Socrates-Erasmus IP on 'Mathematical and Computational Models of Perception and Mental Chronometry', 15-25 April, Loaningdale Centre, Bigggar, Scotland-UK [pdf]


List of Participants [pdf]


Reading List [pdf]

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Background Reading on Bayesian Models in Perception (J Hillis)

Hillis, J.M., Ernst, M.O., Banks, M.S., & Landy, M.S. (2002). Combining sensory information: mandatory fusion within, but not between, senses. Science, 298, 1627-1630. [pdf]

Kersten, D., Mamassian, P., & Yuille, A. (2004). Object perception as Bayesian inference. Annu Rev Psychol, 55, 271-304. [pdf]

Knill, D. C., & Pouget, A. (2004). The Bayesian brain: the role of uncertainty in neural coding and computation. Trends Neurosci, 27(12), 712-719. [pdf]

Knill, D.C. & Richards. W. (1996) Perception as Bayesian Inference, Cambridge University Press.

Schrater, P., & Kersten, D. (2001). Vision, psychophysics and Bayes. In Rao, Olshausen & Lewicki (Eds.) Probabilistic models of the brain, MIT Press. [pdf]

Student Presentation Options for Bayesian Models in Perception (J Hillis)

Brainard, D. H., & Freeman, W. T. (1997). Bayesian color constancy. Journal of the Optical Society of America A, 14(7), 1393-1411. [pdf]

Geisler, W. S., Perry, J. S., Super, B. J., & Gallogly, D. P. (2001). Edge co-occurrence in natural images predicts contour grouping performance. Vision Research, 41(6), 711-724. [pdf]

Knill, D. C. (2003). Mixture models and the probabilistic structure of depth cues. Vision Research, 43(7), 831-854. [pdf]

Mamassian, P., & Landy, M. S. (1998). Observer biases in the 3D interpretation of line drawings. Vision Res, 38(18), 2817-2832. [pdf]

Mamassian, P., & Landy, M. S. (2001). Interaction of visual prior constraints.Vision Res, 41(20), 2653-2668. [pdf]

Najemnik, J., & Geisler, W. S. (2005). Optimal eye movement strategies in visual search. Nature, 434(7031), 387-391. [pdf]

Schrater, P., & Kersten, D. (2000). How optimal depth cue integration depends on the task. International Journal of Computer Vision, 40(1), 72-91. [pdf]

Simoncelli, E. P., & Adelson, E. H. (1996). Noise removal via Bayesian wavelet coring. Proceedings of 3rd IEEE International Conference on Image Processing, I, 379-382. [pdf]

Weiss, Y., Simoncelli, E. P., & Adelson, E. H. (2002). Motion illusions as optimal percepts. Nat Neurosci, 5(6), 598-604. [pdf]


Background Reading on Mental Chronometry (R Ulrich)

(M=Mathematical Modelling, S=Modelling, and Simulation E=Experiments)

Ulrich, R., & Stapf, K.H. (1984). A double-response paradigm to study stimulus intensity effects upon the motor system in simple reaction time experiments. Perception & Psychophysics, 36, 545-558. (ME) [pdf]

Ulrich, R., & Dietz, K. (1985). The short-term storage as a buffer memory between long-term storage and the motor system: A simultaneous-processing model. Journal of Mathematical Psychology, 29, 243-270. (ME) [pdf]

Ulrich, R., & Giray, M. (1986). Separate-activation models with variable base times: Testability and checking of cross-channel dependency. Perception & Psychophysics, 39, 248-254. (MES) [pdf]

Ulrich, R. (1987). Threshold models of temporal-order judgements evaluated by a ternary response-category approach. Perception & Psychophysics, 42, 224-239. (MES) [pdf]

Rammsayer, T., & Ulrich, R. (2001). Counting models of temporal discrimination in humans. Psychonomic Bulletin & Review, 8, 270-277. (ME) [pdf]

Miller, J., & Ulrich, R. (2003). Simple reaction time and statistical facilitation: A parallel grains model. Cognitive Psychology, 46, 101-151. (MS) [pdf]

Student Presentation Options for Mental Chronometry (R Ulrich)

Ulrich, R., & Giray, M. (1989). Measuring reaction times: How accurate must a clock be? Good news for bad clocks! British Journal of Mathematical and Statistical Psychology, 42, 1-12. (M) [pdf]

Ulrich, R., & Wing, A., (1991). A recruitment theory of force-time relations in the production of brief force pulses: The Parallel Force Unit Model. Psychological Review, 98, 268-294. (MES) [pdf]

Ulrich, R., & Miller, J. (1993). Information processing mechanisms generating lognormally distributed reaction times. Mathematical Psychology, 37, 513-525. (MS) [pdf]

Ulrich, R., & Miller, J. (1994). Effects of truncation on reaction time analysis. Journal of Experimental Psychology: General, 123, 34-80. (M) [pdf]

Ulrich, R., & Miller, J. (1997). Tests of race models for reaction time in experiments with asynchronous redundant signals. Journal of Mathematical Psychology, 41, 367-381. (M) [pdf]

