Welcome to the website of the Tasmanian Cognition Laboratory.
The primary aim of the Tasmanian Cognition Laboratory (TASCL) is the experimental investigation of cognitive processes that underpin decision making, language, attention, memory, and learning. The TASCL research group has two broad foci: (1) mathematical and computational cognitive models (2) the application of cognitive psychology to applied problems.
The cognitive modelling focus on broadly applicable evidence accumulation and race models that provide a comprehensive account of behaviour, both in terms of responses that are made and the time it takes to make them. We both contribute to the fundamental development of these models and push the boundaries of their application across psychology and the neurosciences. Applied areas of interest are diverse, and include improving the reliability of eyewitness identification evidence; helping people to better evaluate their own memory, learning, and decision making (i.e., metacognition); investigating the cognitive effects of videogame play; understanding how to enhance public support for climate science and associated policy; and complex and high-pressure decision making in defence and Antarctic contexts. Our research is supported by a number of testing suites with high-end data collection PCs, accompanied by office space for graduate students, in both the Psychology Building and Psychology Research Centre, as well as access to high-performance computers for computational modelling.
Publications with associated pdf files can be found in the publications area. In some cases there are also links to associated data and analysis software (see also the Data and Software area of the site). We gratefully acknowledge support from funding bodies, particularly the Australian Research Council (see the Funding area of the site).
The primary aim of the Tasmanian Cognition Laboratory (TASCL) is the experimental investigation of cognitive processes that underpin decision making, language, attention, memory, and learning. The TASCL research group has two broad foci: (1) mathematical and computational cognitive models (2) the application of cognitive psychology to applied problems.
The cognitive modelling focus on broadly applicable evidence accumulation and race models that provide a comprehensive account of behaviour, both in terms of responses that are made and the time it takes to make them. We both contribute to the fundamental development of these models and push the boundaries of their application across psychology and the neurosciences. Applied areas of interest are diverse, and include improving the reliability of eyewitness identification evidence; helping people to better evaluate their own memory, learning, and decision making (i.e., metacognition); investigating the cognitive effects of videogame play; understanding how to enhance public support for climate science and associated policy; and complex and high-pressure decision making in defence and Antarctic contexts. Our research is supported by a number of testing suites with high-end data collection PCs, accompanied by office space for graduate students, in both the Psychology Building and Psychology Research Centre, as well as access to high-performance computers for computational modelling.
Publications with associated pdf files can be found in the publications area. In some cases there are also links to associated data and analysis software (see also the Data and Software area of the site). We gratefully acknowledge support from funding bodies, particularly the Australian Research Council (see the Funding area of the site).
Recent Publications:
In Press:
- Reynolds, A., Kvam, P., Osth, A. & Heathcote, A. (accepted 18/2/2020). Correlated racing evidence accumulator models. Journal of Mathematical Psychology.
- Matzke, D., Logan, G. D. & Heathcote, A. (accepted 13/2/2020). A cautionary note on evidence-accumulation models of response inhibition in the stop-signal paradigm. Computational Brain & Behavior.
- Damaso, K., Williams, P. & Heathcote, A. (accepted 16/9/2019). Different types of errors and post-error changes. Psychonomic Bulletin & Review. (Supplementary Material)
- Heathcote, A. (accepted 27/8/2019). What do the rules for the wrong game tell us about how to play the right game? Computational Brain & Behavior.
- Lin, Y. S., & Strickland, L. (accepted 12/8/2019). Evidence accumulation models with R: A practical guide to hierarchical Bayesian methods. The Quantitative Methods for Psychology.
