The role of Gestalt grouping principles in visual statistical learning

Arit Glicksohn*, Asher Cohen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


A major issue in visual scene recognition involves the extraction of recurring chunks from a sequence of complex scenes. Previous studies have suggested that this kind of learning is accomplished according to Bayesian principles that constrain the types of extracted chunks. Here we show that perceptual grouping cues are also incorporated in this Bayesian model, providing additional evidence for the possible span of chunks. Experiment 1 replicates previous results showing that observers can learn threeelement chunks without learning smaller, two-element chunks embedded within them. Experiment 2 shows that the very same embedded chunks are learned if they are grouped by perceptual cues, suggesting that perceptual grouping cues play an important role in chunk extraction from complex scenes.

Original languageAmerican English
Pages (from-to)708-713
Number of pages6
JournalAttention, Perception, and Psychophysics
Issue number3
StatePublished - 2011

Bibliographical note

Funding Information:
This work was funded by a grant from the Israel Science Foundation to A.C.


  • Chunking
  • Perceptual organization
  • Scene perception
  • Statistical learning


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