychology, including decision making, social cognition, and causal judgment; however, cognitive models of the memory processes at play during the generation of counterfactual thoughts have not yet been developed. Inspired by theories of list recall and semantic memory search, we build a formal model that examines how a sequence of counterfactual thoughts is retrieved from a set of all possible counterfactuals. Our approach takes the form of a Markov random walk over items in memory and allows for the activation of a counterfactual item to depend on its desirability, probability of selection, language frequency, and semantic similarity with the previously retrieved item. In this way, our model parametrically instantiates prior theories of counterfactual generation within a statistical model that can be fit to data from counterfactual generation tasks. Across three experiments, we show that our model describes and predicts the sequence of counterfactual thoughts that come to mind in response to a particular event, as well as the effects of these counterfactuals on subsequent evaluations and decisions. Our model can also explain key qualitative patterns in counterfactual generation and model the effects of contextual variables such as priming. Overall, our work shows how existing theories of counterfactual generation can be combined with quantitative models of memory search to provide new insights about the generation and consequences of counterfactual thinking.