Too Much Flexibility in a Dynamical Model of Repetitive Negative Thinking?

Iftach and Bernstein propose a dynamical system model of task-unrelated thought that is designed to explain how repetitive negative thinking (RNT) and maladaptive internally-directed cognition more generally arises from attentional biases, working memory, and negative affect. They show that specifically during a period of low task demands, it is easier for negative affect to grab resources and take over with RNT. They also postulate that for individuals with high cognitive reactivity, this tendency for RNT to take over is increased. We argue this paper is an important move forward toward understanding in what circumstances RNT takes over, but also that the model is not yet sufficiently “formalized.” Specifically, we notice excessive levels of flexibility and redundancy that could undermine the explainability of the model. Moreover, the likelihood of negative thinking, as implemented in the proposed model, relies heavily on working memory capacity. In response to this observation, we give suggestions for how the parametrization of this model could be done in a more principled manner. We think such an analysis paves the way for more principled computational modeling of RNT which can be applied to describing empirical data and eventually, to inform decision-making in clinical settings.