The mental representations of perceptual and cognitive stimuli vary on many dimensions. In addition, because of quantal fluctuations in the stimulus, spontaneous neural activity, and fluctuations in arousal and attentiveness, mental events are characterized by an inherent variability. During the last several years, a number of models and theories have been developed that explicitly assume the appropriate mental representation is both multidimensional and probabilistic. This new approach has the potential to revolutionize the study of perception and cognition in the same way that signal…mehr
The mental representations of perceptual and cognitive stimuli vary on many dimensions. In addition, because of quantal fluctuations in the stimulus, spontaneous neural activity, and fluctuations in arousal and attentiveness, mental events are characterized by an inherent variability. During the last several years, a number of models and theories have been developed that explicitly assume the appropriate mental representation is both multidimensional and probabilistic. This new approach has the potential to revolutionize the study of perception and cognition in the same way that signal detection theory revolutionized the study of psychophysics. This unique volume is the first to critically survey this important new area of research.First Published in 1992. Routledge is an imprint of Taylor & Francis, an informa company.
Contents: F.G. Ashby Multivariate Probability Distributions. Part I: Similarity Preference and Choice.J.L. Zinnes D.B. MacKay A Probabilistic Multidimensional Scaling Approach: Properties and Procedures. G. De Soete J.D. Carroll Probabilistic Multidimensional Models of Pairwise Choice Data. U. Bo"ckenholt Multivariate Models of Preference and Choice. D.M. Ennis K. Mullen A General Probabilistic Model for Triad Discrimination Preferential Choice and Two-Alternative Identification. N.A. Perrin Uniting Identification Similarity and Preference: General Recognition Theory. Part II:Interactions Between Perceptual Dimensions. W.T. Maddox Perceptual and Decisional Separability. H. Kadlec J.T. Townsend Signal Detection Analyses of Dimensional Interactions. T.D. Wickens L.A. Olzak Three Views of Association in Concurrent Detection Ratings. Part III:Detection Identification and Categorization.J.P. Thomas L.A. Olzak Simultaneous Detection and Identification. D.M. Ennis Modeling Similarity and Identification When There Are Momentary Fluctuations in Psychological Magnitudes. A.A.J. Marley Developing and Characterizing Multidimensional Thurstone and Luce Models for Identification and Preference. Y. Takane T. Shibayama Structures in Stimulus Identification Data. R.M. Nosofsky Exemplar-Based Approach to Relating Categorization Identification and Recognition. M.M. Cohen D.W. Massaro On the Similarity of Categorization Models. F.G. Ashby Multidimensional Models of Categorization.
Contents: F.G. Ashby Multivariate Probability Distributions. Part I: Similarity Preference and Choice.J.L. Zinnes D.B. MacKay A Probabilistic Multidimensional Scaling Approach: Properties and Procedures. G. De Soete J.D. Carroll Probabilistic Multidimensional Models of Pairwise Choice Data. U. Bo"ckenholt Multivariate Models of Preference and Choice. D.M. Ennis K. Mullen A General Probabilistic Model for Triad Discrimination Preferential Choice and Two-Alternative Identification. N.A. Perrin Uniting Identification Similarity and Preference: General Recognition Theory. Part II:Interactions Between Perceptual Dimensions. W.T. Maddox Perceptual and Decisional Separability. H. Kadlec J.T. Townsend Signal Detection Analyses of Dimensional Interactions. T.D. Wickens L.A. Olzak Three Views of Association in Concurrent Detection Ratings. Part III:Detection Identification and Categorization.J.P. Thomas L.A. Olzak Simultaneous Detection and Identification. D.M. Ennis Modeling Similarity and Identification When There Are Momentary Fluctuations in Psychological Magnitudes. A.A.J. Marley Developing and Characterizing Multidimensional Thurstone and Luce Models for Identification and Preference. Y. Takane T. Shibayama Structures in Stimulus Identification Data. R.M. Nosofsky Exemplar-Based Approach to Relating Categorization Identification and Recognition. M.M. Cohen D.W. Massaro On the Similarity of Categorization Models. F.G. Ashby Multidimensional Models of Categorization.
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