- van Ravenzwaaij, D., Brown, S.D., Marley, A.J., & Heathcote, A. (accepted 29/7/2019). Accumulating Advantages: A New Conceptualization of Rapid Multiple Choice. Psychological Review. doi: 10.1037/rev0000166
- Gronau, Q. F., Heathcote, A. & Matzke, D. (accepted 3/8/2019). Computing Bayes Factors for evidence-accumulation models using Warp-III Bridge Sampling. Behavior Research Methods. https://psyarxiv.com/9g4et
- Starns, J. J., Cataldo, A.M., Rotello, C. M., Annis, J., Aschenbrenner, A., Bröder, A., Cox, G., Criss, A., Curl, R. A., Dobbins, I. G., Dunn, J., Enam, T., Evans, N. J., Farrell, S., Fraundorf, S. H., Gronlund, S. D., Heathcote, A., Heck, A. D. W., Hicks, J. L., Huff, M. J., Kellen, D., Key, K. N., Kilic, A., Klauer, K. C., Kraemer, K. R., Leite, F. P., Lloyd, M. E., Malejka, S., Mason, A., McAdoo, R. M., McDonough, I. M., Michael, R. B., Mickes, L., Mizrak, E., Morgan, D. P., Mueller, S. T., Osth, A., Reynolds, A., Seale-Carlisle, T. M., Singmann, H., Sloane, J. F., Smith, A. M., Tillman, G., van Ravenzwaaij, D., Weidemann, C. T., Wells, G. L., White, C. N., Wilson, J. (accepted 14/6/2019). Assessing theoretical conclusions with blinded inference to investigate a potential inference crisis. Advances in Methods and Practices in Psychological Science. (Supplementary Material)
- Osth, A., Racliff, R., Dunn, J., & Heathcote, A. (accepted 22/5/2019). Two processes are not necessary to understand memory deficits. Behavioral and Brain Sciences.
- Palada, H., Neal, A., Strayer, D., Ballard, T., & Heathcote, A. (accepted 3/5/2019). Competing for cognitive resources: Measuring workload in a time pressured dual-task environment. Journal of Experimental Psychology: Human Perception and Performance. https://psyarxiv.com/bckat/ OSF: https://osf.io/rsn9j/
- Strickland, L., Elliott, D., Wilson, M.D., Loft, S., Neal, A., & Heathcote, A. (accepted 20/2/2019). Prospective memory in the red zone: Cognitive control and capacity sharing in a complex, multi-stimulus task. Journal of Experimental Psychology: Applied. (Supplementary Material)
- Boag, R., Strickland, L., Heathcote, A., Neal, A., & Loft., S. (2019). Cognitive Control and Capacity for Prospective Memory in Simulated Air Traffic Control. Journal of Experimental Psychology: General, 148, 2181-2206.
- Weigard, A., Matzke, D., Heathcote, A., Huang-Pollock, C., (accepted 29/11/2018). Cognitive modeling suggests that attentional failures drive longer stop-signal reaction time estimates in ADHD. Clinical Psychological Science, osf.io/7gmdv/
- Weigard, A., Huang-Pollock, C., Heathcote, A., Hawk Jr., L., & Schlienz, N.J. (accepted 20/8/2018). A cognitive model-based approach to testing mechanistic explanations for neuropsychological decrements during tobacco abstinence. Psychopharmacology. (Supplementary Material)
- Heathcote, A., Lin, Y. S., Reynolds, A., Strickland, L., Gretton, M., & Matzke, D. (accepted 30/May/2018). Dynamic models of choice. Behavior Research Methods. doi: 10.3758/s13428-018-1067-y
- Lin, Y.-S., & Heathcote, A. (in preparation). ggdmc: An R package for hierarchical Bayesian evidence accumulation models, using differential evolution Markov Chain Monte Carlo Sampler. Retrieved from https://github.com/TasCL/ggdmc
In Print:
- van Berkel, N., Dennis, S., Zyphur, M., Li, J., Heathcote, A. & Kostakos, V. (2020). Modeling interaction as a complex system. Human-Computer Interaction, https://doi.org/10.1080/07370024.2020.1715221
- Lin, Y-S., Heathcote, A. & Holmes, W.R. (2019). Parallel probability density approximation. Behavior Research Methods, 51, 2777–2799.
