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Disentangling decision errors from action execution in mouse-tracking studies: The case of effect-based action

Solveig Tonn1, Moritz Schaaf2, Wilfried Kunde3

  • 1Department of Psychology, University of Trier, Johanniterufer 15, 54290, Trier, Germany. tonn@uni-trier.de.

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Mouse-tracking studies risk incorrect conclusions by averaging data. A new method separates online processing from decision errors, revealing crucial differences in cognitive and emotional state research.

Keywords:
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Area of Science:

  • Cognitive Psychology
  • Human-Computer Interaction
  • Neuroscience

Background:

  • Mouse-tracking is a valuable tool for inferring cognitive and emotional states from movement trajectories.
  • Aggregated mouse-tracking data can obscure distinct underlying mechanisms, leading to potential misinterpretations.
  • Averaging data conflates online processing during action execution with decision and initiation process limitations.

Purpose of the Study:

  • To introduce a method for disentangling online processing influences from decision/initiation errors in mouse-tracking data.
  • To assess the appropriateness of process-pure interpretations in mouse-tracking research.
  • To re-evaluate previous findings in ideomotor action control using this novel analytical approach.

Main Methods:

  • Development of a simple analytical method to differentiate contributions from online processing and decision/initiation stages.
  • Application of the method to trial-by-trial data from 12 published experiments on ideomotor action control.
  • Comparative analysis of interpretations based on aggregated versus single-trial trajectory data.

Main Results:

  • The proposed method effectively dissociates online processing from decision and initiation errors.
  • Re-analysis of 12 ideomotor control experiments demonstrated that interpretations of previous results are altered when these factors are separated.
  • Evidence suggests that aggregated data can lead to inaccurate conclusions about cognitive and emotional states.

Conclusions:

  • Researchers using mouse-tracking should prioritize detailed trial-by-trial analyses over aggregated data.
  • Distinguishing between online processing and decision/initiation errors is crucial for accurate interpretation of mouse-tracking data.
  • This approach enhances the validity of inferences about cognitive and emotional states derived from movement trajectories.