Mouse tracking as a window into decision making

Mora Maldonado, Ewan Dunbar, Emmanuel Chemla

Research output: Contribution to journalArticlepeer-review


Mouse tracking promises to be an efficient method to investigate the dynamics of cognitive processes: It is easier to deploy than eyetracking, yet in principle it is much more fine-grained than looking at response times. We investigated these claimed benefits directly, asking how the features of decision processes—notably, decision changes—might be captured in mouse movements. We ran two experiments, one in which we explicitly manipulated whether our stimuli triggered a flip in decision, and one in which we replicated more ecological, classical mouse-tracking results on linguistic negation (Dale & Duran, Cognitive Science, 35, 983–996, 2011). We concluded, first, that spatial information (mouse path) is more important than temporal information (speed and acceleration) for detecting decision changes, and we offer a comparison of the sensitivities of various typical measures used in analyses of mouse tracking (area under the trajectory curve, direction flips, etc.). We do so using an “optimal” analysis of our data (a linear discriminant analysis explicitly trained to classify trajectories) and see what type of data (position, speed, or acceleration) it capitalizes on. We also quantify how its results compare with those based on more standard measures.
Original languageEnglish
Pages (from-to)1085-1101
JournalBehavior Research Methods
Issue number3
Early online date12 Feb 2019
Publication statusPublished - Jun 2019


  • mouse tracking
  • decision making
  • negation processing
  • LDA
  • sentence verification


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