Drift-diffusion modeling of accuracy and reaction times: a deeper insight into retrospective attention

Abstract

Retrospective attention refers to the prioritization of contents held in working memory, a process investigated using the retro-cueing paradigm. This process is evidenced by the retro-cueing benefit, characterized by better performance for retrospectively cued trials. However, traditional statistical analyses fall short in distinguishing between decisional and non-decisional processes underlying this benefit. A pivotal contribution by Shepherdson et al. (2018) addressed this gap by applying drift-diffusion modeling which integrates both accuracy and reaction time measures to disentangle these processes. Their key contribution lies in demonstrating that retro-cues enhance the quality of working memory contents and enable their retrieval in advance of decision making—effects that occur independently of shifts in decision criteria. Building on Shepherdson et al.'s work, we encourage future DDM-based retro-cueing studies to pursue precise, mutually exclusive hypothesis testing and to integrate behavioral and neural data to more clearly distinguish between competing explanations of the retro-cueing benefit.