Eye movement analysis with switching hidden Markov models
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Eye movement analysis with switching hidden Markov models Tim Chuk 1 & Antoni B. Chan 2 & Shinsuke Shimojo 3 & Janet H. Hsiao 1,4
# The Psychonomic Society, Inc. 2019
Abstract Here we propose the eye movement analysis with switching hidden Markov model (EMSHMM) approach to analyzing eye movement data in cognitive tasks involving cognitive state changes. We used a switching hidden Markov model (SHMM) to capture a participant’s cognitive state transitions during the task, with eye movement patterns during each cognitive state being summarized using a regular HMM. We applied EMSHMM to a face preference decision-making task with two pre-assumed cognitive states—exploration and preference-biased periods—and we discovered two common eye movement patterns through clustering the cognitive state transitions. One pattern showed both a later transition from the exploration to the preference-biased cognitive state and a stronger tendency to look at the preferred stimulus at the end, and was associated with higher decision inference accuracy at the end; the other pattern entered the preference-biased cognitive state earlier, leading to earlier abovechance inference accuracy in a trial but lower inference accuracy at the end. This finding was not revealed by any other method. As compared with our previous HMM method, which assumes no cognitive state change (i.e., EMHMM), EMSHMM captured eye movement behavior in the task better, resulting in higher decision inference accuracy. Thus, EMSHMM reveals and provides quantitative measures of individual differences in cognitive behavior/style, making a significant impact on the use of eyetracking to study cognitive behavior across disciplines. Keywords Hidden Markov model . Eye movement . Preference decision making . EMHMM
Recent research has shown that people have idiosyncratic eye movement patterns in visual tasks that are consistent across different stimuli and tasks (e.g., Andrews & Coppola, 1999; Castelhano & Henderson, 2008; Kanan, Bseiso, Ray, Hsiao, & Cottrell, 2015; Poynter, Barber, Inman, & Wiggins, 2013). These idiosyncratic eye movement patterns may reflect individual differences in cognitive style or abilities. For example, Risko, Anderson, Lanthier, and Kingstone (2012) found that participants who demonstrated higher levels of curiosity made significantly more fixations in a scene-viewing task than did * Antoni B. Chan [email protected] * Janet H. Hsiao [email protected] 1
Department of Psychology, University of Hong Kong, Hong Kong, Hong Kong
2
Department of Computer Science, City University of Hong Kong, Hong Kong, Hong Kong
3
Department of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
4
The State Key Laboratory of Brain and Cognitive Sciences, University of Hong Kong, Hong Kong, Hong Kong
those who demonstrated lower levels of curiosity. Wu, Bischof, Anderson, Jakobsen, and Kingstone (2014) found that when viewing human faces, those who scored higher on extraversion and agreeableness personality traits looked at the ey
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