Effects of Target Size and Symmetry on the Structure of Variability in Precision Aiming

Effects of Target Size and Symmetry on the Structure of Variability in Precision Aiming Veronica Romero (romerovc@mail.uc.edu) Center for Cognition, Action and Perception, Department of Psychology, University of Cincinnati, ML 0376, 4150 Edwards Cl., University of Cincinnati, Cincinnati, OH 45221-0376 USA Charles A. Coey (coeyca@mail.uc.edu) Center for Cognition, Action and Perception, Department of Psychology, University of Cincinnati, ML 0376, 4150 Edwards Cl., University of Cincinnati, Cincinnati, OH 45221-0376 USA Andrew Beach (beachaw@mail.uc.edu) Center for Cognition, Action and Perception, Department of Psychology, University of Cincinnati, ML 0376, 4150 Edwards Cl., University of Cincinnati, Cincinnati, OH 45221-0376 USA Michael J. Richardson (richamo@ucmail.uc.edu) Center for Cognition, Action and Perception, Department of Psychology, University of Cincinnati, ML 0376, 4150 Edwards Cl., University of Cincinnati, Cincinnati, OH 45221-0376 USA Abstract The current experiment investigated the effects of target size and symmetry on the dynamics of precision aiming. Participants were asked to sit on a chair and point at the center of four different targets (a small and big square target, and a horizontal and vertical rectangular target). The aiming movements were assessed using linear (root mean square) and non-linear fractal statistics (DFA and MFDFA). We found that participants spontaneously exhibited more movement in target dimensions with less spatial constraint (i.e., larger target dimensions). These larger movements, however, were more deterministic than the movements accompanying the smaller targets, indicating that more variation in aiming does not necessarily mean more random. Finally, even though participants’ movements were multifractal, the different manipulations and task constraints had no effect on the width of the multifractal spectrum. These results suggest that human performance emerges from the complex relationship and interactions that exist between the perception and action capabilities of the human body and the physical environment. Keywords: Cognitive science, psychology, action, motor control, complex systems, 1/f noise. Introduction Accuracy in tasks such as pistol shooting and archery depends on a person’s ability to precisely aim at intended targets, which requires meticulous and refined control of the body and its relationship to the environment around it. Scholz, Schoner and Latash (2000) showed that expert shooters arrange the different components in their body into a motor synergy, coupling certain components to each other and therefore minimizing the necessary movements in order to be more precise. Complimentary research efforts have studied how different task constraints or elements of the physical environment affect how people move their bodies in order to aim precisely, such as target size (Ramenzoni et al., 2011) or distance (Balasubramaniam, Riley & Turvey, 2000). However, the effect that such environmental factors have on how people organize their bodies to achieve precision aiming has not yet been revealed in full detail. Psychologists have traditionally evaluated the impact of task constraints on precision aiming (e.g., target size) using linear statistical tools, such as summarizing effects in means and standard deviations. Recently, statistical techniques allowing researchers to examine more complex aspects of such behavior have come to the fore, most notably, techniques that allow researchers to uncover the fractal structure in movement and behavioral variability (Gilden, 2001; Ihlen, 2012; Delignieres & Marmelat, 2013). Fractal or 1/f scaling refers to patterns in the variability of behavior that are long-term correlated such that deviations early in a recorded behavior are correlated with deviations that occur much later in the behavior. This kind of structure in variability is often referred to as “pink noise”, denoting its difference from the highly irregular or random fluctuations of “white noise” and the highly regular or deterministic fluctuations of “brown noise” (see Figure 1). The degree to which a behavioral measurement series exhibits fractal scaling can be summarized by the Hurst exponent. The Hurst exponent (H) for white noise is 0.5 and for brown noise is 1.5, with pink noise in-between (H ≈ 1) (Ihlen, 2012). Pink noise has been associated with signs of healthy functioning (for a review, Van Orden, Kloos & Wallot, 2009) in different human movement tasks, such as tapping (Kello et al., 2007; Delignieres, Torre & Lemoine, 2008; Torre, Balasubramaniam & Delignieres, 2010), stimulus- response tasks (Holden, Choi, Amazeen & Van Orden, 2010), postural sway (Schmit, Regis & Riley, 2005; Schmit et. al., 2006), walking (Hausdorff, 2007) and eye-movement behavior (Coey et al., 2012).