Psychon Bull Rev DOI 10.3758/s13423-014-0708-0
BRIEF REPORT
Susceptible to distraction: Children lack top-down control over spatial attention capture Nicholas Gaspelin & Tessa Margett-Jordan & Eric Ruthruff
# Psychonomic Society, Inc. 2014
Abstract Considerable evidence has indicated that adults can exert top-down control to avoid distraction by salient-butirrelevant stimuli. However, relatively little research has explored how this ability develops across the lifespan. In the present study, we therefore assessed how well children can control the capture of spatial attention. Children (Mage = 4.2 years) and adults (Mage = 21.5 years) searched for target “spaceships” of a specific color while trying to ignore salient precues that either matched or mismatched the target spaceship color. The results demonstrated that children are, in fact, more vulnerable to capture by irrelevant stimuli than are adults, even after accounting for children’s overall cognitive slowing.
Keywords Attention capture . Visual search . Spatial attention . Children
Attention capture is a daily cognitive phenomenon, rapidly drawing processing resources toward visual stimuli. Adults are not immune to capture, but they can exert top-down control in order to minimize distraction by task-irrelevant salient stimuli. It is unclear, however, when in the lifespan this top-down control over spatial attention develops. It is often assumed that children are vulnerable to visual distraction, yet little empirical research has directly tested this assumption. Before describing how we addressed this issue in the present study, we will first briefly review the attention capture literature.
N. Gaspelin (*) : T. Margett-Jordan : E. Ruthruff Department of Psychology, 1 University of New Mexico, MSC03 2220, Albuquerque, NM 87131-1161, USA e-mail: [email protected]
Top-down control over attention capture in adults Because visual environments are complex, our visual systems select only a small subset of the available information for semantic processing. Spatial attention allows us to covertly shift processing resources across a visual scene, independently of eye movements. Often these shifts are triggered involuntarily by the appearance of a salient stimulus, a phenomenon known as involuntary attention capture. Because involuntary capture is particularly fast (e.g., 35–100 ms; Horowitz, Wolfe, Alvarez, Cohen, & Kuzmova, 2009), it can rapidly draw attention toward important objects (e.g., a yellow “wet floor” sign), as well as toward completely irrelevant ones (e.g., a fidgeting neighbor in class). Despite the debate regarding the details of attention capture, there is strong evidence that adults are captured much more strongly by task-relevant than by task-irrelevant stimuli (Folk, Remington, & Johnston, 1992; but see Theeuwes, 2010). In a seminal study of capture, Folk et al. (1992) used a precuing paradigm: Participants searched displays for a target defined by a simple feature (color or abrupt onset) and reported its identity (X vs. =). The search display was preceded by a salient cue placed randomly at a possible target location. If captured by the precue, participants should respond more quickly to targets at the cued location (valid trials) than to targets located elsewhere (invalid trials), which is called the cue validity effect. Importantly, validity effects were present only for cues that matched the target-finding feature. For example, when the target was defined by red, red cues produced validity effects but white onset cues (i.e., flashing dots) did not, and vice versa. Folk et al. (1992) concluded that attention capture is contingent on a match with the viewer’s attentional set (i.e., it is goal-driven). Much subsequent research has supported the contingentcapture account (e.g., Folk, Leber, & Egeth, 2002; Gaspelin, Ruthruff, Lien, & Jung, 2012; Lien, Ruthruff, Goodin, &
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Remington, 2008; Lien, Ruthruff, & Johnston, 2010). As an example of adults’ extraordinary ability to avoid capture by salient stimuli, Lien et al. (2010) used a precuing paradigm, but changed the upcoming target-finding feature before every trial, indicated by a prompt (e.g., an “R” to indicate red, for 1,200 ms). Surprisingly, trial-to-trial fluctuations in attentional set did not increase vulnerability to capture by task-irrelevant stimuli; indeed, adult participants avoided capture by a color that they had searched for only a few seconds before (but see also Belopolsky, Schreij, & Theeuwes, 2010). It is unclear when in the lifespan this extraordinary topdown control over spatial attention develops. It appears to be widely believed that children are particularly vulnerable to attention capture by irrelevant stimuli. For example, a recent Psychology Today article discussed why children are vulnerable to distraction and how such distraction can be managed (Bernstein, 2012). Similarly, Fisher, Godwin, and Seltman (2014) had children (Mage = 5.4 years) learn information for later recall in either highly decorated or sparsely decorated classroom environments. Children in highly-decorated classrooms were ultimately unable to learn as efficiently as children in sparsely-decorated classrooms, which these researchers took as evidence of distractibility in children. Despite the aforementioned claims, little formal research has actually investigated the basic science of attention capture in children. Although some research has suggested that executive control develops throughout early childhood (Cepeda, Kramer, & Gonzalez de Sather, 2001; Williams, Ponesse, Schachar, Logan, & Tannock, 1999), it is unclear whether this empirical generalization applies specifically to the control of spatial attention, which has high practical importance.
