Publications

Elliott, D., Strickland, L., Loft, S., & Heathcote, A. (2022). Integrated responding improves prospective memory accuracy. Psychonomic Bulletin & Review, 29, 934-942.

Schnuerch, M., Haaf, J. M., Sarafoglou, A., & Rouder, J. N. (2022). Meaningful comparisons with ordinal-scale items. Collabra: Psychology, 8(1), 38594.

Sarafoglou, A., Aust, F., Marsman, M., Wagenmakers, E.-J., & Haaf, J. M. (submitted). multibridge: An R package to evaluate informed hypotheses in Binomial and Multinomial models. PsyArXiv.

Rouder, J. N., Kumar, A., & Haaf, J. M. (submitted). Why Most Studies of Individual Differences With Inhibition Tasks Are Bound To Fail. PsyArxiv.

Rouder, J. N., & Haaf, J. M. (submitted). Optional Stopping and the Interpretation of The Bayes Factor. PsyArXiv.

Hoogeveen, S., Haaf, J. M., Bulbulia, J. A., Ross, R. M., McKay, R., Altay, S., … & van Elk, M. (2022). The Einstein effect provides global evidence for scientific source credibility effects and the influence of religiosity. Nature Human Behaviour, 6(4), 523-535.

[PsyArXiv]

Van Geert, E., Moors, P., Haaf, J. M., & Wagemans, J. (2022). Same Stimulus, Same Temporal Context, Different Percept? Individual Differences in Hysteresis and Adaptation When Perceiving Multistable Dot Lattices. i-Perception, 13(4), 20416695221109300.

[Stage 1 registered report]

Donzallaz, M., Haaf, J. M., & Stevenson, C. (2022). Creative or Not? Hierarchical Diffusion Modeling of the Creative Evaluation Process. Journal of Experimental Psychology: Learning, Memory, and Cognition. Advance online publication. [Preprint]

Heck, D. W., Boehm, U., Boeing-Messing, F., Buerkner, P.-C., Derks, K.,…, & Hoijtink, H. (in press).
A review of applications of the Bayes factor in psychological research. Psychological Methods.

Tanis, C. C., Nauta, F. H., Boersma, M. J., Van der Steenhoven, M. V., Borsboom, D., & Blanken, T. F. (2022). Practical behavioural solutions to COVID-19: Changing the role of behavioural science in crises. PloS one, 17(10), e0272994. [Dataset]

Kucina, T., Wells, L., Lewis, I., de Salas, K., Kohl, A., Palmer, M., Sauer, J.D., Matzke, D., Aidman, E., & Heathcote, A. (2022). A solution to the reliability paradox for decision-conflict tasks. Manuscript submitted for publication.

Heathcote, A., & Matzke, D. (2022). Winner takes all! What are race models, and why and how should psychologists use them? Current Directions in Psychological Science, 31, 383-394.

He, J. L., Hirst, R. J., Puri, R., Coxon, J., Byblow, W., Hinder, M., Skippen, P., Matzke, D., Heathcote, A., Wadsley, C. G., Hyde, C., Parmar, D., Pedapati, E., Gilbert, D. L., Huddleston, D. A., Mostofsky, S., Leunissen, I., MacDonald, H. J.,  Chowdhury, N. S., Gretton, M., Nikitenko, T., Zandbelt, B., Strickland, S., Puts, N. A. J. (2022). OSARI, an open-source anticipated response inhibition task. Behavior Research Methods, 54, 1530–1540.

Castro, S., Heathcote, A., Cooper, J., & Strayer, D. (accepted 16/3/2022). Dynamic workload measurement and modeling: Driving and conversing. Journal of Experimental Psychology: Applied.

Nunez, M. D., Vandekerckhove, J., & Srinivasan, R. (2022). A tutorial on fitting joint models of M/EEG and behavior to understand cognition. Preprint.