doi: 10.3758/s13428-018-1153-1
- Wilson, M. D., Strickland, L., Farrell, S., Visser, T. A. W., & Loft, S. (2019). Prospective Memory Performance in Simulated Air Traffic Control: Robust to Interruptions but Impaired by Retention Interval. Human Factors. https://doi.org/10.1177/00187208198
- Wilson, M. D., Boag, R. J., & Strickland, L. (2019). All models are wrong, some are useful, but are they reproducible? Commentary on Lee et al. (2019), Computational Brain & Behavior, 2, 239–24. https://doi.org/10.1007/s42113-019-00054-x
- Garton, R., Reynolds, A., Hinder, M. R., & Heathcote, A. (2019). Equally flexible and optimal response bias in older compared to younger adults. Psychology and Aging, 34(6), 821-835. (Supplementary Material) doi.org/10.1037/pag0000339
- Weigard, A., Heathcote, A., & Sripada, C. S. (2019). Modeling the effects of Methylphenidate on conflict, top-down control, and evidence accumulation using the Conflict Linear Ballistic Accumulator. Psychopharmacology. SharedIt Link
- Boag, R., Strickland, L., Loft, S., & Heathcote, A. (2019). Strategic attention and decision control support prospective memory in a complex dual-task environment. Cognition, 191,103974. doi: 10.1016/j.cognition.2019.05.011
- Tan, J., Iyer, K. K., Tang, A. D., Jamil, A., Martins, R. N., Sohrabi, H. R., Nitsche, M. A., Hinder, M. R., & Fujiyama, H. (2019). Modulating functional connectivity with non-invasive brain stimulation for the investigation and alleviation of age-associated declines in response inhibition: A narrative review. Neuroimage, 185, 490-512. doi: 10.1016/j.neuroimage.2018.10.044
- Vallence, A-M., Hinder, M. R., & Fujiyama, H. (2019). Data-driven selection of conference speakers based on scientific impact to achieve gender parity. PLOS One, 14(7):e0220481. doi: 10.1371/journal.pone.0220481
- Weigard, A., Heathcote, A., Matzke, D., Huang-Pollock, C. (2019). Cognitive Modeling Suggests That Attentional Failures Drive Longer Stop-Signal Reaction Time Estimates in Attention Deficit/Hyperactivity Disorder. Clinical Psychological Science, 7(4), 856-872. osf.io/7gmdv/
- Lin, Y-S., Heathcote, A., & Holmes, W.R. (2019). Parallel probability density approximation. Behavior Research Methods. Springer Share Link.
- 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., Eagle, D. M., Dupuis, A., Garavan, H., Greenhouse, I., Heathcote, A., Huster, R. J., Jahfari, S., Kenemans, J. L., Leunissen, I., Logan, G. D., Matzke, D., Morein-Zamir, S., Murthy, A., Li, C. S. R., Paré, M., Poldrack, R. A., Ridderinkhof, K. R., Robbins, T. W., Roesch, M. R., Rubia, K., Schachar, R. J., Schall, J. D., Stock, A-K., Swann, N. C., Thakkar, K. N., van der Molen, M. W., Vermeylen, L., Vink, M., Wessel, J. R., Whelan, R., Zandbelt, B. B., Boehler, C. N. (2019). A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task. eLife 2019;8:e46323, doi: 10.7554/eLife.46323, https://elifesciences.org/articles/46323
- Bird, L., Cockerell, R., Gretton, M., Heathcote, A. (2019). The Cognitive Load of Narrative Lies. Applied Cognitive Psychology, 33, 936-942. doi: 10.1002/acp.3567
- Tupper, N., Sauerland, M., Sauer, J.D., & Hope, L. (2019, online). Eyewitness identification procedures for multiple perpetrator crimes: a survey of police in Sweden, Belgium, and the Netherlands. Psychology, Crime & Law. doi.org/10.1080/1068316X.2019.1611828
- Drummond, A., Sauer, J.D., & Hall, L.C. (2019). Loot box limit‐setting: a potential policy to protect video game users with gambling problems? Addiction, 114, 934-936. doi/abs/10.1111/add.14583
- Rainsford, M., Palmer, M.A., & Sauer, J.D., (2019). The Distinctiveness Effect in the Recognition of Whole Melodies. Music Perception: An Interdisciplinary Journal, 36, 253-272. doi: 10.1525/mp.2019.36.3.253
- Monds, L.A., Kloft, L., Sauer, J.D., Honan, C.A., & Palmer, M.A. (2019). No evidence that alcohol intoxication impairs judgments of learning in face recognition. Applied Cognitive Psychology, 33, 325-333. doi: 10.1002/acp.3534
- Dunn, J.C., Heathcote, A., Kalish, M. (2019). Special issue on state-trace analysis. Journal of Mathematical Psychology, 90, 1-3.
- Hawkins, G.E., Mittner, M., Forstmann, B.U., & Heathcote, A. (2019). Modeling distracted performance. Cognitive Psychology, 112, 48-80. https://psyarxiv.com/j86sd, doi: 10.1016/j.cogpsych.2019.05.002
- Castro, S., Strayer, D., Matzke, D., & Heathcote, A. (2019). Cognitive workload measurement and modelling under divided attention. Journal of Experimental Psychology: Human Perception & Performance. doi: 10.1037/xhp0000638
- Matzke, D., Curley, S., Gong, C.Q., & Heathcote, A. (2019). Inhibiting responses to difficult choices. Journal of Experimental Psychology: General, 148, 124-142.
