Mutual Information of Image Fragments Predicts Categorization in Humans: Electrophysiological and Behavioral Evidence

Assaf Harel, Shimon Ullman, Boris Epshtein, Shlomo Bentin

Research output: Contribution to journalArticlepeer-review

Abstract

Computational models suggest that features of intermediate complexity (IC) play a central role in object categorization [Ullman, S., Vidal-Naquet, M., & Sali, E. (2002). Visual features of intermediate complexity and their use in classification. Nature Neuroscience, 5 , 682–687.]. The critical aspect of these features is the amount of mutual information (MI) they deliver. We examined the relation between MI, human categorization and an electrophysiological response to IC features. Categorization performance correlated with MI level as well as with the amplitude of a posterior temporal potential, peaking around 270 ms. Hence, an objective MI measure predicts human object categorization performance and its underlying neural activity. These results demonstrate that informative IC features serve as categorization features in human vision.

Original languageAmerican English
JournalVision Research
Volume47
DOIs
StatePublished - Jul 1 2007

Keywords

  • Categorization
  • Event-related Potentials (ERPs)
  • Features
  • Human Performance
  • Object Recognition

Disciplines

  • Psychology
  • Social and Behavioral Sciences

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