Previous research To determine whether children lack top-down control over spatial attention relative to adults, a study must meet the following criteria. First, a sample of healthy children and adults must be directly compared. Second, given children’s marked overall cognitive slowing (Kail, 1991; Kail & Ferrer, 2007), one must determine whether any age effects reflect mere generalized slowing or a specific deficit in top-down control over spatial attention. A related third point is that the study should specifically compare the relative sizes of the capture effects produced by task-irrelevant and task-relevant stimuli (e.g., as in Folk et al., 1992). Task-relevant stimuli provide a very useful measure of “maximum” capture, so that one can meaningfully interpret the magnitude of capture by task-irrelevant stimuli. Several previous studies have measured attention capture in children (Deltour et al., 2007; Greenaway & Plaisted, 2005; Leclercq & Siéroff, 2013; Mason, Humphreys, & Kent, 2004; Oh-Uchi, Kawahara, & Sugano, 2010; Waters, Lipp, &
Spence, 2004). None of these studies, however, met all of the aforementioned criteria, likely because they were intended to answer somewhat different research questions. A few studies, however, met one or two of the above criteria. Interestingly, these studies suggested that children are not more susceptible to attention capture than adults. Oh-Uchi et al. (2010) compared attention capture in children (Mage = 6.1 years) and adults (Mage = 20.9 years). Participants searched displays of horizontal green fish for a lone vertical green fish and reported its orientation (up vs. down). On half of the trials, one distractor fish differed in color (red) from the green fish. Both age groups were slowed by the presence of the red color-singleton fish (adults by 54.7 ms, children by 200 ms). The researchers concluded that both children and adults are equally susceptible to capture by salient stimuli. However, this study failed to meet the second aforementioned criterion: They did not correct for overall cognitive slowing. Furthermore, the additional-singleton paradigm used in this study made it impossible to include relevant color cues, violating the third criterion. For example, children might have shown even larger interference effects for relevant stimuli, demonstrating a large degree of top-down control over attention capture. Also, it is unclear whether one should classify the color singletons in this study as relevant or irrelevant, because it is unclear whether participants were specifically looking for the unique target shape (vertical fish) or merely looking for any unique object (cf. Bacon & Egeth, 1994). Greenaway and Plaisted (2005, Exp. 1) used a precuing paradigm to assess attention capture in typically developing and in autistic children (Mage = 11.5 years). Complying with the third criterion above, they assessed capture by both irrelevant and relevant stimuli. For typically developing children, validity effects were greater for relevant than for irrelevant cues, indicating some degree of top-down control. Because the study had no adult participants for comparison, however, it remains unclear whether typically developing children are more vulnerable to capture than adults. Their stimulus timing also deviated from those in previous studies with adults (e.g., a longer stimulus onset asynchrony between the cue and search array), complicating comparisons. Finally, the authors did not take into account overall cognitive slowing in children.
The present study To summarize, no previous research has satisfactorily compared top-down control of attention capture in children and adults. Therefore, we designed a study that would satisfy the aforementioned criteria. To establish the full developmental sequence for cognitive processes, one should start with the youngest age of children that can complete testing. Children younger than 4 years old would be too cognitively and
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motorically immature to provide meaningful data on our reaction-time task (for a review, see Kail, 1991). We therefore had preschool children (Mage = 4.2 years) and university students (Mage = 21.5 years) perform in a precuing paradigm. The participants searched target displays for a spaceship of a specific color. This target display was preceded by a nonpredictive precue: a relevant color singleton (target color), an irrelevant color singleton (nontarget color), or an irrelevant abrupt onset. Adults should show the typical contingentcapture effect—large validity effects for relevant cues, but small nonsignificant validity effects for irrelevant cues (as in Folk et al., 1992). The critical question was whether young children would show the same goal-driven pattern or would instead show large validity effects from irrelevant cues, after adjusting for overall cognitive slowing.
Method Participants The participants had normal color vision (as assessed by an Ishihara color vision test) and self- or parent-reported normal or corrected-to-normal visual acuity. Children A group of 44 children (4–5 years old) from two local preschools participated. Four of the participants did not complete the experiment, and one was excluded from the final analyses due to an abnormally high error rate (2.5 SDs above the group mean of 5.1 %). The remaining 39 child participants (21 male, 18 female) had a mean age of 4.2 years. Adults A group of 48 undergraduates (18–55 years old) from the University of New Mexico participated for course credit. Three of the participants were excluded due to abnormally high error rates (2.5 SDs above the adult group mean of 1.9 %). The remaining 45 adults (35 female, ten male) had a mean age of 21.5 years. Materials and procedure Apparatus A laptop computer displayed stimuli on a 14-in. LCD monitor using software created in the C programming language using Allegro gaming libraries (http://alleg. sourceforge.net/ ). Stimuli Each search display contained one spaceship (2.9° in width and 2.0° in height, based on an average viewing distance of 56 cm) in one of four different colors: green (RGB values of 0, 151, 0), red (255, 0, 0), blue (0, 128, 255), and white (255, 255, 255). The placeholders were gray (125, 125, 125), unfilled boxes (3.9° in width and height). All of the colors (except white) were designed to be roughly
equiluminant against a black background. Eight rectangular boxes formed an imaginary circle (18° in diameter), with one additional fixation box in the middle. Only four locations could contain spaceships (top, bottom, left, or right). In the cue frame, color-singleton cues were created by thickening one placeholder box and coloring it (red, blue, or green). The abrupt-onset cues were four white dots (0.8° in diameter) appearing around one placeholder (forming an imaginary diamond 5.5° in height and width). See Fig. 1 for stimuli in each condition. Design Participants were randomly assigned to a target color (red, blue, or green), with the restriction that each color be used equally often across participants. Target identity (left vs. right) and target location were randomly chosen, with the restriction that each identity occurred equally often. Distractor colors and identities were chosen randomly, with the restriction that each display contained one ship of each color and that equal numbers of ships faced in each direction. Each cue type (red, blue, green, or onset) was equally probable (25 %) and chosen randomly. Cue location (always one of the four possible target locations) was chosen randomly, and therefore was nonpredictive of target location (25 % valid, 75 % invalid). The experiment began with a practice block of 32 trials, followed by eight regular blocks of 32 trials. Procedure Both children and adults received instructions with audio and animations designed to make the task engaging (see Fig. 2A). An astronaut character explained that the participant was helping with a space mission to cross the solar system. Target-colored ships needed fuel. To assist in fueling, the participant was to quickly report which way the target-color ship faced by pressing a key labeled with a left or a right arrow (actual keys: “Z” and “M”). Participants were instructed to ignore the precue. An adult experimenter sat with each child participant throughout the experimental session, offering instructions and motivation. Each trial began with a presentation of the nine placeholders for 1,000 ms. Then, the fixation placeholder disappeared for 100 ms and reappeared for 500 ms to denote trial onset. Next, the precue display appeared for 100 ms, followed by the placeholder frame for another 50 ms. The search array then appeared until response. Extensive piloting revealed that these cue and search display durations produced cue validity effects in both adults and children. Participants received immediate feedback on accuracy. If a response was correct, a rewarding chime sounded and the search display disappeared. If incorrect, a low buzzer sounded and the target-colored ship shrank until it disappeared. After each block, participants were told that they had reached a new planet (see Fig. 2B) and received block
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Fig. 1 Example trial sequence from the red target condition for each of the three possible cue types (all invalid in the examples shown). In the grayscale figures, the red target is portrayed as a gray ship amongst white
ships (actual colors: white, blue, and green), and color cues are shown as dashed boxes (irrelevant [blue/green] and relevant [red]). To download color figures, please visit www.unm.edu/~ruthruff/DevColorFigures.pdf
performance feedback in the form of two gauges, one for speed and one for accuracy (with three labels: “good,” “great,” or “awesome”). The gauge needle slowly rose until it reached the achieved position. The needle never dropped below “good.” The accuracy gauge’s range was identical for children and adults (lower limit 85 % and upper limit 100 %).