- Skippen, P., Matzke, D., Heathcote, A., Fulham, W., Michie, P., & Karayanidis, F. (2019). Reliability of triggering inhibitory process is a better predictor of impulsivity than SSRT. Acta Psychologica, 192, 104-117, https://psyarxiv.com/vg5rd/
- Heathcote, A., Holloway, E., & Sauer, J.D. (2019). Confidence and varieties of bias. Journal of Mathematical Psychology, 90, 31-46. doi: 10.1016/j.jmp.2018.10.002
Book Chapters:
-Strickland, L., Loft, S., & Heathcote, A. (2019). Evidence Accumulation Modeling of Event-Based Prospective Memory. In J. Rummel & M.A. McDaniel (Eds), Current Issues in Memory: Prospective Memory (pp. 78-94). London, United Kingdom: Taylor & Francis.
Technical Reports:
- French, B., Duenser, A., Heathcote, A. (2018). Trust in Automation – A Literature Review. CSIRO Report EP184082. CSIRO, Australia.
For any questions related to this site please email:
contact@tascl.org
In Press:
- Reynolds, A., Kvam, P., Osth, A. & Heathcote, A. (accepted 18/2/2020). Correlated racing evidence accumulator models. Journal of Mathematical Psychology.
- Matzke, D., Logan, G. D. & Heathcote, A. (accepted 13/2/2020). A cautionary note on evidence-accumulation models of response inhibition in the stop-signal paradigm. Computational Brain & Behavior.
- Damaso, K., Williams, P. & Heathcote, A. (accepted 16/9/2019). Different types of errors and post-error changes. Psychonomic Bulletin & Review. (Supplementary Material)
- Heathcote, A. (accepted 27/8/2019). What do the rules for the wrong game tell us about how to play the right game? Computational Brain & Behavior.
- Lin, Y. S., & Strickland, L. (accepted 12/8/2019). Evidence accumulation models with R: A practical guide to hierarchical Bayesian methods. The Quantitative Methods for Psychology.
- van Ravenzwaaij, D., Brown, S.D., Marley, A.J., & Heathcote, A. (accepted 29/7/2019). Accumulating Advantages: A New Conceptualization of Rapid Multiple Choice. Psychological Review. doi: 10.1037/rev0000166
- Gronau, Q. F., Heathcote, A. & Matzke, D. (accepted 3/8/2019). Computing Bayes Factors for evidence-accumulation models using Warp-III Bridge Sampling. Behavior Research Methods. https://psyarxiv.com/9g4et
- Starns, J. J., Cataldo, A.M., Rotello, C. M., Annis, J., Aschenbrenner, A., Bröder, A., Cox, G., Criss, A., Curl, R. A., Dobbins, I. G., Dunn, J., Enam, T., Evans, N. J., Farrell, S., Fraundorf, S. H., Gronlund, S. D., Heathcote, A., Heck, A. D. W., Hicks, J. L., Huff, M. J., Kellen, D., Key, K. N., Kilic, A., Klauer, K. C., Kraemer, K. R., Leite, F. P., Lloyd, M. E., Malejka, S., Mason, A., McAdoo, R. M., McDonough, I. M., Michael, R. B., Mickes, L., Mizrak, E., Morgan, D. P., Mueller, S. T., Osth, A., Reynolds, A., Seale-Carlisle, T. M., Singmann, H., Sloane, J. F., Smith, A. M., Tillman, G., van Ravenzwaaij, D., Weidemann, C. T., Wells, G. L., White, C. N., Wilson, J. (accepted 14/6/2019). Assessing theoretical conclusions with blinded inference to investigate a potential inference crisis. Advances in Methods and Practices in Psychological Science. (Supplementary Material)
- Osth, A., Racliff, R., Dunn, J., & Heathcote, A. (accepted 22/5/2019). Two processes are not necessary to understand memory deficits. Behavioral and Brain Sciences.