Ulrich R. & Miller, J. (2004). Threshold estimation in two-alternative (2AFC) tasks: The Spearman-Kaerber method. Perception & Psychophysics, 66, 517-533. (MS) [pdf]

Rinkenauer, G., Osman, A., Ulrich, R., Mueller-Gethmann, H., & Mattes, S. (2004). On the locus of speed-accuracy trade-off in reaction time: Inferences from the lateralized readiness potential. Journal of Experimental Psychology: General, 133, 261-282. (EM) [pdf]

Miller, J., Ulrich, R. & Rolke, B. (in press). Parallel and serial processing in dual-tasking: An optimization account. Cognitive Psychology. (ME) [pdf]

Bausenhart K. M., Rolke, B., Hackley, S. A., & Ulrich, R. (in press). The locus of temporal preparation effects: Evidence from the psychological refractory period paradigm. Psychonomic Bullentin & Review (E) [pdf]

Ulrich, R., Fernadez, S., Jentzsch, I., Rolke, B., Schroeter, H. & Leuthold, H. (in press). The psychological refractory period: Is response execution part of the processing bottleneck? Psychological Science. (E) [pdf]

Ulrich, R., Nitschke, J., & Rammsayer,T. (in press).  Crossmodal temporal discrimination: Assessing the predictions of a general pacemaker-counter model. Perception & Psychophysics (ME) [pdf]

Background Reading on Psychophysical Models (F Wichmann)

Wichmann, F.A., & Hill, J.N. (2001a). The psychometric function: I Fitting, sampling, and goodness of fit. Perception & Psychophysics, 63(8). 1293-1313. [pdf]

Wichmann, F.A., & Hill, J.N. (2001b). The psychometric function: II Bootstrap-based confidence intervals and sampling. Perception & Psychophysics, 63(8). 1314-1329. [pdf]

Kuss, M., Jaekel, F., & Wichmann, F.A. (2005). Bayesian inference for psychometric functions. Journal of Vision, 5, 478-492. [pdf]

Wichmann, F.A., Graf, A.B.A., Simoncelli, E.P., Buelthoff, H.H., & Schoelkopf, B. (2005). Machine learning applied to perception: decision-images for gender classification. In: Advances in neural information processing systems, Vol. 17 (Eds. L.K. Saul, Y.Weiss, & L. Bottou), pp.1489-1496. [pdf]

Student Presentation Options for Psychophysical Models (F Wichmann)

H. Levitt (1971). Transformed Up-Down Methods in Psychoacoustics.  Journal of the Acoustical Society of America, 49, 467-477. [pdf]

Treutwein, B. (1995) Adaptive psychophysical procedures. Vision Research, 35, 2503-2522. [pdf]

King-Smith, P.E., Grisby, S.S., Vingrys, A.J., Benes, S.C., & Supowit, A.  (1994). Efficient and unbiased modification of the QUEST threshold method: Theory, simulations, experimental evaluation and practical implementation. Vision Research, 34(7), 885-912. [pdf]

Watson, A.B., & Fitzhugh, A. (1990). The method of constant stimuli is inefficient. Perception & Psychophysics, 47(1), 87-91. [pdf]

Background Reading on Bistable Perception (R Goutcher)

Blake, R. & Logothetis, N.K. (2002). Visual competition. Nature Reviews: Neuroscience, 3, 1-11.[pdf]

Leopold, D.A. & Logothetis, N.K. (1999). Multistable phenomena: Changing views in perception. Trends in Cognitive Sciences, 3, 254-264.[pdf]

Mamassian, P., & Goutcher, R. (2005). Temporal dynamics in bistable perception. Journal of Vision, 5(4), 361-375.[pdf]

Student Presentation Options for “Bistable Perception” (R Goutcher)

Blake, R. (1989). A neural theory of binocular rivalry. Psychological Review, 96, 145-167.[pdf]

Brascamp, J. W., van Ee, R., Pestman, W. R., & van den Berg, A. V. (2005). Distributions of alternation rates in various forms of bistable perception. Journal of Vision, 5(4), 287-298.[pdf]

Haynes, J. –D. & Rees, G. (2005). Predicting the orientation of invisible stimuli from activity in human primary visual cortex. Nature Neuroscience, 8, 686-691.[pdf]

Hupé, J.M. & Rubin, N. (2003). The dynamics of bi-stable alternation in ambiguous motion displays: a fresh look at plaids. Vision Research, 43, 531-548.[pdf]

Leopold, D.A., Wilke, M., Maier, A. & Logothetis, N.K. (2002). Stable perception of visually ambiguous patterns. Nature Neuroscience, 5, 605-609.[pdf]

Logothetis, N.K. (1998). Single units and conscious vision. Philosophical Transactions of the Royal Society of London, Series B, 353, 1801-1818.[pdf]

Logothetis, N.K., Leopold, D.A. & Sheinberg, D.L. (1996). What is rivalling during binocular rivalry? Nature, 380, 621 – 624.[pdf]