The Diffusion Decision Model for Non-Specialists

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Review of the diffusion model

Diffusion Decision Model: Current issues and history – In this paper we reviewed a number of topics including relationships among models, brief presentation, expanded judgments, collapsing bounds and urgency, optimality, and applications.

Annotated list of diffusion model publications – Many of our papers have research that is being used without the authors being aware of some of this history. Here is a list in which we describe each of our diffusion model papers in a couple of sentences.

Packages for diffusion model fitting:

Wiecki, T.V., Sofer, I. and Frank, M.J. (2013). HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python. Frontiers in Neuroinformatics, 7, 1-10.

Vandekerckhove, J., & Tuerlinckx, F. (2008). Diffusion model analysis with MATLAB: A DMAT primer. Behavior Research Methods, 40, 61-72.

Voss, A. & Voss, J. (2007) Fast-dm: A free program for efficient diffusion model analysis. Behavior Research Methods, 39, 767-775.

Voss, A., & Voss, J. (2008). A Fast Numerical Algorithm for the Estimation of Diffusion-Model Parameters. Journal of Mathematical Psychology, 52, 1-9.

Wagenmakers, E-J., Van Der Maas, H. L. J. & Grasman, R. P. P. P. (2007). An EZ-diffusion model for response time and accuracy. Psychonomic Bulletin and Review, 14, 3-22.

Applications – a lot of work has been done using applications of the diffusion model to areas such as:


Huang-Pollock, C., Ratcliff, R., McKoon, G., Shapiro, Z., Weigard, A., & Galloway-Long, H. (2017). Using the diffusion model to explain cognitive deficits in Attention Deficit Hyperactivity Disorder. Journal of Abnormal Child Psychology, 45(1), 57-68.

Mulder, M.J., Bos, D., Weusten, J.M.H., van Belle, J., van Dijk, S.C., Simen, P., van Engeland, H., & Durson, S. (2010). Basic impairments in regulating the speed-accuracy tradeoff predict symptoms of attention-deficit/hyperactivity disorder. Biological Psychiatry, 68, 1114-1119.


Voskuilen, C., Ratcliff, R., & McKoon, G. (2018). Aging and confidence judgments in item recognitionJournal of Experimental Psychology: Learning, Memory, and Cognition, 44, 1-23.

Ratcliff, R., Thapar, A., & McKoon, G. (2011). Effects of aging and IQ on item and associative memory. Journal of Experimental Psychology: General, 140, 464-487.

Ratcliff, R., Thapar, A., & McKoon, G. (2010). Individual differences, aging, and IQ in two-choice tasks. Cognitive Psychology, 60, 127-157.

Ratcliff, R., Thapar, A., & McKoon, G. (2007). Application of the diffusion model to two-choice tasks for adults 75-90 years old. Psychology and Aging, 22, 56-66.

Ratcliff, R., Thapar, A., & McKoon, G. (2006). Aging and individual differences in rapid two-choice decisions. Psychonomic Bulletin and Review, 13, 626-635.

Ratcliff, R., Thapar, A., & McKoon, G. (2006). Aging, practice, and perceptual tasks: A diffusion model analysis. Psychology and Aging, 21, 353-371.

Ratcliff, R., Thapar, A., Gomez, P. & McKoon, G. (2004). A diffusion model analysis of the effects of aging in the lexical-decision task.Psychology and Aging, 19, 278-289.

Thapar, A., Ratcliff, R., & McKoon, G. (2003). A diffusion model analysis of the effects of aging on letter discrimination. Psychology and Aging, 18, 415-429.

Ratcliff, R., Thapar, A. & McKoon, G. (2003). A diffusion model analysis of the effects of aging on brightness discrimination. Perception and Psychophysics, 65, 523-535.

Ratcliff, R., Thapar, A., & McKoon, G. (2001). The effects of aging on reaction time in a signal detection task. Psychology and Aging, 16, 323-341.

