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Article Excerpt
INTRODUCTION
The ability to notice behaviorally meaningful objects and events in the visual surroundings is fundamental to an operator's capacity to maintain performance in a complex environment. Indeed, Endsley's (1995) widely cited model of situation awareness recognizes the perception of task-relevant information in the environment as the foundational stage of knowing and understanding "what is going on around you" (Endsley, 2000, p. 5). It is less obvious, however, how easily perception and attention may fail. Despite people's impressions of a detailed and continuous visual world, human performance data indicate that lapses of perception and attention are frequent and often consequential. Jones and Endsley (1996), for example, found that 76% of pilot errors were attributable to failures of perception and attention. Similarly, attentional lapses have been implicated as an important cause of various forms of traffic error (Langham, Hole, Edwards, & O'Neil, 2002; Larsen & Kines, 2002).
Recent findings in the study of visual performance have corroborated the suggestion that perception is less comprehensive than introspection suggests. Evidence demonstrates that attention is generally necessary, for the conscious perception of objects within a static scene (Mack & Rock, 1998) as well as for the detection of events within a scene (Pringle, Irwin, Kramer; & Atchley, 2001; Pringle, Kramer, & Irwin, 2004; Rensink, O'Regan, & Clark, 1997; Simons & Levin, 1997). Under common circumstances, visual events generate localized transient signals--motion or flicker--which capture attention and ensure that changes within an operator's surroundings are noticed. When the transient signal produced by an event is somehow masked, however, the event itself may go unattended and therefore undetected.
Even seemingly obvious changes can thus fail to reach awareness, a phenomenon known as change blindness (Simons & Levin, 1997). To avoid such perceptual failure, an observer must rely on effortful, attentive scanning (Hollingworth, Schrock, & Henderson, 2001; Rensink et al., 1997) to actively encode objects and note changes to them. Bottom-up/stimulus-driven and top-down/knowledge-driven processes guide such scanning, helping to ensure that changes are detected more easily when made to objects that are physically salient or meaningful within the context of a scene (Pringle et al., 2001, 2004). Nonetheless, changes to important and physically conspicuous objects often go unnoticed.
The study of change blindness has provided basic researchers with insight into the cognitive and neural bases of conscious perception. The implications of the phenomenon, however, extend into applied domains. Data indicate that change blindness can result from a variety naturalistic visual events, including saccades (Grimes, 1996), blinks (O'Regan, Deubel, Clark, & Rensink, 2000), egomotion (Wallis & Bulthoff, 2000), occlusion of a changing item (Simons & Levin, 1998), and the presence of irrelevant transient signals (O'Regan, Rensink, & Clark, 1999). As such, change blindness can occur outside of contrived laboratory settings (Simons & Levin, 1998) and is likely to mediate visual performance in real-world tasks and circumstances. An understanding of the mechanisms and processes underlying change detection might therefore provide insight into the limits of human perception and cognition outside the lab. By the same token, change detection may serve as a gauge of perceptual-cognitive performance under varying circumstances.
One applied use of the change detection paradigm has been in the study of the effects of cognitive distraction on perceptual performance. An experiment by Richard et al. (2002) examined the effects of a secondary task on reaction times (RTs) for the detection of changes in traffic scenes. Meant to simulate a hands-flee cellular phone conversation, the loading task required participants to listen to and remember a short declarative sentence presented through a speaker. A test of sentence memory followed each trial. Control conditions required observers to perform the change detection task alone. Notably, the pairing of an auditory secondary task with the visual primary task minimized the possibility of sensory or peripheral conflict. Data nonetheless revealed that change detection was reliably slowed by the imposition of the distracting task. This was true, interestingly, even for changes that were highly meaningful within the context of the scenes presented. In other words, top-down/knowledge-driven processes did not seem to attenuate the effects of the loading task.
This implies that distraction may impair the perception of even highly task-relevant stimuli. In light of evidence for an important role of eye movements in mediating change detection (Hollingworth et al., 2001), along with findings that nonvisual cognitive workload can modify saccadic behavior (e.g., May, Kennedy, Williams, Dunlap, & Brannan, 1990; Recarte & Nunes, 2000, 2003), Richard et al. (2002) speculated that the effect of distraction in the change detection task might be to disrupt observers' oculomotor scanning.
EXPERIMENT 1
The aim of the current work was to further explore the consequences of hands-free cellular phone conversation for visual performance in a change detection task. Observers were asked to search for changes within complex traffic scenes, in which flicker of the display was used to mask the local transients produced by the changes. In Experiment 1, observers performed the change detection task either under single-task control conditions or while concurrently maintaining a casual conversation with an experimenter's confederate. Naturalistic conversation was chosen as the secondary task to simulate the form of cognitive load that would obtain from cellular phone use, a common real-world distraction. In dual-task conditions of Experiment 2, observers performed the change detection task while listening attentively to a conversation between others. Eye-tracking data were recorded along with RTs and error rates. Target objects were varied in salience and in meaningfulness so that the effects of distraction on stimulus-driven and knowledge-driven processes could be assessed.
Two questions were of particular interest. First, what is the effect of distraction on oculomotor behavior and visual encoding during search for change? As noted, eye movements appear to play an important role in change detection. More specifically, data from Hollingworth et al. (2001) indicate that changes in the flicker paradigm are rarely detected until after they have been fixated. Other findings indicate that saccadic behavior is also subject to interference from nonvisual secondary tasks. Recartes and Nunes (2000), for instance, found that imposition of a cognitive loading task modified drivers' fixation durations and altered oculomotor scan patterns in an on-road task. It is thus possible, as postulated by Richard et al. (2002), that the degrading effects of the distracting task they employed were mediated by changes in observers' oculomotor scanning behavior. Another possibility is that distraction might impair change detection by degrading the attentional processing of foveated information. Strayer, Drews, and Johnston...
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