Year: 2011
Type: article
Abstract: Doing Cognitive Science by Hand: A Tutorial on Computer Mouse-Tracking Jonathan B. Freeman ([email protected]) Department of Psychology, Tufts University Medford, MA 02155 Rick Dale ([email protected]) Department of Psychology, The University of Memphis Memphis, TN 38152 Michael J. Spivey ([email protected]) Department of Cognitive and Information Sciences, University of California, Merced Merced, CA 95343 Keywords: mouse-tracking, control, action cognitive dynamics, motor across domains and pushes a unified methodological message that manual action provides a powerful window into cognitive processes (Freeman, Dale, & Farmer, 2011). Mouse-tracking research also has theoretical significance, and it is often used to make critical distinctions between competing theoretical accounts. For example, mouse-tracking data have already been central to the development of broad theories of mental processing (Spivey, 2007), and researchers often use such data to select one theoretical model over another, e.g., dynamic versus symbolic models (Farmer, Anderson, & Spivey, 2007; Freeman & Ambady, 2011a; Freeman et al., 2008). For example, in one study, participants categorized faces’ sex by moving the mouse from the bottom-center of the screen to a M ALE or F EMALE response, located in the top-left and top-right corners (Figure 1; Freeman & Ambady, 2011b). When simultaneously processing a sex- atypical voice, participants’ mouse movements were continuously attracted to the opposite sex-category response before arriving at response consistent with the face’s sex. This opened up the real-time face‒voice integration process and showed how ongoing processing results from the two modalities are dynamically integrated over time. Background Recently, the measurement of computer-mouse trajectories en route to choices on the screen has served as a window into the real-time dynamics of a wide range of cognitive processes. This mouse-tracking methodology is able to provide a sensitive, temporally fine-grained measure by which participants’ tentative commitments to various choice alternatives can be tracked semi-continuously over hundreds of milliseconds. Similar in spirit to the goals of eye-tracking methods, mouse-tracking may provide access to the micro- structure of perceptual, cognitive, and social decisions. Though both methodologies have their strengths, one advantage of mouse-tracking is that it relies on continuous streams of hand motion rather than discrete saccades, and it does so with nominal cost—needing nothing more than a computer and mouse. These qualities led Magnuson (2005, p. 9996) to comment that “the continuous data provided by the mouse-tracking technique [has] the potential to address not only specialized theoretical debates but also some of the biggest questions facing cognitive science.” The mouse-tracking methodology has been applied across a range of topics in cognitive science in recent years. Through tracking hand movement, novel findings about the real-time dynamics of cognition have been made with respect to spoken-word recognition (Spivey, Grosjean, & Knoblich, 2005), semantic categorization (Dale, Kehoe, & Spivey, 2007), sentence processing (Dale & Duran, in press; Farmer, Cargill, Hindy, Dale, & Spivey, 2007), evaluative thinking (Wojnowicz, Ferguson, Dale, & Spivey, 2009), person perception (Freeman & Ambady, 2009; Freeman, Ambady, Rule, & Johnson, 2008; Freeman, Pauker, Apfelbaum, & Ambady, 2010), audiovisual integration (Freeman & Ambady, 2011b), learning (Dale, Roche, Snyder, & McCall, 2008), decision making (McKinstry, Dale, & Spivey, 2008), deception (Duran, Dale, & McNamara, 2010), time perception (Miles, Betka, Pendry, & Macrae, 2010), and many others. This research cuts Figure 1. Mouse-tracking reveals continuous integration of face and voice processing (Freeman & Ambady, 2011b).
Institution: Tufts University
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2573455183