- Palada, H., Neal, A., Strayer, D., Ballard, T., & Heathcote, A. (accepted 3/5/2019). Competing for cognitive resources: Measuring workload in a time pressured dual-task environment. Journal of Experimental Psychology: Human Perception and Performance. https://psyarxiv.com/bckat/ OSF: https://osf.io/rsn9j/
- Strickland, L., Elliott, D., Wilson, M.D., Loft, S., Neal, A., & Heathcote, A. (accepted 20/2/2019). Prospective memory in the red zone: Cognitive control and capacity sharing in a complex, multi-stimulus task. Journal of Experimental Psychology: Applied. (Supplementary Material)
- Boag, R., Strickland, L., Heathcote, A., Neal, A., & Loft., S. (2019). Cognitive Control and Capacity for Prospective Memory in Simulated Air Traffic Control. Journal of Experimental Psychology: General, 148, 2181-2206.
- Weigard, A., Matzke, D., Heathcote, A., Huang-Pollock, C., (accepted 29/11/2018). Cognitive modeling suggests that attentional failures drive longer stop-signal reaction time estimates in ADHD. Clinical Psychological Science, osf.io/7gmdv/
- Weigard, A., Huang-Pollock, C., Heathcote, A., Hawk Jr., L., & Schlienz, N.J. (accepted 20/8/2018). A cognitive model-based approach to testing mechanistic explanations for neuropsychological decrements during tobacco abstinence. Psychopharmacology. (Supplementary Material)
- Heathcote, A., Lin, Y. S., Reynolds, A., Strickland, L., Gretton, M., & Matzke, D. (accepted 30/May/2018). Dynamic models of choice. Behavior Research Methods. doi: 10.3758/s13428-018-1067-y
- Lin, Y.-S., & Heathcote, A. (in preparation). ggdmc: An R package for hierarchical Bayesian evidence accumulation models, using differential evolution Markov Chain Monte Carlo Sampler. Retrieved from https://github.com/TasCL/ggdmc
In Print:
- van Berkel, N., Dennis, S., Zyphur, M., Li, J., Heathcote, A. & Kostakos, V. (2020). Modeling interaction as a complex system. Human-Computer Interaction, https://doi.org/10.1080/07370024.2020.1715221
- Lin, Y-S., Heathcote, A. & Holmes, W.R. (2019). Parallel probability density approximation. Behavior Research Methods, 51, 2777–2799.
doi: 10.3758/s13428-018-1153-1
- Wilson, M. D., Strickland, L., Farrell, S., Visser, T. A. W., & Loft, S. (2019). Prospective Memory Performance in Simulated Air Traffic Control: Robust to Interruptions but Impaired by Retention Interval. Human Factors. https://doi.org/10.1177/00187208198
- Wilson, M. D., Boag, R. J., & Strickland, L. (2019). All models are wrong, some are useful, but are they reproducible? Commentary on Lee et al. (2019), Computational Brain & Behavior, 2, 239–24. https://doi.org/10.1007/s42113-019-00054-x
- Garton, R., Reynolds, A., Hinder, M. R., & Heathcote, A. (2019). Equally flexible and optimal response bias in older compared to younger adults. Psychology and Aging, 34(6), 821-835. (Supplementary Material) doi.org/10.1037/pag0000339
- Weigard, A., Heathcote, A., & Sripada, C. S. (2019). Modeling the effects of Methylphenidate on conflict, top-down control, and evidence accumulation using the Conflict Linear Ballistic Accumulator. Psychopharmacology. SharedIt Link
- Boag, R., Strickland, L., Loft, S., & Heathcote, A. (2019). Strategic attention and decision control support prospective memory in a complex dual-task environment. Cognition, 191,103974. doi: 10.1016/j.cognition.2019.05.011
- Tan, J., Iyer, K. K., Tang, A. D., Jamil, A., Martins, R. N., Sohrabi, H. R., Nitsche, M. A., Hinder, M. R., & Fujiyama, H. (2019). Modulating functional connectivity with non-invasive brain stimulation for the investigation and alleviation of age-associated declines in response inhibition: A narrative review. Neuroimage, 185, 490-512. doi: 10.1016/j.neuroimage.2018.10.044
- Vallence, A-M., Hinder, M. R., & Fujiyama, H. (2019). Data-driven selection of conference speakers based on scientific impact to achieve gender parity. PLOS One, 14(7):e0220481. doi: 10.1371/journal.pone.0220481
- Weigard, A., Heathcote, A., Matzke, D., Huang-Pollock, C. (2019). Cognitive Modeling Suggests That Attentional Failures Drive Longer Stop-Signal Reaction Time Estimates in Attention Deficit/Hyperactivity Disorder. Clinical Psychological Science, 7(4), 856-872. osf.io/7gmdv/
- Lin, Y-S., Heathcote, A., & Holmes, W.R. (2019). Parallel probability density approximation. Behavior Research Methods. Springer Share Link.
