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Results: 69
Number of items: 69
  • Open Access
    Boehm, U., Matzke, D., Gretton, M., Castro, S., Cooper, J., Skinner, M., Strayer, D., & Heathcote, A. (2021). Real-time prediction of fluctuations in cognitive workload. Cognitive Research: Principles and Implications, 6, Article 30. https://doi.org/10.1186/s41235-021-00289-y
  • Open Access
    Miletić, S., Boag, R. J., Trutti, A. C., Stevenson, N., Forstmann, B. U., & Heathcote, A. (2021). A new model of decision processing in instrumental learning tasks. eLife, 10, Article e63055. https://doi.org/10.7554/eLife.63055
  • Open Access
    Matzke, D., Logan, G. D., & Heathcote, A. (2020). A Cautionary Note on Evidence-Accumulation Models of Response Inhibition in the Stop-Signal Paradigm. Computational Brain & Behavior, 3(3), 269–288. https://doi.org/10.1007/s42113-020-00075-x
  • Open Access
    Skippen, P., Fulham, W. R., Michie, P. T., Matzke, D., Heathcote, A., & Karayanidis, F. (2020). Reconsidering electrophysiological markers of response inhibition in light of trigger failures in the stop-signal task. Psychophysiology, 57(10), Article e13619. https://doi.org/10.1111/psyp.13619
  • Open Access
    Gronau, Q. F., Heathcote, A., & Matzke, D. (2020). Computing Bayes factors for evidence-accumulation models using Warp-III bridge sampling. Behavior Research Methods, 52(2), 918-937. https://doi.org/10.3758/s13428-019-01290-6
  • Open Access
    Verbruggen, F., Aron, A. R., Band, G. P. H., Beste, C., Bissett, P. G., Brockett, A. T., Brown, J. W., Chamberlain, S. R., Chambers, C. D., Colonius, H., Colzato, L. S., Corneil, B. D., Coxon, J. P., Dupuis, A., Eagle, D. M., Garavan, H., Greenhouse, I., Heathcote, A., Huster, R. J., ... Boehler, C. N. (2019). A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task. eLife, 8, Article e46323. https://doi.org/10.7554/eLife.46323
  • Open Access
    Skippen, P., Matzke, D., Heathcote, A., Fulham, W. R., Michie, P., & Karayanidis, F. (2019). Reliability of triggering inhibitory process is a better predictor of impulsivity than SSRT. Acta Psychologica, 192, 104-117. https://doi.org/10.1016/j.actpsy.2018.10.016
  • Open Access
    Heathcote, A., Lin, Y.-S., Reynolds, A., Strickland, L., Gretton, M., & Matzke, D. (2019). Dynamic models of choice. Behavior Research Methods, 51(2), 961-985. https://doi.org/10.3758/s13428-018-1067-y
  • Open Access
    Dutilh, G., Annis, J., Brown, S. D., Cassey, P., Evans, N. J., Grasman, R. P. P. P., Hawkins, G. E., Heathcote, A., Holmes, W. R., Krypotos, A.-M., Kupitz, C. N., Leite, F. P., Lerche, V., Lin, Y.-S., Logan, G. D., Palmeri, T. J., Starns, J. J., Trueblood, J. S., van Maanen, L., ... Donkin, C. (2019). The Quality of Response Time Data Inference: A Blinded, Collaborative Assessment of the Validity of Cognitive Models. Psychonomic Bulletin & Review, 26(4), 1051-1069. https://doi.org/10.3758/s13423-017-1417-2
  • Open Access
    Matzke, D., Curley, S., Gong, C. Q., & Heathcote, A. (2019). Inhibiting Responses to Difficult Choices. Journal of Experimental Psychology: General, 148(1), 124-142. https://doi.org/10.1037/xge0000525
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