However, because young children are much slower than adults (Kail, 1991), we used different response time (RT) ranges for the different age groups, on the basis of pilot studies. The RT gauges ranged from 2,000 to 1,300 ms for 4-year-old children, 1,500 to 800 ms for 5-year-old children, and 900 to 400 ms for adults.
Fig. 2 Selected animations from the instructions and block feedback. (A) In the instructions, participants were told that they were on a space mission and needed to fuel passing ships of a particular color. (B) During
the block breaks, participants received space-themed feedback about their progress on the space mission. Customized gauges reported the participants’ speed and accuracy for each block
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cues. However, validity effects for irrelevant cues were much larger in children (87.1 ms) than in adults (11.2 ms), t(82) = 3.66, p < .001.
Results RT trimming Occasional inattention (e.g., turning to ask the experimenter a question) led to outliers. To eliminate outliers, we excluded RTs greater than 5,000 ms for children (3.9 % of trials), and greater than 1,000 ms for adults (1.72 % of trials). We then also removed RTs below 200 ms or above 2.5 standard deviations from the individual participant’s mean RT (2.7 % of trials in children, and 2.0 % of trials in adults). Error trials and practice trials were also excluded from the RT analyses. Raw RT analysis We first performed a mixed-design three-way analysis of variance (ANOVA) on mean RTs (see Table 1) with the factors Age (adults vs. children), Cue Relevance (relevant vs. irrelevant), and Cue validity (valid vs. invalid). Children responded much more slowly (1,727 ms) than adults (542 ms), F(1, 82) = 418.82, p < .001, ηp2 = .836, in line with previous studies of RTs in young children (Kail, 1991; Kail & Ferrer, 2007). Consistent with the overall RT slowing factor of about 3, cue validity effects were three times larger for children (126 ms) than for adults (39 ms), F(1, 82) = 19.146, p < .001, ηp2 = .189. Both groups produced shorter RTs on valid trials (1,094 ms) than on invalid trials (1,176 ms), F(1, 82) = 69.038, p < .001, ηp2 = .457, suggesting that some cues captured attention. The 150-ms stimulus onset asynchrony between the cue and target displays, known to yield robust cue validity effects in adults, also appears to be appropriate for assessing capture in children (despite their overall cognitive slowing). Validity effects were larger for relevant cues (115 ms) than for irrelevant cues (49 ms), F(1, 82) = 11.631, p < .001, ηp2 = .124, indicating a goal-driven component to attention capture. The three-way interaction of cue relevance, cue validity, and age was not significant, F(1, 82) = 0.286, p > .10, ηp2 = .003. As is shown in Fig. 3A, both children and adults showed greater validity effects from relevant cues than from irrelevant Table 1 Mean response times (in milliseconds) and validity effects by age, cue relevance, and cue validity Adult
Invalid Valid Validity effect CCR
Children
Relevant
Irrelevant
Relevant
Irrelevant
573 507 66.7
550 539 11.2 83.2 %
1,791 1,627 163.8
1,789 1,701 87.6 46.5 %
CCR = contingent-capture ratio. Validity effects were calculated as invalid minus valid.
Normalized RTs Children responded approximately three times more slowly than adults, making direct comparisons of the validity effects on raw RTs between adults and children dubious. Accordingly, we normalized each participant’s RT (see Table 2) by dividing each participant’s mean RT in a given condition by their overall mean RT and then converting this proportion to a percentage. We then performed a mixeddesign two-way ANOVA on the resulting percent cue validity effects with the factors Age and Cue Relevance. Validity effects were greater for relevant cues (11.0 %) than for irrelevant cues (3.8 %), F(1, 82) = 40.726, p < .001, ηp2 = .332, again confirming a goal-driven component to capture (see Fig. 3B). More critically, the interaction of cue relevance and age was significant, F(1, 82) = 7.206, p < .01, ηp2 = .081. Preplanned t tests revealed that validity effects for relevant cues were not statistically different between children (9.7 %) and adults (12.2 %), t(82) = 1.19, p > .10. Validity effects for irrelevant cues, however, were nearly three times larger for children (5.5 %) than for adults (2.0 %), t(82) = 2.76, p < .007. Thus, even when cue validity effects are adjusted for relative cognitive slowing due to age, children still show much larger validity effects from irrelevant stimuli.
Contingent capture ratio (CCR) As an overall index of top-down control over capture, we computed the contingent-capture ratio (CCR) for each individual, using cue validity effects (CVE), as follows: individual irrelevant CVE 1− 100: group relevant CVE
The CCR is scaled as a percentage of the group cue validity effects, which corrects for group differences in cognitive speed. Thus, the CCR reflects overall top-down control over attention capture, unbiased by the overall validity effect size (which was much greater in children). A high CCR indicates strong top-down control (i.e., much more capture by relevant than by irrelevant cues). A low CCR indicates weak top-down control (i.e., roughly equal capture by relevant and irrelevant cues). As is shown in Fig. 4, the CCRs were much smaller for children (46.5 %) than for adults (83.2 %), t(82) = 2.67, p < .01, confirming that children have significantly less top-down control.