Alzheimer’s Disease

Aschenbrenner, A.J., Balota, D.A., Gordon, B.A., Ratcliff, R., & Morris, J.C. (2016). A diffusion model analysis of episodic recognition in individuals with a family history for Alzheimer disease: The Adult Child Study. Neuropsychology, 30, 225-238.

Anxiety + Depression

White, C.N., Ratcliff, R., & Vasey, M.W. (2016). Anxiety-related threat bias in recognition memory: The moderating effect of list composition. Cognition and Emotion, 30(8), 1446-1460.

White, C. N., Ratcliff, R., Vasey, M. W., & McKoon, G. (2010). Anxiety enhances threat processing without competition among multiple inputs: A diffusion model analysis.Emotion, 10, 662-677.

White, C. N., Ratcliff, R., Vasey, M. W., & McKoon, G. (2010). Using diffusion models to understand clinical disorders. Journal of Mathematical Psychology, 54, 39-52.

White, C., Ratcliff, R., Vasey, M. & McKoon, G. (2009). Dysphoria and memory for emotional material: A diffusion model analysis. Cognition and Emotion, 23, 181-205.


Ratcliff, R., Perea, M., Colangelo, A. & Buchanan, L. (2004). A diffusion model account of normal and impaired readers. Brain and Cognition, 55, 374-382.


Thompson, C.A., Ratcliff, R., & McKoon, G. (2016). Individual differences in the components of children’s and adults’ information processing for simple symbolic and non-symbolic numeric decisionsJournal of Experimental Child Psychology, 150, 48-71.

Ratcliff, R., Love, J., Thompson, C. A., & Opfer, J. (2012). Children are not like older adults: A diffusion model analysis of developmental changes in speeded responses. Child Development, 83, 367-381.


Ratcliff, R. (2015). Modeling one-choice and two-choice driving tasks. Attention, Perception and Psychophysics, 77, 2134-2144.

Ratcliff, R., & Strayer, D. (2014). Modeling simple driving tasks with a one-boundary diffusion model. Psychonomic Bulletin and Review21, 577-589.


Zeguers, M.H.T., Snellings, P., Tijms, J., Weeda, W.D., Tamboer, P., Bexkens, A. & Huizenga, H.M. (2011). Specifying theories of developmental dyslexia: A diffusion model analysis of word recognition. Developmental Science, 14, 1340-1354.


Geddes, J., Ratcliff, R., Allerhand, M., Childers, R., Wright, R.J., Frier, B.M., & Deary, I.J. (2010). Modeling the effects of hypoglycemia on a two-choice task in adult humans. Neuropsychology, 24, 652-660.

Neuroscience, EEG + Single-Cell Recording

de Hollander, G., Labruna, L., Sellaro, R., Trutti, A., Colzato, L., Ratcliff, R., Ivry, R., & Forstmann, B.U. (2016). Transcranial direct current stimulation does not influence the speed-accuracy tradeoff in perceptual decision making: Evidence from three independent replication studies. Journal of Cognitive Neuroscience, 7, 1-12.

Forstmann, B. U., Ratcliff, R., & Wagenmakers, E.-J. (2016). Sequential sampling models in cognitive neuroscience: Advantages, applications, and extensions. Annual Review of Psychology, 67, 641-666.

Ratcliff, R., Sederberg, P., Smith, T., & Childers, R. (2016). A single trial analysis of EEG in recognition memory: Tracking the neural correlates of memory strengthNeuropsychologia, 93, 128-141.

Hawkins, G. E., Forstmann, B. U., Wagenmakers, E.-J., Ratcliff, R., & Brown, S. D. (2015). Revisiting the evidence for collapsing boundaries and urgency signals in perceptual decision-makingJournal of Neuroscience, 35, 2476-2484.

Mulder, M.J., Boekel, W., Ratcliff, R., & Forstmann, B.U. (2014). Cortico-subthalamic connection predicts individual differences in value-driven choice bias. Brain Structure and Function, 219, 1239-1249.