Heathcote, A., Garton, R., Hinder, M.R., Reynolds, A., Tanis, C., & Matzke, D. (2022). Slower processing dominates executive-function deficits in cognitive aging. Manuscript submitted for publication.

Tanis, C.C., Heathcote, A., Zrubka, M., & Matzke, D. (2022). A hybrid approach to dynamic cognitive psychometrics. Manuscript submitted for publication.

Ghaderi-Kangavari, A., Amani Rad, J., Parand, K. & Nunez, M.D. (2022). Neuro-cognitive models of single-trial EEG measures describe latent effects of spatial attention during perceptual decision making. bioRxiv.

Hawkins, G. E., Mittner, M., Forstmann, B. U., & Heathcote, A. (2022). Self-reported mind wandering reflects executive control and selective attention. Psychonomic Bulletin & Review, 29, 2167-2180.

Choo, Y., Matzke, D., Bowren, M. D, Tranel, D., & Wessel, J. R. (2022). Right inferior frontal gyrus damage is associated with impaired initiation of inhibitory control, but not its implementation. eLife, 11:e79667.

Sebastian, A., Forstmann, B.U., & Matzke, D. (2022). Reliability of triggering the stop process is related to prefrontal-subthalamic hyperdirect pathway recruitment. Manuscript submitted for publication. 

Strickland, L., Heathcote, A., Humphreys, M. S., & Loft, S. (2022). Target learning in event-based prospective memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 48, 1110-1126.

Kvam, P., Marley, A. A. J., & Heathcote, A. (2022). A unified theory of discrete and continuous responding. Psychological Review. 

Ghaderi-Kangavari, A., Rad, J. A., & Nunez, M. D. (2022). A general integrative neurocognitive modeling framework to jointly describe EEG and decision-making on single trials. PsycArXiv Preprints.

Sun, Q. J., Vo, K., Lui, K., Nunez, M., Vandekerckhove, J., & Srinivasan, R. (2022). Decision SincNet: Neurocognitive models of decision making that predict cognitive processes from neural signals. arXiv preprint arXiv:2208.02845.

Aidman, E., Fogarty, G. J., Crampton, J., Bond, J., Taylor, P., Heathcote, A., & Zaichkowsky, L. (2022). An app-enhanced cognitive fitness training program for athletes: The rationale and validation protocol. Frontiers in Psychology, 13, 957551.

Kumar, A., Benjamin, A. S., Heathcote, A., & Steyvers, M. (2022). Comparing models of learning and relearning in large-scale cognitive training data sets. npj Science of Learning, 7, 24.

Isherwood, S.J.S, Bazin, P.L., Miletic, S., Trutti, A.C., Tse, D.H.Y, Stevenson, N.R., Heathcote, A., Matzke, D., Innes, R.J., Habli, S., Sokolowski, D.R., Goa, P.E., Alkemade, A., Haberg, A.K., & Forstmann, B.U. Intra-individual networks of response inhibition and interference resolution at 7T. Manuscript submitted for publication. 

Strickland, L., Boag, R.J., Heathcote, A., Bowden, V., & Loft, S. (2022).  Automated decision aids: When are they advisors and when do they take control of human decision making? Journal of Experimental Psychology: Applied.

Boag, R.J., Strickland, L., Heathcote, A., Neal, A., Palada, H., & Loft, S. (2022). Evidence accumulation modelling in the wild: Understanding safety-critical decisions. Trends in Cognitive Sciences, 27, 175-188. 

Damaso, K. A. M., Williams, P. G., & Heathcote, A. (2022). What happens after a fast versus slow error, and how does it relate to evidence accumulation? Computational Brain & Behavior, 5, 527–546.

Rouder, J. N., Schnuerch, M., Haaf, J. M., & Morey, R. D. (2022). Principles of Model Specification in ANOVA Designs. Computational Brain & Behavior, 1-14.

