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Two-Dimensional Symmetric Form Discrimination: Fast Learning, but Not That Fast
Ivans Chou and Lucia M. Vaina
Vol. 104, No. 1 (Jul., 1995), pp. 33-41
Published by: Springer
Stable URL: http://www.jstor.org/stable/20117414
Page Count: 9
You can always find the topics here!Topics: Symmetry, Discrimination learning, Sensory discrimination, Learning rate, Perceptual learning, Learning, Visual learning, Visual fields, Transfer of training, Visual perception
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Several authors have characterized a striking phenomenon of perceptual learning in visual discrimination tasks. This learning process is selective for the stimulus characteristics and location in the visual field. Since the human visual system exploits symmetry for object recognition we were interested in exploring how it learns to use preattentive symmetry cues for discriminating simple, meaningless, forms. In this study, similar to previous studies of perceptual learning, we asked whether the effects of practice acquired in the discrimination of pairs of shape with a specific orientation of the symmetry axis would transfer to the discrimination of shapes with different orientation of symmetry axis, or to shapes presented in different areas of the visual field. We found that there was no learning transfer between forms with very different axes of symmetry (90° apart). Interestingly, however, we found a transfer of learning effect to horizontally oriented symmetry axis from a condition with an axis of symmetry differing by 45°. Also it appears that some subjects took a longer time to learn than the typical "fast learning" paradigm would predict. Data showed that when observers practice discrimination of meaningless symmetric forms, consistent improvement in the performance occurs. This improvement is lasting over days, and it tends to be specific for the area of the visual field trained. We will discuss results from some of the observers whose learning was not "fast", but who actually improved with more practice and with large time intervals (1 day) between training sessions.
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