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Fig. 3 (A) Cue validity effects by age group and cue relevance. (B) Normalized cue validity effects by age group and cue relevance. Error bars represent between-subjects standard errors of the means
Irrelevant cue type
Discussion
We also performed a mixed-design two-way ANOVA on cue validity effects (see Table 3) with the factors Age (adults vs. children) and Irrelevant-Cue Type (color singleton vs. abrupt onset). Validity effects were not significantly different for onsets (50.6 ms) and color singletons (49.7 ms), F(1, 82) < 1, p > .10, ηp2 < .001. The interaction between irrelevant-cue type and age was also nonsignificant, F(1, 82) < 1, p > .10, ηp2 < .001.
Adults are generally adept at exerting top-down control to block distraction by irrelevant stimuli (e.g., Folk et al., 1992; Lien et al., 2010). It is unclear, however, when in the lifespan this top-down control over attention capture develops. In the modern age, a plethora of salient visual stimuli vie for children’s visual attention, such as highly luminous computer screens and brightly colored advertisements. A better understanding of attention capture in children would allow us to design more effective educational environments, both at home and in the classroom. To compare top-down control of attention in children and adults, we designed a precuing task with three key elements: We directly compared adults and children, we compared relevant and irrelevant salient stimuli, and we adjusted for
Error rates We performed the same ANOVA from the raw RT analysis on mean error rates (see Table 4). Error rates were higher in children (4.6 %) than in adults (1.5 %), F(1, 82) = 35.689, p < .001, ηp2 = .303. All other main effects and interactions were nonsignificant.
Table 2 Normalized response times (in milliseconds) and validity effects by age, cue relevance, and cue validity Adult
Invalid Valid Validity effect
Children
Relevant
Irrelevant
Relevant
Irrelevant
105.7 % 93.5 % 12.2 %
101.4 % 99.5 % 2.0 %
104.0 % 94.4 % 9.7 %
103.6 % 98.0 % 5.5 %
The normalized mean response time was calculated as a participant’s mean response time in a condition over the participant’s overall mean response time (multiplied by 100).
Fig. 4 Contingent-capture ratios (CCRs) plotted by age group. Error bars represent between-subjects standard errors of the means
Psychon Bull Rev Table 3 Mean response times (in milliseconds) and validity effects by age, irrelevant cue type, and cue validity Adult Singleton
Children Onset
Singleton
Onset
Invalid
548.8
553.3
1,785.1
1,795.0
Valid Validity effect
543.3 5.5
530.8 22.5
1,691.3 93.8
1,716.3 78.7
children’s overall slowing. Importantly, the precuing task was painstakingly modified to be child-friendly by creating an engaging, space-themed game. Consistent with a goal-driven component of attention capture, validity effects were much greater for relevant than for irrelevant cues, in both adults and children. Children, however, were more susceptible to distraction by irrelevant stimuli than were adults. The raw validity effects for irrelevant cues were much larger in children (87.6 ms) than in adults (11.2 ms). Even after normalizing RTs to account for children’s overall slowing, validity effects for irrelevant cues were still almost three times larger for children (5.5 %) than for adults (2.0 %). Similarly, contingent-capture ratios (an index of top-down control) were much smaller in children (46.5 %) than in adults (83.2 %). Overall, the story is clear: Young children (4–5 years of age) are indeed more susceptible to visual distraction than are adults. Attention capture across the lifespan In the present study, we demonstrated that top-down attentional control is under development in preschool-aged children (Mage = 4.2 years). This development appears to continue throughout early childhood. Greenaway and Plaisted (2005) had older children (Mage = 11.5 years) perform a precuing paradigm roughly similar to the one in the present study. In their color target condition (similar to the present experiment), the CCR was approximately 50 % (estimated from their figures), close to that obtained here with much younger children (46.5 %). Paired with the results from the present study, this suggests that top-down attentional control develops after 11.5 years of age. This lack of top-down control over visual attention would manifest in broad deficits in attentional Table 4 Error rates by age, cue relevance, and cue validity Adult
Invalid Valid Validity effect
Children
Relevant
Irrelevant
Relevant
Irrelevant
2.0 % 0.8 % 1.1 %
1.4 % 1.9 % –0.5 %
4.4 % 4.8 % –0.4 %
4.3 % 5.1 % –0.8 %
filtering (Gaspelin, Ruthruff, & Jung, 2014) and visual search (Wolfe, 1994), including classroom contexts. Note, however, that capture by salience also has positive consequences. It allows visual attention to rapidly orient to warning signals and other salient stimuli that, although not relevant to the immediate goal, are potentially important. Because children frequently explore novel visual environments with limited prior knowledge, a more stimulus-driven strategy may often be adaptive. Once top-down control over spatial attention has developed, it appears to remain largely intact in later life. For example, some research suggests that elderly adults (e.g., over 60 years of age) continue to exert top-down control over visual attention to avoid attention capture by salient stimuli. Lien, Gemperle, and Ruthruff (2011) had participants perform in a precuing paradigm resembling ours. Older adults showed a CCR of 83.7 %, similar to that of the college-age adults in the present study (83.2 %), demonstrating preserved top-down control over spatial attention.
Relation to executive control Previous research has suggested a tight coupling of the ability to resist visual distraction and more general executive-control abilities. For example, in several attention-capture tasks, Fukuda and Vogel (2009) found that working memory span was highly correlated with the ability to avoid interference from salient distractor items. Executive control develops substantially from childhood (4–9 years old) to young adulthood (18–30 years old), as assessed by the task-switching paradigm (Cepeda et al., 2001) or the stop-signal paradigm (Williams et al., 1999). This development of executive control seems to be related to the development of the frontal cortex and the anterior cingulate cortex (Atkinson & Braddick, 2012).
Conclusions In the present study, we assessed the abilities of children and adults to exert top-down control to block attention capture by salient visual stimuli. To this end, we modified a precuing task to engage young children (a space mission). Adults showed the standard contingent-capture effect—large capture effects for relevant cues, but negligible capture effects for irrelevant cues. Although children showed some top-down control over visual attention (roughly 50 %), these results confirm the popular assumption that children are much more vulnerable to distraction by irrelevant stimuli than are adults. This finding justifies attempts to protect children against distraction (e.g., in educational contexts).
