A computational modeling approach to understanding the psychological and neural mechanisms underlying directional reasoning about ambiguous events

Abstract

People often view the ambiguities of their social world through a subjective, rather than objective lens. For example, people may construe ambiguous social events in ways that are consistent with their current moods or with the goals they wish to achieve (e.g., Blanchette & Richards, 2010; Pauker, Rule, & Ambady, 2010). Although both mood and motivation direct reasoning about ambiguity, little is known about whether similar mechanisms account for the effects of mood or motivation. Furthermore, similar neural profiles have been associated with mood-congruent ambiguity resolution and motivated reasoning (e.g., Bhanji & Beer, 2012; Hughes & Beer, 2013), but the extent to which these regions support the same underlying processes has not been explored. A deep understanding of the underlying mechanisms has been difficult to assess because previous research has utilized self-report and reaction time measures to explore the effects of mood and motivation on ambiguity (e.g., Butler & Mathews, 1983; Ditto et al., 1998). People have little introspective access to the cognitive processes that lead to their decisions (Nisbett & Wilson, 1977), and reaction time analyses cannot disentangle underlying mechanisms. Therefore a deeper understanding requires alternative approaches. Drift-diffusion modeling (DDM) makes it possible to independently estimate parameters related to two mechanisms theorized to be involved ambiguity construal: expectations and preferential evidence accumulation. This dissertation describes five studies that utilize DDM to examine two overarching research questions: (I) What role do expectations and preferential evidence accumulation play in the influence of mood and motivation on the construal of ambiguity (Studies 1a, 1b, 3, 4) and (II) Are these processes supported by neural regions known to be involved in the effects of mood and motivation on the construal of ambiguity (Studies 2, 4)? The findings support a predicted role for expectations in mood-congruent and motivated construals of ambiguity. In addition, VMPFC supported motivated expectations that contribute to ambiguity construal. The role of preferential evidence accumulation, on the other hand, was less robust. Findings contribute to our understanding of mood-congruent and motivated reasoning about ambiguity and suggest fruitful approaches for future work exploring directed reasoning about ambiguous events.