The eyes grasp, the hands see: Metric category knowledge transfers between vision and touch
- Authors
- Wallraven, Christian; Buelthoff, Heinrich H.; Waterkamp, Steffen; van Dam, Loes; Gaiert, Nina
- Issue Date
- 8월-2014
- Publisher
- SPRINGER
- Keywords
- Shape; Object categorization; Vision; Haptics; Categorization; Multisensory representations
- Citation
- PSYCHONOMIC BULLETIN & REVIEW, v.21, no.4, pp.976 - 985
- Indexed
- SSCI
SCOPUS
- Journal Title
- PSYCHONOMIC BULLETIN & REVIEW
- Volume
- 21
- Number
- 4
- Start Page
- 976
- End Page
- 985
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/97751
- DOI
- 10.3758/s13423-013-0563-4
- ISSN
- 1069-9384
- Abstract
- Categorization of seen objects is often determined by the shapes of objects. However, shape is not exclusive to the visual modality: The haptic system also is expert at identifying shapes. Hence, an important question for understanding shape processing is whether humans store separate modality-dependent shape representations, or whether information is integrated into one multisensory representation. To answer this question, we created a metric space of computer-generated novel objects varying in shape. These objects were then printed using a 3-D printer, to generate tangible stimuli. In a categorization experiment, participants first explored the objects visually and haptically. We found that both modalities led to highly similar categorization behavior. Next, participants were trained either visually or haptically on shape categories within the metric space. As expected, visual training increased visual performance, and haptic training increased haptic performance. Importantly, however, we found that visual training also improved haptic performance, and vice versa. Two additional experiments showed that the location of the categorical boundary in the metric space also transferred across modalities, as did heightened discriminability of objects adjacent to the boundary. This observed transfer of metric category knowledge across modalities indicates that visual and haptic forms of shape information are integrated into a shared multisensory representation.
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Collections - Graduate School > Department of Artificial Intelligence > 1. Journal Articles
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