The role of peripheral vision in implicit contextual cuing

Abstract

76Our environment contains a large amount of visual information, such as different objects, buildings, and faces, making it impossible to process this complex information at once. In order to compensate for the limitations of the visual system, attention is allocated to the most relevant visual information. Attention can be guided by bottom-up and top-down processes. That is, a specific visual feature can attract attention (e.g., a fast-moving object or a bright color), resulting in an eye movement to the source of information (bottom-up process). In addition, knowledge about our environment can guide attention (top-down process).One of the top-down mechanisms that guide attention is a result of implicit contextual learning, as was initially shown by Chun and Jiang (1998). They suggested that visual information from our environment can be learned implicitly and can subsequently guide attention to a specific target location. That is, the association between a target and its surrounding visual context (such as spatial information) can be memorized, improving performance on a visual search task. The contextual-cuing paradigm is typically used to study implicit contextual learning of spatial information. It involves a visual search task, in which a rotated target stimulus (T) is presented among a number of rotated distractors (Ls). The participants have to locate the target as quickly as possible and indicate the direction of rotation. Half of the spatial configurations (i.e., positions of the stimuli) are repeated during the experiment. Interestingly, response times are shorter when the configurations are repeated than when they are new, indicating that contextual information was memorized (Chun, 2000;Chun & Jiang, 1998;Peterson & Kramer, 2001). Participants are not aware of the repetitions and perform at chance level on a recognition memory task, indicating that it is an implicit memory process. This effect is found after a few repetitions (Chun & Jiang, 1998) and remains for weeks after testing (Chun & Jiang, 2003;Jiang, Song, & Rigas, 2005), indicating that it is a robust mechanism.Recently, Brady and Chun (2007) proposed a model of implicit contextual learning, based on the idea that contextual learning results from the pairwise statistical association between the distractor locations and the target. They used this model to predict the outcome of different contextual-cuing tasks. An important and interesting aspect of the model is that it includes a spatial constraint, assuming that learning is restricted to the local area around the target. Thus, a very limited amount of contextual information is learned, which is spatially close to the target. They stated that "observers may be encoding just one snapshot of the local context surrounding the target when it is detected" (p. 813). Brady and Chun tested this model by comparing modeling results with behavioral results under different task conditions and found that the model was accurate in predicting the behavioral results of various experimental studies. The idea...

Statistical learning in the past modulates contextual cueing in the future

“…Thus, the present study supports previous findings showing that implicit contextual associations are retained across inconsistencies and possible sources of retroactive interference (Chun & Jiang, 2003;Jiang, Song, & Rigas, 2005;Jungé et al, 2007;Mednick, Makovski, Cai, & Jiang, 2009;van Asselen & Castelo-Branco, 2009;Zellin et al, 2013). As for the results of Experiment 1, successful contextual cueing in both the exchange and return phases suggests that old contexts cue at least two (predictable) target locations equally efficiently with no evidence of interference between target locations (see also Conci et al, 2011).…”

“…In statistical learning, observers often form implicit expectations about future occurrences of familiar visual events based on their predictability (Beesley & Le Pelley, 2010;Dale, Duran, & Morehead, 2012;Reder, Weber, Shang, & Vanyukov, 2003;Turk-Browne, Scholl, Johnson, & Chun, 2010; see also Neider & Zelinsky, 2006, for more naturalistic scenes). For example, when observers implicitly expected fixed target locations not to be predicted by surrounding context information (new contexts), they were unable to learn actual old (i.e., repeated) contexts when they were presented (Jungé, Scholl, & Chun, 2007).…”

Simulated loss of foveal vision eliminates visual search advantage in repeated displays

“…Two important differences between the study of van Asselen and Castelo-Branco (2009) and our data have to be considered. First, the stimulus positions used by van Asselen and Castelo-Branco (2009) fell approximately into the area covered by the scotoma in our study, that covered an area of 3.5° (4.5° including the Gaussian fading at the border which additionally degraded the visual input to some extent).…”

“…Nevertheless, they also observed a contribution of global regularities to contextual cueing. van Asselen and Castelo-Branco (2009) examined the contribution of peripheral vision to contextual cueing. In their study, participants were instructed to fixate centrally throughout display presentation.…”

Rewarding context accelerates implicit guidance in visual search

“…This finding has been widely accepted as reflecting a case in which implicit learning affects the attentional system: The learned implicit spatial context guides attention toward the target location (Chun & Jiang, 1998, 1999Chun & Nakayama, 2000;van Asselen & Castelo-Branco, 2009). This finding has been supported by eye movement studies (Manginelli & Pollmann, 2009;Peterson & Kramer, 2001;Tseng & Li, 2004;van Asselen, Sampaio, Pina, & CasteloBranco, 2011) and electrophysiological studies (Olson, Chun, & Allison, 2001;Schankin & Schubö, 2009).…”