Using cognitive load tasks to constrain hypotheses about the role of the default mode network in social cognition: uncertainty reduction as a unifying framework

Although the default mode network (DMN) is consistently implicated in social cognition, its functional contributions to social thought and behavior have been challenging to characterize. To date, scientific understanding of DMN function has mainly been informed by neuroimaging studies of task-based activation. In this review, we adopt a complementary approach, capitalizing on the observation that exogenous cognitive load tasks reliably deactivate the DMN. In a variety of dual-task studies, an exogenous cognitive load task (e.g. digit string memorization) has been paired with a concurrent task of interest (e.g. personality trait attribution). Although typically conducted for other reasons, we propose that such studies offer a means to ask what happens to behavioral performance across a range of tasks when DMN activity is temporarily perturbed, helping to constrain hypotheses about the cognitive functions of the DMN. Here, we review patterns of behavioral performance on a variety of social and nonsocial tasks under concurrent cognitive load, treating load as a temporary DMN perturbation. Although results are mixed when organized by task type, a clearer pattern emerges when organized by how much uncertainty reduction demand (URD) tasks imposed on participants: tasks involving higher URD, but not lower URD, are reliably disrupted under exogenous cognitive load. This evidence tentatively suggests uncertainty reduction as an overarching framework through which to view the contributions of the DMN to (social) cognition, reconciling seemingly contradictory evidence from past studies and opening new avenues for future research. • Cognitive load suppresses the DMN, inducing a temporary network perturbation. • Changes in behavior under load-induced DMN suppression may inform DMN function. • In past studies, load disrupted tasks with higher uncertainty reduction demand. • Uncertainty reduction is a framework through which to understand DMN contributions.