May 2008
Volume 8, Issue 6
Free
Vision Sciences Society Annual Meeting Abstract  |   May 2008
Predicting perceptual expertise from semantic knowledge: An indexed car test for prosopagnosic patients
Author Affiliations
  • Hashim Hanif
    Medical College, Aga Khan University
  • Rana Khalil
    Medical College, Aga Khan University
  • George Malcolm
    Human Vision and Eye Movement Laboratory, Departments of Neurology, Ophthalmology and Visual Science, University of British Columbia
  • Jason Barton
    Human Vision and Eye Movement Laboratory, Departments of Neurology, Ophthalmology and Visual Science, University of British Columbia
Journal of Vision May 2008, Vol.8, 185. doi:https://doi.org/10.1167/8.6.185
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      Hashim Hanif, Rana Khalil, George Malcolm, Jason Barton; Predicting perceptual expertise from semantic knowledge: An indexed car test for prosopagnosic patients. Journal of Vision 2008;8(6):185. https://doi.org/10.1167/8.6.185.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Studies of whether the prosopagnosic recognition impairment extends to other objects are confounded by variable expertise of people for other objects. Ideally, performance for non-face object recognition by these patients should be adjusted for premorbid expertise. We explored whether an index of semantic knowledge about cars could predict the performance of healthy subjects in a test of visual recognition of cars. 23 subjects perform three items involving all European, Asian and American cars made from 1950 to the present. First, they used Likert scales to rate their own knowledge of cars from each decade. Second, we administered a semantic questionnaire, asking them to provide the make (manufacturer's name) for all models made in this period. Third, we administered a perceptual test that showed the images of 150 cars, for which they were required to provide decade, model and make if possible. Half of the subjects performed the perceptual test before the semantic, and half the reverse. Semantic knowledge correlated well with perceptual recognition of make (r=.85) and model (r=.90), but less so with recognition of decade of make (r = .30). A combined perceptual index of Make + 4*(Model) + 0.2*(Decade) yielded the optimum correlation of perceptual knowledge with semantic knowledge (r = .93). Self-ratings correlated moderately with semantic knowledge (r=.57), and with perceptual recognition of make (r=.59), model (r=.54), and decade of make (r = .33). A combined perceptual index of Make + 2.1*(Model) + 0.5*(Decade) yielded the optimum correlation of perceptual knowledge with self-rating (r = .61). We conclude that semantic car knowledge but not self-rating is a reasonably accurate predictor of perceptual recognition of cars by make and model. A semantic index may be useful for adjusting perceptual recognition scores for premorbid expertise when studying patients with face or object recognition deficits.

Hanif, H. Khalil, R. Malcolm, G. Barton, J. (2008). Predicting perceptual expertise from semantic knowledge: An indexed car test for prosopagnosic patients [Abstract]. Journal of Vision, 8(6):185, 185a, http://journalofvision.org/8/6/185/, doi:10.1167/8.6.185. [CrossRef]
Footnotes
 This work was supported by operating grants from the CIHR (MOP-77615) and NIMH (1R01 MH069898). JJSB was supported by a Canada Research Chair and a Senior Scholarship from the Michael Smith Foundation for Health Research.
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