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References Atkinson, J., & Braddick, O. (2012). Visual attention in the first years: Typical development and developmental disorders. Developmental Medicine and Child Neurology, 54, 589–595. Bacon, W. F., & Egeth, H. E. (1994). Overriding stimulus-driven attentional capture. Perception & Psychophysics, 55, 485–496. doi:10. 3758/BF03205306 Belopolsky, A. V., Schreij, D., & Theeuwes, J. (2010). What is top-down about contingent capture? Attention, Perception, & Psychophysics, 72, 326–341. doi:10.3758/APP.72.2.326 Bernstein, J. (2012, September 3). Liking the child you love. Psychology Today. Retrieved from www.psychologytoday.com/blog/liking-thechild-you-love/201209/helping-children-and-teens-distractibility Cepeda, N. J., Kramer, A. F., & Gonzalez de Sather, J. C. M. (2001). Changes in executive control across the life span: Examination of task-switching performance. Developmental Psychology, 37, 715– 730. Deltour, L., Barathon, M., Quaglino, V., Vernier, M.-P., Despretz, P., Boucart, M., & Berquin, P. (2007). Children with benign epilepsy with centrotemporal spikes (BECTS) show impaired attentional control: Evidence from an attentional capture paradigm. Epileptic Disorders, 9, 32–38. Fisher, A. V., Godwin, K. E., & Seltman, H. (2014). Visual environment, attention allocation, and learning in young children: When too much of a good thing may be bad. Psychological Science, 25, 1362–1370. doi:10.1177/0956797614533801 Folk, C. L., Leber, A. B., & Egeth, H. E. (2002). Made you blink! Contingent attentional capture produces a spatial blink. Perception & Psychophysics, 64, 741–753. doi: 10.3758/ BF03194741 Folk, C. L., Remington, R. W., & Johnston, J. C. (1992). Involuntary covert orienting is contingent on attentional control settings. Journal of Experimental Psychology: Human Perception and Performance, 18, 1030–1044. doi:10.1037/0096-1523.18.4.1030 Fukuda, K., & Vogel, E. K. (2009). Human variation in overriding attentional capture. Journal of Neuroscience, 29, 8726–8733. doi: 10.1523/JNEUROSCI.2145-09.2009 Gaspelin, N., Ruthruff, E., & Jung, K. (2014). Slippage theory and the flanker paradigm: An early-selection account of selective attention failures. Journal of Experimental Psychology: Human Perception and Performance, 40, 1257–1273. doi:10.1037/a0036179 Gaspelin, N., Ruthruff, E., Lien, M.-C., & Jung, K. (2012). Breaking through the attentional window: Capture by abrupt onsets versus color singletons. Attention, Perception, & Psychophysics, 74, 1461– 1474. doi:10.3758/s13414-012-0343-7
Greenaway, R., & Plaisted, K. (2005). Top-down attentional modulation in autistic spectrum disorders is stimulus-specific. Psychological Science, 16, 987–994. doi:10.1111/j.1467-9280.2005.01648.x Horowitz, T. S., Wolfe, J. M., Alvarez, G. A., Cohen, M. A., & Kuzmova, Y. I. (2009). The speed of free will. Quarterly Journal of Experimental Psychology, 62, 2262–2288. doi:10.1080/ 17470210902732155 Kail, R. V. (1991). Developmental change in speed of processing during childhood and adolescence. Psychological Bulletin, 109, 490–501. Kail, R. V., & Ferrer, E. (2007). Processing speed in childhood and adolescence: Longitudinal models for examining developmental change. Child Development, 78, 1760–1770. Leclercq, V., & Siéroff, E. (2013). Development of endogenous orienting of attention in school-age children. Child Neuropsychology, 19, 400–419. Lien, M.-C., Gemperle, A., & Ruthruff, E. (2011). Aging and involuntary attention capture: Electrophysiological evidence for preserved attentional control with advanced age. Psychology and Aging, 26, 188– 202. doi:10.1037/a0021073 Lien, M.-C., Ruthruff, E., Goodin, Z., & Remington, R. W. (2008). Contingent attentional capture by top-down control settings: Converging evidence from event-related potentials. Journal of Experimental Psychology: Human Perception and Performance, 34, 509–530. doi:10.1037/0096-1523.34.3.509 Lien, M.-C., Ruthruff, E., & Johnston, J. C. (2010). Attentional capture with rapidly changing attentional control settings. Journal of Experimental Psychology: Human Perception and Performance, 36, 1–16. doi:10.1037/a0015875 Mason, D. J., Humphreys, G. W., & Kent, L. (2004). Visual search, singleton capture, and the control of attentional set in ADHD. Cognitive Neuropsychology, 21, 661–687. Oh-Uchi, A., Kawahara, J., & Sugano, L. (2010). Attentional capture and meta-attentional judgment: A study of young children, parents, and university students. Psychologia, 53, 114–124. Theeuwes, J. (2010). Top-down and bottom-up control of visual selection. Acta Psychologica, 135, 77–99. doi:10.1016/j.actpsy.2010.02. 006 Waters, A. M., Lipp, O. V., & Spence, S. H. (2004). Attentional bias toward fear-related stimuli: An investigation with nonselected children and adults and children with anxiety disorders. Journal of Experimental Child Psychology, 89, 320–337. Williams, B. R., Ponesse, J. S., Schachar, R. J., Logan, G. D., & Tannock, R. (1999). Development of inhibitory control across the life span. Developmental Psychology, 35, 205–213. Wolfe, J. M. (1994). Guided Search 2.0: A revised model of visual search. Psychonomic Bulletin & Review, 1, 202–238. doi:10.3758/ BF03200774
BRIEF REPORT
Susceptible to distraction: Children lack top-down control over spatial attention capture Nicholas Gaspelin & Tessa Margett-Jordan & Eric Ruthruff
# Psychonomic Society, Inc. 2014
Abstract Considerable evidence has indicated that adults can exert top-down control to avoid distraction by salient-butirrelevant stimuli. However, relatively little research has explored how this ability develops across the lifespan. In the present study, we therefore assessed how well children can control the capture of spatial attention. Children (Mage = 4.2 years) and adults (Mage = 21.5 years) searched for target “spaceships” of a specific color while trying to ignore salient precues that either matched or mismatched the target spaceship color. The results demonstrated that children are, in fact, more vulnerable to capture by irrelevant stimuli than are adults, even after accounting for children’s overall cognitive slowing.
