Drift-diffusion modeling of accuracy and reaction times: a deeper insight into retrospective attention Fuentes-Guerra, Águeda Cipriani, Germán González García, Carlos Botta, Fabiano This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness [research project PID2020-116342GA-I00 to CGG, and PID2020-118214GB-I00 to FB, funded by MCIN/ AEI /10.13039/501100011033]. CG-G was also supported by Grant RYC2021-033536-I funded by MCIN/AEI/10.13039/501100011033 and by the European Union Next Generation EU/PRTR. FB was also supported by Grant PRE2021-100459 funded by 10.13039/501100011033. Additionally, this publication was funded by ESF+, CEX2023-001312-M by MCIN/AEI/10.13039/501100011033 and UCE- PP2023-11 by University of Granada. This article is part of the thesis of GAC under the supervision of FB and Juan Lupiáñez. 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. 2026-01-29T08:34:09Z 2026-01-29T08:34:09Z 2025 journal article Published version: Cipriani, G., González-García, C., Fuentes-Guerra, Á., & Botta, F. (2025). Drift-Diffusion Modeling of Accuracy and Reaction Times: A Deeper Insight Into Retrospective Attention. Journal of Experimental Psychology: Human Perception and Performance, 51(11), 1461–1463. https://doi.org/10.1037/xhp0001349 https://hdl.handle.net/10481/110450 10.1037/xhp0001349 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Wolters Kluwer