September 2015
Volume 15, Issue 12
Free
Vision Sciences Society Annual Meeting Abstract  |   September 2015
How drawing shapes object representations
Author Affiliations
  • Judith Fan
    Department of Psychology, Princeton University
  • Daniel Yamins
    McGovern Institute for Brain Research, Massachusetts Institute of Technology
  • Nicholas Turk-Browne
    Department of Psychology, Princeton University
Journal of Vision September 2015, Vol.15, 44. doi:10.1167/15.12.44
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      Judith Fan, Daniel Yamins, Nicholas Turk-Browne; How drawing shapes object representations. Journal of Vision 2015;15(12):44. doi: 10.1167/15.12.44.

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

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Abstract

Drawing is a powerful tool for communicating ideas visually — a few well-placed strokes can convey the identity of a face, object, or scene. Here we examine how people learn to draw real-world objects in order to understand the more general consequences of visual production on the representation of objects in the mind. As a case study, we ask: How does practice drawing particular objects affect the way that those and other objects are represented? Participants played an online game in which they were prompted on each trial with an image (N=314) or word (N=276) that referred to a target object for them to draw. We used a high-performing, deep convolutional neural network model of ventral visual cortex to guess the identity of the drawn object in real time, providing participants immediate feedback about the quality of their drawing. Objects belonged to one of eight categories, each containing eight items. Each participant was randomly assigned two of these categories. During training, participants drew four randomly selected objects in one category (Trained) multiple times. Before and after training, participants drew the other four objects in that category (Near), as well as the objects in the second category (Far), once each. We found that drawings of Trained items were better recognized by the model after training, and that this improvement reflected decreased confusions with other items in the same category. By contrast, recognition of Near items worsened after training, which reflected increased within-category confusion. Recognition of Far items did not change significantly. These results show that visual production can reshape the representational space for objects: by differentiating trained objects and merging other objects nearby in the space. More broadly, these findings suggest that the outward expression of visual concepts can itself bring about changes to their internal representation.

Meeting abstract presented at VSS 2015

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