Bartoš, F., Aust, F., & Haaf, J. M. (2022). Informed Bayesian survival analysis. BMC Medical Research Methodology, 22, 238.

Ballard, T., Neal, A., Farrell, S., Lloyd, E., Lim, J., & Heathcote, A. (2022). A general architecture for modeling the dynamics of goal-directed motivation and decision making. Psychological Review, 129, 146-174.

Elliott, J. G. C., Gilboa-Schechtman, E., Grigorenko, E. L., Heathcote, A., Purdie-Greenaway, V. J., Uddin, L. Q., van der Maas, H. L. J., & Waldmann, M. R. (2022). Editorial. Psychological Review, 129, 1-3.

Nunez, M. D., Charupanit, K., Sen-Gupta, I., Lopour, B. A., & Lin, J. J. (2022). Beyond rates: Time-varying dynamics of high frequency oscillations as a biomarker of the seizure onset zone. Journal of Neural Engineering, 19, 016034.

Dablander, F*., Blanken, T. F*., Tanis, C. C*., Breed, R., Coffeng, L. E., Crommelin, D., … Borsboom, D. (2022). A Multidisciplinary Perspective on COVID-19 Exit Strategies. PsyArXiv.
[* shared first authorship]

Borsboom, D., Blanken, T. F., Dablander, F., Tanis, C. C., Van Harreveld, F., & Van Mieghem, P. (2022). The lighting of the BECONs: A behavioral data science approach to tracking interventions in COVID-19 research. Journal of Behavioral Data Science, 2(1), 1–34.

Damaso, K.A.M., Castro, S.C., Todd, J., Strayer, D.L., Provost, A., Matzke, D., & Heathcote, A.J. (2022). A cognitive model of response omissions in distraction paradigms. Memory & Cognition, 50, 962-978. [Supplementary Materials]

Sutton, K., Heathcote, A., & Bore, M. (2007). Measuring 3-D understanding on the Web and in the laboratory. Behavior Research Methods, 39(4), 926–939.

Heathcote, A., Brown, S., & Cousineau, D. (2004). QMPE: Estimating Lognormal, Wald, and Weibull RT distributions with a parameter-dependent lower bound. Behavior Research Methods, Instruments, & Computers, 36(2), 277–290.

Heathcote, A. (2004). Fitting Wald and ex-Wald distributions to response time data: An example using functions for the S-PLUS package. Behavior Research Methods, Instruments, & Computers, 36(4), 678–694.

Cousineau, D., Brown, S., & Heathcote, A. (2004). Fitting distributions using maximum likelihood: Methods and packages. Behavior Research Methods, Instruments, & Computers, 36(4), 742–756.

Heathcote, A., & Brown, S. (2004). Beyond curve fitting? Comment on Liu, Mayer-Kress, and Newell (2003). Journal of Motor Behavior, 36(2), 225–232.

Heathcote, A., & Brown, S. (2004). Reply to Speckman and Rouder: A theoretical basis for QML. Psychonomic Bulletin & Review, 11(3), 577–578.

Heathcote, A., Brown, S., & Mewhort, D. J. K. (2000). The power law repealed: The case for an exponential law of practice. Psychonomic Bulletin & Review, 7(2), 185–207.

Treloar, C., McCall, N., Rolfe, I., Pearson, S.-A., Garvey, G., & Heathcote, A. (2000). Factors affecting progress of Australian and international students in a problem-based learning medical course. Medical Education, 34(9), 708–715.

Heathcote, A., & Brown, S. (2000). The law of practice and localist neural network models. Comment on Page, M., Connectionist modelling in psychology: A localist Manifesto. Behavioral and Brain Sciences, 23(4), 479–480.

Hill, J., Rolfe, I. E., Pearson, S.-A., & Heathcote, A. (1998). Do junior doctors feel they are prepared for hospital practice? A study of graduates from traditional and non-traditional medical schools. Medical Education, 32(1), 19–24.