September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
Curved features are critical for animate/inanimate categorization in macaques
Author Affiliations
  • Marissa Yetter
    Laboratory of Brain and Cognition, NIMH, NIH
  • Mark Eldridge
    Laboratory of Neuropsychology, NIMH, NIH
  • Grace Mammarella
    Laboratory of Neuropsychology, NIMH, NIH
  • Leslie Ungerleider
    Laboratory of Brain and Cognition, NIMH, NIH
  • Xiaomin Yue
    Laboratory of Brain and Cognition, NIMH, NIH
Journal of Vision September 2018, Vol.18, 555. doi:10.1167/18.10.555
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Marissa Yetter, Mark Eldridge, Grace Mammarella, Leslie Ungerleider, Xiaomin Yue; Curved features are critical for animate/inanimate categorization in macaques. Journal of Vision 2018;18(10):555. doi: 10.1167/18.10.555.

      Download citation file:


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

      ×
  • Supplements
Abstract

In an earlier fMRI study, we showed that multivoxel activity patterns, measured with support vector machine classification, encoded animate vs. inanimate categories in the macaque inferior temporal cortex. However, the classification accuracy was reduced to chance after removing the variance in the fMRI activity patterns that was explained by the curved and rectilinear image features, as quantified using curved and rectilinear Gabor filters. These results indicate that categorization in the macaque inferior temporal cortex might not stem from acquired semantic knowledge of the characteristics that distinguish animate from inanimate object categories, but rather from the unique image-based features. The current experiment was designed to directly examine those two possibilities using behavioral tests. First, one rhesus macaque was trained to categorize images of animate and inanimate objects. Then, the same monkey was tested on a large number of trial-unique images of animate and inanimate objects across five days to assess whether this training generalized to unfamiliar objects. We found that the animal's classification accuracy for these unfamiliar objects averaged 84.55%, supporting our fMRI conclusion that animate/inanimate categorization does not stem from acquired semantic knowledge of animate vs. inanimate categories. We also tested whether image features that differ substantially between the two object categories, such as curvilinear and rectilinear information, contribute to the monkey's classification accuracy. The same animal was tested across five days on sets of synthetic animate and inanimate images created using an algorithm that significantly distorted the global shape of the original images, while maintaining the original images' intermediate features (e.g. curvilinear and rectilinear information). We found that the animal's classification accuracy was significantly above chance (63.57%), suggesting that unique image-based features, such as curvilinear features, distinguish animate from inanimate objects and give rise to the formation of animate/inanimate categorization in macaques to some extent.

Meeting abstract presented at VSS 2018

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×