Quality of average representation can be enhanced by refined individual items

Jihong Lee, Sang Chul Chong

Research output: Contribution to journalArticlepeer-review


Ensemble perception is efficient because it summarizes redundant and complex information. However, it loses the fine details of individual items during the averaging process. Such characteristics of ensemble perception are similar to those of coarse processing. Here, we tested whether extracting an average of a set was similar to coarse processing. To manipulate coarse processing, we used the fast flicker adaptation known as suppressing coarse information processed by the magnocellular pathway. We hypothesized that if computing the average of a set relied on coarse processing, the precision of an averaging task should decrease after adaptation compared to baseline (no-adaptation). Across experiments with various features (orientation in Experiment 1, size in Experiment 2, and facial expression in Experiment 3), we found that suppressing coarse information did not disrupt the performance of the averaging tasks. Rather, adaptation increased the precision of mean representation. The precision of mean representation might have increased because fine information was relatively enhanced after adaptation. Our results suggest that the quality of ensemble representation relies on that of individual items.

Original languageEnglish
JournalAttention, Perception, and Psychophysics
Publication statusAccepted/In press - 2020

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2019R1A2B5B01070038). Data in this research article were previously presented at the 19th annual meeting of the Vision Sciences Society (May 2019).

Publisher Copyright:
© 2020, The Psychonomic Society, Inc.

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Experimental and Cognitive Psychology
  • Sensory Systems
  • Linguistics and Language

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