Keywords Attention capture . Visual search . Spatial attention . Children
Attention capture is a daily cognitive phenomenon, rapidly drawing processing resources toward visual stimuli. Adults are not immune to capture, but they can exert top-down control in order to minimize distraction by task-irrelevant salient stimuli. It is unclear, however, when in the lifespan this top-down control over spatial attention develops. It is often assumed that children are vulnerable to visual distraction, yet little empirical research has directly tested this assumption. Before describing how we addressed this issue in the present study, we will first briefly review the attention capture literature.
N. Gaspelin (*) : T. Margett-Jordan : E. Ruthruff Department of Psychology, 1 University of New Mexico, MSC03 2220, Albuquerque, NM 87131-1161, USA e-mail: [email protected]
Top-down control over attention capture in adults Because visual environments are complex, our visual systems select only a small subset of the available information for semantic processing. Spatial attention allows us to covertly shift processing resources across a visual scene, independently of eye movements. Often these shifts are triggered involuntarily by the appearance of a salient stimulus, a phenomenon known as involuntary attention capture. Because involuntary capture is particularly fast (e.g., 35–100 ms; Horowitz, Wolfe, Alvarez, Cohen, & Kuzmova, 2009), it can rapidly draw attention toward important objects (e.g., a yellow “wet floor” sign), as well as toward completely irrelevant ones (e.g., a fidgeting neighbor in class). Despite the debate regarding the details of attention capture, there is strong evidence that adults are captured much more strongly by task-relevant than by task-irrelevant stimuli (Folk, Remington, & Johnston, 1992; but see Theeuwes, 2010). In a seminal study of capture, Folk et al. (1992) used a precuing paradigm: Participants searched displays for a target defined by a simple feature (color or abrupt onset) and reported its identity (X vs. =). The search display was preceded by a salient cue placed randomly at a possible target location. If captured by the precue, participants should respond more quickly to targets at the cued location (valid trials) than to targets located elsewhere (invalid trials), which is called the cue validity effect. Importantly, validity effects were present only for cues that matched the target-finding feature. For example, when the target was defined by red, red cues produced validity effects but white onset cues (i.e., flashing dots) did not, and vice versa. Folk et al. (1992) concluded that attention capture is contingent on a match with the viewer’s attentional set (i.e., it is goal-driven). Much subsequent research has supported the contingentcapture account (e.g., Folk, Leber, & Egeth, 2002; Gaspelin, Ruthruff, Lien, & Jung, 2012; Lien, Ruthruff, Goodin, &
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Remington, 2008; Lien, Ruthruff, & Johnston, 2010). As an example of adults’ extraordinary ability to avoid capture by salient stimuli, Lien et al. (2010) used a precuing paradigm, but changed the upcoming target-finding feature before every trial, indicated by a prompt (e.g., an “R” to indicate red, for 1,200 ms). Surprisingly, trial-to-trial fluctuations in attentional set did not increase vulnerability to capture by task-irrelevant stimuli; indeed, adult participants avoided capture by a color that they had searched for only a few seconds before (but see also Belopolsky, Schreij, & Theeuwes, 2010). It is unclear when in the lifespan this extraordinary topdown control over spatial attention develops. It appears to be widely believed that children are particularly vulnerable to attention capture by irrelevant stimuli. For example, a recent Psychology Today article discussed why children are vulnerable to distraction and how such distraction can be managed (Bernstein, 2012). Similarly, Fisher, Godwin, and Seltman (2014) had children (Mage = 5.4 years) learn information for later recall in either highly decorated or sparsely decorated classroom environments. Children in highly-decorated classrooms were ultimately unable to learn as efficiently as children in sparsely-decorated classrooms, which these researchers took as evidence of distractibility in children. Despite the aforementioned claims, little formal research has actually investigated the basic science of attention capture in children. Although some research has suggested that executive control develops throughout early childhood (Cepeda, Kramer, & Gonzalez de Sather, 2001; Williams, Ponesse, Schachar, Logan, & Tannock, 1999), it is unclear whether this empirical generalization applies specifically to the control of spatial attention, which has high practical importance.
Previous research To determine whether children lack top-down control over spatial attention relative to adults, a study must meet the following criteria. First, a sample of healthy children and adults must be directly compared. Second, given children’s marked overall cognitive slowing (Kail, 1991; Kail & Ferrer, 2007), one must determine whether any age effects reflect mere generalized slowing or a specific deficit in top-down control over spatial attention. A related third point is that the study should specifically compare the relative sizes of the capture effects produced by task-irrelevant and task-relevant stimuli (e.g., as in Folk et al., 1992). Task-relevant stimuli provide a very useful measure of “maximum” capture, so that one can meaningfully interpret the magnitude of capture by task-irrelevant stimuli. Several previous studies have measured attention capture in children (Deltour et al., 2007; Greenaway & Plaisted, 2005; Leclercq & Siéroff, 2013; Mason, Humphreys, & Kent, 2004; Oh-Uchi, Kawahara, & Sugano, 2010; Waters, Lipp, &
Spence, 2004). None of these studies, however, met all of the aforementioned criteria, likely because they were intended to answer somewhat different research questions. A few studies, however, met one or two of the above criteria. Interestingly, these studies suggested that children are not more susceptible to attention capture than adults. Oh-Uchi et al. (2010) compared attention capture in children (Mage = 6.1 years) and adults (Mage = 20.9 years). Participants searched displays of horizontal green fish for a lone vertical green fish and reported its orientation (up vs. down). On half of the trials, one distractor fish differed in color (red) from the green fish. Both age groups were slowed by the presence of the red color-singleton fish (adults by 54.7 ms, children by 200 ms). The researchers concluded that both children and adults are equally susceptible to capture by salient stimuli. However, this study failed to meet the second aforementioned criterion: They did not correct for overall cognitive slowing. Furthermore, the additional-singleton paradigm used in this study made it impossible to include relevant color cues, violating the third criterion. For example, children might have shown even larger interference effects for relevant stimuli, demonstrating a large degree of top-down control over attention capture. Also, it is unclear whether one should classify the color singletons in this study as relevant or irrelevant, because it is unclear whether participants were specifically looking for the unique target shape (vertical fish) or merely looking for any unique object (cf. Bacon & Egeth, 1994). Greenaway and Plaisted (2005, Exp. 1) used a precuing paradigm to assess attention capture in typically developing and in autistic children (Mage = 11.5 years). Complying with the third criterion above, they assessed capture by both irrelevant and relevant stimuli. For typically developing children, validity effects were greater for relevant than for irrelevant cues, indicating some degree of top-down control. Because the study had no adult participants for comparison, however, it remains unclear whether typically developing children are more vulnerable to capture than adults. Their stimulus timing also deviated from those in previous studies with adults (e.g., a longer stimulus onset asynchrony between the cue and search array), complicating comparisons. Finally, the authors did not take into account overall cognitive slowing in children.
