The diffusion model’s drift rate parameter primarily reflects efficiency, rather than speed, of evidence accumulation

Bibliographic Data

ID21641215
AuthorsAlexander Weigard (0000-0003-3820-6461, University of Michigan, corresponding author), M Fiona Molloy (0000-0002-1530-2867, University of Michigan), Chandra Sripada (0000-0001-9025-6453, University of Michigan), Andrew Heathcote (0000-0003-4324-5537, University of Amsterdam)
Year2026
Volume33
Issue3
Publication date2026-03-01
Open AccessYes
TypeARTICLE
VenuePsychonomic Bulletin & Review (JOURNAL)
Journal identifiersISSN: 1069-9384 • E-ISSN: 1531-5320
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.3758/s13423-026-02861-3
PMID41748773
OpenAlexW7131689563
LanguageEN
References cited60

Applications of the diffusion decision model (DDM) to the study of cognitive individual differences consistently find that the model’s drift rate ( v ) parameter forms a cohesive factor across many tasks and relates to measures of higher-order cognitive functioning, including general cognitive ability and working memory. This parameter is often interpreted as a measure of “processing speed,” a traditional psychometric construct thought to reflect an individual’s basic speed of information processing across tasks. However, conceptual differences between v and traditional notions of processing speed make this mapping far from straightforward. Racing accumulator models, which provide a more flexible and comprehensive account of behavioral data than the DDM, allow for the speed with which individuals accumulate evidence to be dissociated from the efficiency with which they accumulate task-relevant evidence (versus task-irrelevant evidence). We applied the DDM and a racing accumulator model to three tasks across three independent datasets to gauge the extent to which v parameter findings from the cognitive individual differences literature reflect speed of evidence accumulation (SEA) versus efficiency of evidence accumulation (EEA). Across all tasks, v was more strongly related to EEA than SEA. EEA was consistently related to measures of general cognitive ability, working memory, and executive function whereas SEA explained v parameter, and its relations with higher-order cognitive abilities, primarily reflect EEA rather than SEA and challenge the widespread practice of equating v with the traditional “processing speed” construct

Cognition · Diffusion · Equating · Information processing · Functional Brain Connectivity Studies · Neural and Behavioral Psychology Studies · Visual and Cognitive Learning Processes

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