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Rapid serial blinks: An index of temporally increased cognitive load

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  • Ryota Nomura
  • Shunichi Maruno

Abstract

In recent years, natural viewing settings with video presentation have been used in neurological and psychological experiments. However, the experienced cognitive load may differ among participants. In this study, we show that rapid serial blinks (RSB) can indicate temporally increased cognitive load with high temporal resolution. We proposed a method to create a personal criterion for respective participants by using empirical blink intervals. When we focused on more than four serial blinks (i.e., three inter-blink intervals), an increased number of RSB detect participants who felt hard to understanding, indicating a poor understanding of the subject matter. By contrast, a constant criterion across participants used in previous study could not detect participant’s understanding. These results suggest that individual differences in cognitive trait of each participant may skew the results of experiments. To avoid biases, we recommend researchers to perform an operational check on individually different temporally increased cognitive loads among experimental groups.

Suggested Citation

  • Ryota Nomura & Shunichi Maruno, 2019. "Rapid serial blinks: An index of temporally increased cognitive load," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-11, December.
    • Handle: RePEc:plo:pone00:0225897
    DOI: 10.1371/journal.pone.0225897
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    References listed on IDEAS

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    1. Jacek P. Dmochowski & Matthew A. Bezdek & Brian P. Abelson & John S. Johnson & Eric H. Schumacher & Lucas C. Parra, 2014. "Audience preferences are predicted by temporal reliability of neural processing," Nature Communications, Nature, vol. 5(1), pages 1-9, December.
    2. Ryota Nomura & Ying-Zong Liang & Kenji Morita & Kantaro Fujiwara & Tohru Ikeguchi, 2018. "Threshold-varying integrate-and-fire model reproduces distributions of spontaneous blink intervals," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-14, October.
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