ReviewPsychonomic bulletin & review2020
Sequential sampling models without random between-trial variability: the racing diffusion model of speeded decision making.
Review in Psychonomic bulletin & review, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Neuropsychological differential diagnosis of Alzheimer's disease and vascular dementia: a systematic review with meta-regressions.Frontiers in aging neuroscience · 2023Pooled it
- Modeling decision dynamics disentangles working memory, cognitive control and reinforcement learning and reveals clinical differences.PLoS computational biology · 2026Article
- Decomposing response inhibition: A POMDP model.PLoS computational biology · 2026Article
- Imagine No Resources: Attention Is Selection and Normalization for Choice.Perspectives on psychological science : a journal of the Association for Psychological Science · 2026Article
- Challenging the mechanism for the implicit association test.Nature human behaviour · 2026Article
- Can Systematic Drift Rate Variability Replace Random Variability in the Diffusion Decision Model?Computational brain & behavior · 2026Article
- dynConfiR: An R package for sequential sampling models of decision confidence.Behavior research methods · 2026Article
- An illustrative guide to expressing cognitive theories using evidence accumulation modelling.Behavior research methods · 2026Article
- Primate-informed neural network for visual decision-making.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Value computations underpin flexible emotion expression.Communications psychology · 2025Article
- Aligning visual imagery to the operator improves geospatial situation awareness in a single-display 360-degree periscope concept.Cognitive research: principles and implications · 2025Article
- Parameter identifiability in evidence-accumulation models: The effect of error rates on the diffusion decision model and the linear ballistic accumulator.Psychonomic bulletin & review · 2025Article
- The Tweedledum and Tweedledee of dynamic decisions: Discriminating between diffusion decision and accumulator models.Psychonomic bulletin & review · 2025Review
- The neural implausibility of the diffusion decision model doesn't matter for cognitive psychometrics, but the Ornstein-Uhlenbeck model is better.Psychonomic bulletin & review · 2024Article
- Mnemonic vs. Executive Contributions to the N400: A Connectionist Approach to False Memories.Computational brain & behavior · 2024Article
- The neural network RTNet exhibits the signatures of human perceptual decision-making.Nature human behaviour · 2024Article
- The effects of non-diagnostic information on confidence and decision making.Memory & cognition · 2024Article
- The gated cascade diffusion model: An integrated theory of decision making, motor preparation, and motor execution.Psychological review · 2024Article
- Are there jumps in evidence accumulation, and what, if anything, do they reflect psychologically? An analysis of Lévy Flights models of decision-making.Psychonomic bulletin & review · 2024Review
- Joint Modelling of Latent Cognitive Mechanisms Shared Across Decision-Making Domains.Computational brain & behavior · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Most current sequential sampling models have random between-trial variability in their parameters. These sources of variability make the models more complex in order to fit response time data, do not provide any further explanation to how the data were generated, and have recently been criticised for allowing infinite flexibility in the models. To explore and test the need of between-trial variability parameters we develop a simple sequential sampling model of N-choice speeded decision making: the racing diffusion model. The model makes speeded decisions from a race of evidence accumulators that integrate information in a noisy fashion within a trial. The racing diffusion does not assume that any evidence accumulation process varies between trial, and so, the model provides alternative explanations of key response time phenomena, such as fast and slow error response times relative to correct response times. Overall, our paper gives good reason to rethink including between-trial variability parameters in sequential sampling models.
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.