The present study To summarize, no previous research has satisfactorily compared top-down control of attention capture in children and adults. Therefore, we designed a study that would satisfy the aforementioned criteria. To establish the full developmental sequence for cognitive processes, one should start with the youngest age of children that can complete testing. Children younger than 4 years old would be too cognitively and
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motorically immature to provide meaningful data on our reaction-time task (for a review, see Kail, 1991). We therefore had preschool children (Mage = 4.2 years) and university students (Mage = 21.5 years) perform in a precuing paradigm. The participants searched target displays for a spaceship of a specific color. This target display was preceded by a nonpredictive precue: a relevant color singleton (target color), an irrelevant color singleton (nontarget color), or an irrelevant abrupt onset. Adults should show the typical contingentcapture effect—large validity effects for relevant cues, but small nonsignificant validity effects for irrelevant cues (as in Folk et al., 1992). The critical question was whether young children would show the same goal-driven pattern or would instead show large validity effects from irrelevant cues, after adjusting for overall cognitive slowing.
Method Participants The participants had normal color vision (as assessed by an Ishihara color vision test) and self- or parent-reported normal or corrected-to-normal visual acuity. Children A group of 44 children (4–5 years old) from two local preschools participated. Four of the participants did not complete the experiment, and one was excluded from the final analyses due to an abnormally high error rate (2.5 SDs above the group mean of 5.1 %). The remaining 39 child participants (21 male, 18 female) had a mean age of 4.2 years. Adults A group of 48 undergraduates (18–55 years old) from the University of New Mexico participated for course credit. Three of the participants were excluded due to abnormally high error rates (2.5 SDs above the adult group mean of 1.9 %). The remaining 45 adults (35 female, ten male) had a mean age of 21.5 years. Materials and procedure Apparatus A laptop computer displayed stimuli on a 14-in. LCD monitor using software created in the C programming language using Allegro gaming libraries (http://alleg. sourceforge.net/ ). Stimuli Each search display contained one spaceship (2.9° in width and 2.0° in height, based on an average viewing distance of 56 cm) in one of four different colors: green (RGB values of 0, 151, 0), red (255, 0, 0), blue (0, 128, 255), and white (255, 255, 255). The placeholders were gray (125, 125, 125), unfilled boxes (3.9° in width and height). All of the colors (except white) were designed to be roughly
equiluminant against a black background. Eight rectangular boxes formed an imaginary circle (18° in diameter), with one additional fixation box in the middle. Only four locations could contain spaceships (top, bottom, left, or right). In the cue frame, color-singleton cues were created by thickening one placeholder box and coloring it (red, blue, or green). The abrupt-onset cues were four white dots (0.8° in diameter) appearing around one placeholder (forming an imaginary diamond 5.5° in height and width). See Fig. 1 for stimuli in each condition. Design Participants were randomly assigned to a target color (red, blue, or green), with the restriction that each color be used equally often across participants. Target identity (left vs. right) and target location were randomly chosen, with the restriction that each identity occurred equally often. Distractor colors and identities were chosen randomly, with the restriction that each display contained one ship of each color and that equal numbers of ships faced in each direction. Each cue type (red, blue, green, or onset) was equally probable (25 %) and chosen randomly. Cue location (always one of the four possible target locations) was chosen randomly, and therefore was nonpredictive of target location (25 % valid, 75 % invalid). The experiment began with a practice block of 32 trials, followed by eight regular blocks of 32 trials. Procedure Both children and adults received instructions with audio and animations designed to make the task engaging (see Fig. 2A). An astronaut character explained that the participant was helping with a space mission to cross the solar system. Target-colored ships needed fuel. To assist in fueling, the participant was to quickly report which way the target-color ship faced by pressing a key labeled with a left or a right arrow (actual keys: “Z” and “M”). Participants were instructed to ignore the precue. An adult experimenter sat with each child participant throughout the experimental session, offering instructions and motivation. Each trial began with a presentation of the nine placeholders for 1,000 ms. Then, the fixation placeholder disappeared for 100 ms and reappeared for 500 ms to denote trial onset. Next, the precue display appeared for 100 ms, followed by the placeholder frame for another 50 ms. The search array then appeared until response. Extensive piloting revealed that these cue and search display durations produced cue validity effects in both adults and children. Participants received immediate feedback on accuracy. If a response was correct, a rewarding chime sounded and the search display disappeared. If incorrect, a low buzzer sounded and the target-colored ship shrank until it disappeared. After each block, participants were told that they had reached a new planet (see Fig. 2B) and received block
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Fig. 1 Example trial sequence from the red target condition for each of the three possible cue types (all invalid in the examples shown). In the grayscale figures, the red target is portrayed as a gray ship amongst white
ships (actual colors: white, blue, and green), and color cues are shown as dashed boxes (irrelevant [blue/green] and relevant [red]). To download color figures, please visit www.unm.edu/~ruthruff/DevColorFigures.pdf
performance feedback in the form of two gauges, one for speed and one for accuracy (with three labels: “good,” “great,” or “awesome”). The gauge needle slowly rose until it reached the achieved position. The needle never dropped below “good.” The accuracy gauge’s range was identical for children and adults (lower limit 85 % and upper limit 100 %).
