ArticlePsychological review2018
Modeling numerosity representation with an integrated diffusion model.
Article in Psychological review, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Latent Neurocognitive Mechanisms Underlying Quantity Discrimination in Children with and without Mathematical Learning Disabilities.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Reinforcement Learning and Decision Making in Depression in Adolescents and Young Adults: Insights from a New Model of the Probabilistic Reward Task.Computational psychiatry (Cambridge, Mass.) · 2025Article
- A novel behavioral paradigm reveals the nature of confidence computation in multi-alternative perceptual decision making.Research square · 2024Article
- Most quantifiers have many meanings.Psychonomic bulletin & review · 2024Article
- The gated cascade diffusion model: An integrated theory of decision making, motor preparation, and motor execution.Psychological review · 2024Article
- Joint contributions of preview and task instructions on visual search strategy selection.Attention, perception & psychophysics · 2024Article
- Measuring utility with diffusion models.Science advances · 2023Article
- Integrated diffusion models for distance effects in number memory.Cognitive psychology · 2022Article
- How much time does it take to discriminate two sets by their numbers of elements?Attention, perception & psychophysics · 2022Article
- Modeling Conditional Dependence of Response Accuracy and Response Time with the Diffusion Item Response Theory Model.Psychometrika · 2022Article
- High-value decisions are fast and accurate, inconsistent with diminishing value sensitivity.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Response bias in numerosity perception at early judgments and systematic underestimation.Attention, perception & psychophysics · 2022Article
- An initial 'snapshot' of sensory information biases the likelihood and speed of subsequent changes of mind.PLoS computational biology · 2022Article
- Estimating systematic and random sources of variability in perceptual decision-making: A reply to Evans, Tillman, & Wagenmakers (2020).Psychological review · 2021Article
- Automatic place-value activation in magnitude-irrelevant parity judgement.Psychological research · 2021Article
- Examining aging and numerosity using an integrated diffusion model.Journal of experimental psychology. Learning, memory, and cognition · 2020Article
- Modeling the interaction of numerosity and perceptual variables with the diffusion model.Cognitive psychology · 2020Article
- Decision making in numeracy tasks with spatially continuous scales.Cognitive psychology · 2020Article
- Decision making on spatially continuous scales.Psychological review · 2018Article
- Modeling 2-alternative forced-choice tasks: Accounting for both magnitude and difference effects.Cognitive psychology · 2018Article
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2 authors.
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Abstract
Models of the representation of numerosity information used in discrimination tasks are integrated with a diffusion decision model. The representation models assume distributions of numerosity either with means and SD that increase linearly with numerosity or with means that increase logarithmically with constant SD. The models produce coefficients that are applied to differences between two numerosities to produce drift rates and these drive the decision process. The linear and log models make differential predictions about how response time (RT) distributions and accuracy change with numerosity and which model is successful depends on the task. When the task is to decide which of two side-by-side arrays of dots has more dots, the log model fits decreasing accuracy and increasing RT as numerosity increases. When the task is to decide, for dots of two colors mixed in a single array, which color has more dots, the linear model fits decreasing accuracy and decreasing RT as numerosity increases. For both tasks, variables such as the areas covered by the dots affect performance, but if the task is changed to one in which the subject has to decide whether the number of dots in a single array is more or less than a standard, the variables have little effect on performance. Model parameters correlate across tasks suggesting commonalities in the abilities to perform them. Overall, results show that the representation used depends on the task and no single representation can account for the data from all the paradigms. (PsycINFO Database Record
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