Academic journal article Attention, Perception and Psychophysics

Modulations of Eye Movement Patterns by Spatial Filtering during the Learning and Testing Phases of an Old/new Face Recognition Task

Academic journal article Attention, Perception and Psychophysics

Modulations of Eye Movement Patterns by Spatial Filtering during the Learning and Testing Phases of an Old/new Face Recognition Task

Article excerpt

Published online: 7 October 2014

© The Psychonomic Society, Inc. 2014

Abstract In two experiments, we examined the effects of varying the spatial frequency (SF) content of face images on eye movements during the learning and testing phases of an old/new recognition task. At both learning and testing, participants were presented with face stimuli band-pass filtered to 11 different SF bands, as well as an unfiltered baseline condition. We found that eye movements varied significantly as a function of SF. Specifically, the frequency of transitions between facial features showed a band-pass pattern, with more transitions for middle-band faces ([asymptotically =]5-20 cycles/face) than for low-band ([asymptotically =]<5 cpf) or high-band ([asymptotically =]>20 cpf) ones. These findings were similar for the learning and testing phases. The distributions of transitions across facial features were similar for the middle-band, high-band, and unfiltered faces, showing a concentration on the eyes and mouth; conversely, low-band faces elicited mostly transitions involving the nose and nasion. The eye movement patterns elicited by low, middle, and high bands are similar to those previous researchers have suggested reflect holistic, configural, and featural processing, respectively. More generally, our results are compatible with the hypotheses that eye movements are functional, and that the visual system makes flexible use of visuospatial information in face processing. Finally, our finding that only middle spatial frequencies yielded the same number and distribution of fixations as unfiltered faces adds more evidence to the idea that these frequencies are especially important for face recognition, and reveals a possible mediator for the superior performance that they elicit.

Keywords Face recognition . Eyetracking . Spatial frequency . Configural processing

In understanding human face recognition, it is important to determine what kind of information the visual system is retrieving from face images and for what purposes. The two most fundamental factors by which visuospatial information varies are its location and its level of detail. A great deal of earlier work in face recognition has examined one of these two factors in isolation. For instance, the utility of information from different locations on the face was typically examined by showing different portions of the stimulus (Goldstein & Mackenberg, 1961; Hess & Pick, 1974) or by using eyetracking to measure where on a face people look (Althoff & Cohen, 1999; Luria & Strauss, 1978; Yarbus, 1967). Other studies have examined the utility of different levels of detail by spatially filtering a face, or noise-masking some range of spatial frequencies, to see which levels of visual detail are most necessary or most effective for recognition (Collin, Liu, Troje, McMullen, & Chaudhuri, 2004; Collin, Therrien, Campbell, & Hamm, 2012; Collin, Therrien, Martin, & Rainville, 2006; Collin, Wang, & O'Byrne, 2006; Costen, Parker, & Craw, 1994, 1996; Fiorentini, Maffei, & Sandini, 1983; Liu, Collin, Rainville, & Chaudhuri, 2000; Näsänen, 1999; Parker & Costen, 2001; Rolls, Baylis, & Leonard, 1985; Watier, Collin, & Boutet, 2010).

More recently, studies have attempted to determine how the information in a face stimulus varies as a function of both location and level of detail simultaneously (Gosselin & Schyns, 2001; Schyns, Bonnar, & Gosselin, 2002; Schyns & Gosselin, 2003; Sekuler, Gaspar, Gold, & Bennett, 2004; Vinette, Gosselin, & Schyns, 2004; Willenbockel et al., 2010). These studies have used sophisticated techniques such as Bubbles (Chauvin, Worsley, Schyns, Arguin, & Gosselin, 2005; Gosselin & Schyns, 2001; Wang, Friel, Gosselin, & Schyns, 2011) or reverse correlation (Ahumada & Lovell, 1971; Eckstein & Ahumada, 2002; Mangini & Biederman, 2004; Neri, Parker, & Blakemore, 1999; Sekuler et al. …

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