- 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., Eagle, D. M., Dupuis, A., Garavan, H., Greenhouse, I., Heathcote, A., Huster, R. J., Jahfari, S., Kenemans, J. L., Leunissen, I., Logan, G. D., Matzke, D., Morein-Zamir, S., Murthy, A., Li, C. S. R., Paré, M., Poldrack, R. A., Ridderinkhof, K. R., Robbins, T. W., Roesch, M. R., Rubia, K., Schachar, R. J., Schall, J. D., Stock, A-K., Swann, N. C., Thakkar, K. N., van der Molen, M. W., Vermeylen, L., Vink, M., Wessel, J. R., Whelan, R., Zandbelt, B. B., Boehler, C. N. (2019). A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task. eLife 2019;8:e46323, doi: 10.7554/eLife.46323, https://elifesciences.org/articles/46323
- Bird, L., Cockerell, R., Gretton, M., Heathcote, A. (2019). The Cognitive Load of Narrative Lies. Applied Cognitive Psychology, 33, 936-942. doi: 10.1002/acp.3567
- Tupper, N., Sauerland, M., Sauer, J.D., & Hope, L. (2019, online). Eyewitness identification procedures for multiple perpetrator crimes: a survey of police in Sweden, Belgium, and the Netherlands. Psychology, Crime & Law. doi.org/10.1080/1068316X.2019.1611828
- Drummond, A., Sauer, J.D., & Hall, L.C. (2019). Loot box limit‐setting: a potential policy to protect video game users with gambling problems? Addiction, 114, 934-936. doi/abs/10.1111/add.14583
- Rainsford, M., Palmer, M.A., & Sauer, J.D., (2019). The Distinctiveness Effect in the Recognition of Whole Melodies. Music Perception: An Interdisciplinary Journal, 36, 253-272. doi: 10.1525/mp.2019.36.3.253
- Monds, L.A., Kloft, L., Sauer, J.D., Honan, C.A., & Palmer, M.A. (2019). No evidence that alcohol intoxication impairs judgments of learning in face recognition. Applied Cognitive Psychology, 33, 325-333. doi: 10.1002/acp.3534
- Dunn, J.C., Heathcote, A., Kalish, M. (2019). Special issue on state-trace analysis. Journal of Mathematical Psychology, 90, 1-3.
- Hawkins, G.E., Mittner, M., Forstmann, B.U., & Heathcote, A. (2019). Modeling distracted performance. Cognitive Psychology, 112, 48-80. https://psyarxiv.com/j86sd, doi: 10.1016/j.cogpsych.2019.05.002
- Castro, S., Strayer, D., Matzke, D., & Heathcote, A. (2019). Cognitive workload measurement and modelling under divided attention. Journal of Experimental Psychology: Human Perception & Performance. doi: 10.1037/xhp0000638
- Matzke, D., Curley, S., Gong, C.Q., & Heathcote, A. (2019). Inhibiting responses to difficult choices. Journal of Experimental Psychology: General, 148, 124-142.
- Skippen, P., Matzke, D., Heathcote, A., Fulham, W., Michie, P., & Karayanidis, F. (2019). Reliability of triggering inhibitory process is a better predictor of impulsivity than SSRT. Acta Psychologica, 192, 104-117, https://psyarxiv.com/vg5rd/
- Heathcote, A., Holloway, E., & Sauer, J.D. (2019). Confidence and varieties of bias. Journal of Mathematical Psychology, 90, 31-46. doi: 10.1016/j.jmp.2018.10.002
Book Chapters:
-Strickland, L., Loft, S., & Heathcote, A. (2019). Evidence Accumulation Modeling of Event-Based Prospective Memory. In J. Rummel & M.A. McDaniel (Eds), Current Issues in Memory: Prospective Memory (pp. 78-94). London, United Kingdom: Taylor & Francis.
Technical Reports:
- French, B., Duenser, A., Heathcote, A. (2018). Trust in Automation – A Literature Review. CSIRO Report EP184082. CSIRO, Australia.
For any questions related to this site please email:
contact@tascl.org