Mind reading : Discovering individual preferences from eye movements using switching hidden Markov models
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Title of host publication | The Annual Meeting of the Cognitive Science Society 2016 |
Publication status | Published - Aug 2016 |
Link(s)
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(ce6ed7f2-5101-40e9-bd4f-69c4e8de7bcd).html |
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Abstract
Here we used a hidden Markov model (HMM) based approach to infer individual choices from eye movements in preference decision-making. We assumed that during a decision making process, participants may switch between exploration
and decision-making periods, and this behavior can be better captured with a Switching HMM (SHMM). Through clustering individual eye movement patterns described in SHMMs, we automatically discovered two groups of participants
with different decision making behavior. One group showed a strong and early bias to look more often at the to-be chosen stimulus (i.e., the gaze cascade effect; Shimojo et al., 2003) with a short final decision-making period. The other
group showed a weaker cascade effect with a longer final decision-making
period. The SHMMs also showed capable of inferring participants’ preference choice on each trial with high accuracy. Thus, our SHMM approach made it possible to reveal individual differences in decision making and discover individual preferences from eye movement data.
and decision-making periods, and this behavior can be better captured with a Switching HMM (SHMM). Through clustering individual eye movement patterns described in SHMMs, we automatically discovered two groups of participants
with different decision making behavior. One group showed a strong and early bias to look more often at the to-be chosen stimulus (i.e., the gaze cascade effect; Shimojo et al., 2003) with a short final decision-making period. The other
group showed a weaker cascade effect with a longer final decision-making
period. The SHMMs also showed capable of inferring participants’ preference choice on each trial with high accuracy. Thus, our SHMM approach made it possible to reveal individual differences in decision making and discover individual preferences from eye movement data.
Research Area(s)
- hidden Markov model, gaze preference, eye movement, face recognition
Citation Format(s)
Mind reading: Discovering individual preferences from eye movements using switching hidden Markov models. / Chuk, Tim; Chan, Antoni B.; Shimojo, Shinsuke (Shin) et al.
The Annual Meeting of the Cognitive Science Society 2016. 2016.
The Annual Meeting of the Cognitive Science Society 2016. 2016.
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review