Literature DB >> 28646399

Mousetrap: An integrated, open-source mouse-tracking package.

Pascal J Kieslich1,2, Felix Henninger3,4,5.   

Abstract

Mouse-tracking - the analysis of mouse movements in computerized experiments - is becoming increasingly popular in the cognitive sciences. Mouse movements are taken as an indicator of commitment to or conflict between choice options during the decision process. Using mouse-tracking, researchers have gained insight into the temporal development of cognitive processes across a growing number of psychological domains. In the current article, we present software that offers easy and convenient means of recording and analyzing mouse movements in computerized laboratory experiments. In particular, we introduce and demonstrate the mousetrap plugin that adds mouse-tracking to OpenSesame, a popular general-purpose graphical experiment builder. By integrating with this existing experimental software, mousetrap allows for the creation of mouse-tracking studies through a graphical interface, without requiring programming skills. Thus, researchers can benefit from the core features of a validated software package and the many extensions available for it (e.g., the integration with auxiliary hardware such as eye-tracking, or the support of interactive experiments). In addition, the recorded data can be imported directly into the statistical programming language R using the mousetrap package, which greatly facilitates analysis. Mousetrap is cross-platform, open-source and available free of charge from https://github.com/pascalkieslich/mousetrap-os .

Entities:  

Keywords:  Experimental design; Mouse-tracking; OpenSesame; Process tracing; Python; Response dynamics; Software

Mesh:

Year:  2017        PMID: 28646399     DOI: 10.3758/s13428-017-0900-z

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  22 in total

1.  Generalized Processing Tree Models: Jointly Modeling Discrete and Continuous Variables.

Authors:  Daniel W Heck; Edgar Erdfelder; Pascal J Kieslich
Journal:  Psychometrika       Date:  2018-05-24       Impact factor: 2.500

Review 2.  Tracking continuities in the flanker task: From continuous flow to movement trajectories.

Authors:  Christopher D Erb; Katie A Smith; Jeff Moher
Journal:  Atten Percept Psychophys       Date:  2020-10-21       Impact factor: 2.199

3.  Response dynamics of event-based prospective memory retrieval in mouse tracking.

Authors:  Jason L Hicks; Samantha N Spitler; Megan H Papesh
Journal:  Mem Cognit       Date:  2019-07

4.  Design factors in mouse-tracking: What makes a difference?

Authors:  Pascal J Kieslich; Martin Schoemann; Tobias Grage; Johanna Hepp; Stefan Scherbaum
Journal:  Behav Res Methods       Date:  2020-02

Review 5.  Using mouse cursor tracking to investigate online cognition: Preserving methodological ingenuity while moving toward reproducible science.

Authors:  Martin Schoemann; Denis O'Hora; Rick Dale; Stefan Scherbaum
Journal:  Psychon Bull Rev       Date:  2020-12-14

6.  Decision landscapes: visualizing mouse-tracking data.

Authors:  A Zgonnikov; A Aleni; P T Piiroinen; D O'Hora; M di Bernardo
Journal:  R Soc Open Sci       Date:  2017-11-08       Impact factor: 2.963

7.  Augmented Go/No-Go Task: Mouse Cursor Motion Measures Improve ADHD Symptom Assessment in Healthy College Students.

Authors:  Anton Leontyev; Stanley Sun; Mary Wolfe; Takashi Yamauchi
Journal:  Front Psychol       Date:  2018-04-11

8.  Open-source software for mouse-tracking in Qualtrics to measure category competition.

Authors:  Maya B Mathur; David B Reichling
Journal:  Behav Res Methods       Date:  2019-10

9.  Mouse movement measures enhance the stop-signal task in adult ADHD assessment.

Authors:  Anton Leontyev; Takashi Yamauchi
Journal:  PLoS One       Date:  2019-11-26       Impact factor: 3.240

10.  Measuring the Timing of the Bilingual Advantage.

Authors:  Sara Incera
Journal:  Front Psychol       Date:  2018-10-16
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