Perceptual learning in object recognition: object specificity and size invariance

Abstract

A series of four experiments measured the transfer of perceptual learning in object recognition. Subjects viewed backward-masked, gray-scale images of common objects and practiced an object naming task for multiple days. In Experiment 1, recognition thresholds decreased on average by over 20% over 5 days of training but increased reliably following the transfer to a new set of objects. This suggests that the learning was specific to the practiced objects. Experiment 2 ruled out familiarity with strategies specific to the experimental context, such as stimulus discrimination, as the source of the improvement. Experiments 3 and 4 found that learning transferred across changes in image size. Learning could not be accounted for solely by an improvement in general perceptual abilities, nor by learning of the specific experimental context. Our results indicate that a large amount of learning took place in object-specific mechanisms that are insensitive to image size.

Repetition priming and the haptic recognition of familiar and unfamiliar objects

“…To examine the generality of this account, it is important that we examine how the haptic system attains object constancy across other transformations. For example, the visual system has consistently demonstrated size constancy in object recognition (see, e.g., Biederman & Cooper, 1992;Furmanski & Engel, 2000). If the haptic system processes size in the same way as the visual system, then it too may demonstrate size invariance in object recognition.…”

Perceptual learning and representational learning in humans and animals

“…In perceptual learning paradigms, the subject is presented with a well-defined task explained verbally by the experimenter-orientation discrimination, for example (Fiorentini & Berardi, 1980;Furmanski & Engel, 2000;Petrov, Dosher, & Lu, 2006), texture discrimination (Ahissar & Hochstein, 1997;Karni & Sagi, 1991), motion direction discrimination (Matthews, Liu, Geesaman, & Qian, 1999), or a hyperacuity test (Poggio, Fahle, & Edelman, 1992). After repetitive training (typically including feedback), the subject's performance improves as quantified by threshold or reaction time measures.…”

“…After repetitive training (typically including feedback), the subject's performance improves as quantified by threshold or reaction time measures. This experimental paradigm has been explored extensively in both the psychophysical (Dosher & Lu, 1998;Furmanski & Engel, 2000;Gold, Bennett, & Sekuler, 1999) and the neurophysiological domains (Gilbert, Sigman, & Crist, neurophysiological domains (Gilbert,Sigman,& Crist,141 © 2009 The Psychonomic Society, Inc.…”

Physiological Correlates of Perceptual Learning in Monkey V1 and V2

“…In the classification model (D), the observed response will be associated with an orientation less than 45°(gray region) since no orientation in the black region produces such a response. 1997, 2000Ellison and Walsh 1998;Fiorentini 1989;Sagi 1991, 1993;Schoups and Orban 1996;Sigman and Gilbert 2000;Rettenbach 1995, 2000), object identification (Furmanski and Engel 2000), and discrimination of differences in direction (Ball and Sekuler 1987;Zohary et al 1994), orientation (Matthews et al 1999(Matthews et al , 2001Mayer 1983;Schoups et al 1995b;Orban 1985, 1994a), spatial frequency (Fine and Jacobs 2000), and spatial phase (Berardi and Fiorentini 1987;Fiorentini andBerardi 1980, 1981). The range of techniques, time courses, and measures of these learning effects makes comparison difficult (I.…”