Mulder, M.J., Wagenmakers, E.J., Ratcliff, R., Wouter Boekel, W. & Forstmann, B.U. (2012). Bias in the brain: a diffusion model analysis of prior probability and potential payoff. Journal of Neuroscience, 32, 2335-2343.

Ratcliff, R., & Frank, M. (2012). Reinforcement-based decision making in corticostriatal circuits: mutual constraints by neurocomputational and diffusion models. Neural Computation, 24, 1186-1229.

Winkel, J., Van Maanen, L., Ratcliff, R., van der Schaaf, M.E., van Schouwenburg, M.R., Cools, R., & Forstmann, B.U. (2012). Bromocriptine does not alter speed-accuracy tradeoff. Frontiers in Decision Neuroscience, 6, 1-8. doi: 10.3389/fnins.2012.00126.

Kuhn, S., Schmiedek, F., Schott, B., Ratcliff, R., Heinze, H-J., Duzel, E., Lindenberger, U., and Levden, M. (2011). Brain areas consistently linked to individual differences in perceptual decision-making in younger as well as older adults before and after training. Journal of Cognitive Neuroscience, 23, 2147-2158.

Ratcliff, R., Hasegawa, Y.T., Hasegawa, Y.P., Childers, R., Smith, P.L., & Segraves, M.A. (2011). Inhibition in superior colliculus neurons in a brightness discrimination task? Neural Computation, 23, 1790-1820.

Sajda, P., Philiastides, M.G., Heekeren, H., & Ratcliff, R. (2011). Linking neuronal variability to perceptual decision making via neuroimaging. In M. Ding & D.L. Glanzman, The dynamic brain: An exploration of neuronal variability and its functional significance (pp. 214-232). New York: Oxford University Press.

Ratcliff, R., Philiastides, M. G., & Sajda, P. (2009). Quality of evidence for perceptual decision making is indexed by trial-to-trial variability of the EEG. Proceedings of the National Academy of Sciences, 106, 6539-6544.

Ratcliff, R., Hasegawa, Y.T., Hasegawa, Y.P., Smith, P.L., & Segraves, M.A. (2007). Dual diffusion model for single-cell recording data from the superior colliculus in a brightness-discrimination task. Journal of Neurophysiology, 97, 1756-1774.

Farrell, S., Ratcliff, R., Cherian, A., & Segraves, M. (2006). Modeling unidimensional categorization in monkeys. Learning and Behavior,34, 86-101.

Ferrera, V. P., Grinband, J., Xiao, Q, Hirsch, J., Ratcliff, R. (2006). Distinguishing evidence accumulation from response bias in categorical decision making. Society for Neuroscience Abstracts.

Philiastides, M.G., Ratcliff, R., & Sajda, P. (2006). Neural representation of task difficulty and decision-making during perceptual categorization: A timing diagram. Journal of Neuroscience, 26, 8965-8975.

Smith, P.L., & Ratcliff, R. (2004). Psychology and neurobiology of simple decisions. Trends in Neuroscience, 27, 161-168.

Ratcliff, R., Cherian, A., & Segraves, M. (2003). A comparison of macaque behavior and superior colliculus neuronal activity to predictions from models of simple two-choice decisions. Journal of Neurophysiology, 90, 1392-1407.

Segraves, M.A., Cherian, A., & Ratcliff, R. (1999). Rhesus monkey performance and superior colliculus activity during a reaction time task. Society for Neuroscience Abstracts, 25, 19-20.

Sleep deprivation

Ratcliff, R. & Van Dongen, H.P.A. (2018). The effects of sleep deprivation on item and associative recognition memoryJournal of Experimental Psychology: Learning, Memory and Cognition, 44, 193-208.

Ratcliff, R. & Van Dongen, H.P.A. (2011). A diffusion model for one-choice reaction time tasks and the cognitive effects of sleep deprivation. Proceedings of the National Academy of Sciences, 108, 11285-11290. Supplementary material available here.

Ratcliff, R. & Van Dongen, H.P.A. (2009). Sleep deprivation affects multiple distinct cognitive processes. Psychonomic Bulletin and Review,16, 742-751.