References

Balakrishnan, J. D. (1998). Some more sensitive measures of sensitivity and response bias. Psychological Methods, 3(1), 68–90. https://doi.org/10.1037/1082-989X.3.1.68

Banks, W. P. (1970). Signal detection theory and human memory. Psychological Bulletin, 74(2), 81–99. https://doi.org/10.1037/h0029531

Berry, C. J., Shanks, D. R., & Henson, R. N. A. (2008). A unitary signal-detection model of implicit and explicit memory. Trends in Cognitive Sciences, 12(10), 367–373. https://doi.org/10.1016/J.TICS.2008.06.005

Britten, K. H., Shadlen, M. N., Newsome, W. T., & Movshon, J. A. (1992). The analysis of visual motion: a comparison of neuronal and psychophysical performance. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 12(12), 4745–4765. https://doi.org/10.1523/JNEUROSCI.12-12-04745.1992

Creelman, C. D. (2015). Signal detection theory, History of. In International encyclopedia of the social & behavioral sciences (Second Edition, pp. 952–956). Elsevier Inc. https://doi.org/10.1016/B978-0-08-097086-8.43091-6

DeCarlo, L. T. (2002). Signal detection theory with finite mixture distributions: Theoretical developments with applications to recognition memory. Psychological Review, 109(4), 710–721. https://doi.org/10.1037/0033-295X.109.4.710

Glanzer, M., Kim, K., Hilford, A., & Adams, J. K. (1999). Slope of the receiver-operating characteristic in recognition memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25(2), 500–513. https://doi.org/10.1037/0278-7393.25.2.500

Gold, J. I., & Shadlen, M. N. (2002). Banburismus and the brain. Neuron, 36(2), 299–308. https://doi.org/10.1016/S0896-6273(02)00971-6

Gold, J. I., & Shadlen, M. N. (2007). The neural basis of decision making. Annual Review of Neuroscience, 30, 535–574. https://doi.org/10.1146/annurev.neuro.29.051605.113038

Green, D. M., & Swets, J. A. (1966). Signal detection theory and psychophysics. Wiley.

Ingham, J. G. (1970). Individual differences in signal detection. Acta Psychologica, 34(C), 39–50. https://doi.org/10.1016/0001-6918(70)90003-X

Krantz, D. H. (1969). Threshold theories of signal detection. Psychological Review, 76(3), 308–324. https://doi.org/10.1037/h0027238

Lusted, L. B. (1971). Signal detectability and medical decision-making. Science (New York, N.Y.), 171(3977), 1217–1219. https://doi.org/10.1126/SCIENCE.171.3977.1217

Lynn, S. K., & Barrett, L. F. (2014). “Utilizing” signal detection theory. Psychological Science, 25(9), 1663–1673. https://doi.org/10.1177/0956797614541991

Macmillan, N. A., & Creelman, C. D. (1990). Response bias: Characteristics of detection theory, threshold theory, and “nonparametric” indexes. Psychological Bulletin, 107(3), 401–413. https://doi.org/10.1037/0033-2909.107.3.401

Marcum, J. I. (1947). A statistical theory of target detection by pulsed radar (Research Memorandum RM-754-PR). RAND Corporation. https://www.rand.org/pubs/research_memoranda/RM754.html

Pastore, R. E., Crawley, E. J., Berens, M. S., & Skelly, M. A. (2003). “Nonparametric”A’ and other modern misconceptions about signal detection theory. Psychonomic Bulletin & Review, 10(3), 556–569. https://doi.org/10.3758/BF03196517

Peterson, W., Birdsall, T., & Fox, W. (1954). The theory of signal detectability. Transactions of the IRE Professional Group on Information Theory, 4(4), 171–212. https://doi.org/10.1109/TIT.1954.1057460

Pilly, P. K., & Seitz, A. R. (2009). What a difference a parameter makes: A psychophysical comparison of random dot motion algorithms. Vision Research, 49(13), 1599–1612. https://doi.org/10.1016/J.VISRES.2009.03.019

Ratcliff, R., & McKoon, G. (2008). The diffusion decision model: Theory and data for two-choice decision tasks. Neural Computation, 20(4), 873–922. https://doi.org/10.1162/neco.2008.12-06-420

Ratcliff, R., Sheu, C., & Gronlund, S. D. (1992). Testing global memory models using ROC curves. Psychological Review, 99(3), 518–535. https://doi.org/10.1037/0033-295X.99.3.518

Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016). Diffusion decision model: Current issues and history. Trends in Cognitive Sciences, 20(4), 260–281. https://doi.org/10.1016/j.tics.2016.01.007

Stanislaw, H., & Todorov, N. (1999). Calculation of signal detection theory measures. Behavior Research Methods, Instruments, & Computers, 31(1), 137–149. https://doi.org/10.3758/BF03207704

Swets, J. A. (1996). Signal detection theory and ROC analysis in psychology and diagnostics. Routledge. https://doi.org/10.4324/9781315806167

Tanner, W. P., & Swets, J. A. (1954). A decision-making theory of visual detection. Psychological Review, 61(6), 401–409. https://doi.org/10.1037/h0058700

Verde, M. F., Macmillan, N. A., & Rotello, C. M. (2006). Measures of sensitivity based on a single hit rate and false alarm rate: The accuracy, precision, and robustness of′,Az, andA’. Perception & Psychophysics, 68(4), 643–654. https://doi.org/10.3758/BF03208765

Wagenmakers, E.-J., Maas, H. L. J., & Grasman, R. P. P. P. (2007). An EZ-diffusion model for response time and accuracy. Psychonomic Bulletin & Review, 14(1), 3–22. https://doi.org/10.3758/BF03194023

Weidemann, C. T., & Kahana, M. J. (2016). Assessing recognition memory using confidence ratings and response times. Royal Society Open Science, 3(4), 150670. https://doi.org/10.1098/rsos.150670

Wixted, J. T., & Mickes, L. (2015). Evaluating eyewitness identification procedures: ROC analysis and its misconceptions. Journal of Applied Research in Memory and Cognition, 4(4), 318–323. https://doi.org/10.1016/j.jarmac.2015.08.009

Wixted, J. T., Mickes, L., Wetmore, S. A., Gronlund, S. D., & Neuschatz, J. S. (2017). ROC analysis in theory and practice. Journal of Applied Research in Memory and Cognition, 6(3), 343–351. https://doi.org/10.1016/j.jarmac.2016.12.002

Yates, J. F., & Tschirhart, M. D. (2006). Decision-making expertise. In K. A. Ericsson, N. Charness, P. J. Feltovich, & R. R. Hoffman (Eds.), The Cambridge handbook of expertise and expert performance (pp. 421–438). Cambridge University Press.

Zhang, J., Riehle, A., Requin, J., & Kornblum, S. (1997). Dynamics of single neuron activity in monkey primary motor cortex related to sensorimotor transformation. Journal of Neuroscience, 17(6), 2227–2246. https://doi.org/10.1523/JNEUROSCI.17-06-02227.1997