-
3For deep networks, the whole equals the sum of the partsBehavioral and Brain Sciences 46. 2023.Deep convolutional networks exceed humans in sensitivity to local image properties, but unlike biological vision systems, do not discover and encode abstract relations that capture important properties of objects and events in the world. Coupling network architectures with additional machinery for encoding abstract relations will make deep networks better models of human abilities and more versatile and capable artificial devices.
-
150Perceptual learning and the technology of expertisePragmatics and Cognition 16 (2): 356-405. 2008.Learning in educational settings most often emphasizes declarative and procedural knowledge. Studies of expertise, however, point to other, equally important components of learning, especially improvements produced by experience in the extraction of information: Perceptual learning. Here we describe research that combines principles of perceptual learning with computer technology to address persistent difficulties in mathematics learning. We report three experiments in which we developed and tes…Read more
-
142Perception of partly occluded objects in infancy* 1Cognitive Psychology 15 (4). 1983.Four-month-old infants sometimes can perceive the unity of a partly hidden object. In each of a series of experiments, infants were habituated to one object whose top and bottom were visible but whose center was occluded by a nearer object. They were then tested with a fully visible continuous object and with two fully visible object pieces with a gap where the occluder had been. Pattems of dishabituation suggested that infants perceive the boundaries of a partly hidden object by analyzing the m…Read more
-
16Interpolation processes in object perception: Reply to Anderson (2007)Psychological Review 114 (2): 488-502. 2007.
-
7Perceptual learningIn J. Wixted & H. Pashler (eds.), Stevens' Handbook of Experimental Psychology, Wiley. 2002.
-
79Finding the Pope in the pizza: Abstract invariants and cognitive constraints on perceptual learningBehavioral and Brain Sciences 21 (1): 30-30. 1998.Schyns, Goldstone & Thibaut argue that categorization experience results in the learning of new perceptual features that are not derivable from the learner's existing feature set. We explore the meaning and implications of this “nonderivability” claim and relate it to the question of whether perceptual invariants are learnable, and if so, what might be entailed in learning them.
-
Learning, motivation, and emotionIn J. Wixted & H. Pashler (eds.), Stevens' Handbook of Experimental Psychology, Wiley. pp. 267. 2002.
-
123Perceptual Learning Modules in Mathematics: Enhancing Students' Pattern Recognition, Structure Extraction, and FluencyTopics in Cognitive Science 2 (2): 285-305. 2010.
-
12From Flashes to Edges to Objects: Recovery of Local Edge Fragments Initiates Spatiotemporal Boundary FormationFrontiers in Psychology 7. 2016.
-
Discontinuity theory and the perception of illusory figuresBulletin of the Psychonomic Society 26 (6): 516-516. 1988.
-
Interpolation processes in visual object perception-evidence for a discontinuity theoryBulletin of the Psychonomic Society 25 (5): 334-334. 1987.
-
12Postscript: Identity and constraints in models of object formationPsychological Review 114 (2): 502-508. 2007.
-
27Non-rigid illusory contours and global shape transformations defined by spatiotemporal boundary formationFrontiers in Human Neuroscience 8. 2014.