Computational and Clinical Approaches to Pattern Recognition and Concept Formation

The ninth volume in this highly acclaimed series discusses the computational and clinical approaches to pattern recognition and concept formation regarding: visual and spatial processing models; computational models, templates and hierarchical models. An ideal reference for students and professionals in experimental psychology and behavioral analysis.

Contents: Part I:Visual and Spatial Processing Models. E. Bisiach, S. Meregalli, A. Berti, Mechanisms of Production-Control and Belief-Fixation in Human Visuo-Spatial Processing Clinical Evidence from Hemispatial Neglect. G.A. Carpenter, S. Grossberg, Neural Dynamics of Category Learning and Recognition: Structural Invariants, Reinforcements, and Evoked Potentials. M.A. Cohen, S. Grossberg, Unitized Recognition Codes for Parts and Wholes: The Unique Cue in Configural Discriminations. A. Trehub, A Confusion Matrix for Hand-Printed Alphabetic Characters: Testing a Neuronal Model. Part II:Computational Models. J.A. Feldman, Massively Parallel Computational Models. Part III:Template and Hierarchical Models. E.G. Heinemann, S. Chase, A Quantitative Model for Pattern Recognition. M.L. Commons, P.W. Hallinan, W. Fong, K.G. McCarthy, Intelligent Pattern Recognition: Hierarchical Organization of Concepts.