However, because young children are much slower than adults (Kail, 1991), we used different response time (RT) ranges for the different age groups, on the basis of pilot studies. The RT gauges ranged from 2,000 to 1,300 ms for 4-year-old children, 1,500 to 800 ms for 5-year-old children, and 900 to 400 ms for adults.
Fig. 2 Selected animations from the instructions and block feedback. (A) In the instructions, participants were told that they were on a space mission and needed to fuel passing ships of a particular color. (B) During
the block breaks, participants received space-themed feedback about their progress on the space mission. Customized gauges reported the participants’ speed and accuracy for each block
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cues. However, validity effects for irrelevant cues were much larger in children (87.1 ms) than in adults (11.2 ms), t(82) = 3.66, p < .001.
Results RT trimming Occasional inattention (e.g., turning to ask the experimenter a question) led to outliers. To eliminate outliers, we excluded RTs greater than 5,000 ms for children (3.9 % of trials), and greater than 1,000 ms for adults (1.72 % of trials). We then also removed RTs below 200 ms or above 2.5 standard deviations from the individual participant’s mean RT (2.7 % of trials in children, and 2.0 % of trials in adults). Error trials and practice trials were also excluded from the RT analyses. Raw RT analysis We first performed a mixed-design three-way analysis of variance (ANOVA) on mean RTs (see Table 1) with the factors Age (adults vs. children), Cue Relevance (relevant vs. irrelevant), and Cue validity (valid vs. invalid). Children responded much more slowly (1,727 ms) than adults (542 ms), F(1, 82) = 418.82, p < .001, ηp2 = .836, in line with previous studies of RTs in young children (Kail, 1991; Kail & Ferrer, 2007). Consistent with the overall RT slowing factor of about 3, cue validity effects were three times larger for children (126 ms) than for adults (39 ms), F(1, 82) = 19.146, p < .001, ηp2 = .189. Both groups produced shorter RTs on valid trials (1,094 ms) than on invalid trials (1,176 ms), F(1, 82) = 69.038, p < .001, ηp2 = .457, suggesting that some cues captured attention. The 150-ms stimulus onset asynchrony between the cue and target displays, known to yield robust cue validity effects in adults, also appears to be appropriate for assessing capture in children (despite their overall cognitive slowing). Validity effects were larger for relevant cues (115 ms) than for irrelevant cues (49 ms), F(1, 82) = 11.631, p < .001, ηp2 = .124, indicating a goal-driven component to attention capture. The three-way interaction of cue relevance, cue validity, and age was not significant, F(1, 82) = 0.286, p > .10, ηp2 = .003. As is shown in Fig. 3A, both children and adults showed greater validity effects from relevant cues than from irrelevant Table 1 Mean response times (in milliseconds) and validity effects by age, cue relevance, and cue validity Adult
Invalid Valid Validity effect CCR
Children
Relevant
Irrelevant
Relevant
Irrelevant
573 507 66.7
550 539 11.2 83.2 %
1,791 1,627 163.8
1,789 1,701 87.6 46.5 %
CCR = contingent-capture ratio. Validity effects were calculated as invalid minus valid.
Normalized RTs Children responded approximately three times more slowly than adults, making direct comparisons of the validity effects on raw RTs between adults and children dubious. Accordingly, we normalized each participant’s RT (see Table 2) by dividing each participant’s mean RT in a given condition by their overall mean RT and then converting this proportion to a percentage. We then performed a mixeddesign two-way ANOVA on the resulting percent cue validity effects with the factors Age and Cue Relevance. Validity effects were greater for relevant cues (11.0 %) than for irrelevant cues (3.8 %), F(1, 82) = 40.726, p < .001, ηp2 = .332, again confirming a goal-driven component to capture (see Fig. 3B). More critically, the interaction of cue relevance and age was significant, F(1, 82) = 7.206, p < .01, ηp2 = .081. Preplanned t tests revealed that validity effects for relevant cues were not statistically different between children (9.7 %) and adults (12.2 %), t(82) = 1.19, p > .10. Validity effects for irrelevant cues, however, were nearly three times larger for children (5.5 %) than for adults (2.0 %), t(82) = 2.76, p < .007. Thus, even when cue validity effects are adjusted for relative cognitive slowing due to age, children still show much larger validity effects from irrelevant stimuli.
Contingent capture ratio (CCR) As an overall index of top-down control over capture, we computed the contingent-capture ratio (CCR) for each individual, using cue validity effects (CVE), as follows: individual irrelevant CVE 1− 100: group relevant CVE
The CCR is scaled as a percentage of the group cue validity effects, which corrects for group differences in cognitive speed. Thus, the CCR reflects overall top-down control over attention capture, unbiased by the overall validity effect size (which was much greater in children). A high CCR indicates strong top-down control (i.e., much more capture by relevant than by irrelevant cues). A low CCR indicates weak top-down control (i.e., roughly equal capture by relevant and irrelevant cues). As is shown in Fig. 4, the CCRs were much smaller for children (46.5 %) than for adults (83.2 %), t(82) = 2.67, p < .01, confirming that children have significantly less top-down control.
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Fig. 3 (A) Cue validity effects by age group and cue relevance. (B) Normalized cue validity effects by age group and cue relevance. Error bars represent between-subjects standard errors of the means
Irrelevant cue type
Discussion
We also performed a mixed-design two-way ANOVA on cue validity effects (see Table 3) with the factors Age (adults vs. children) and Irrelevant-Cue Type (color singleton vs. abrupt onset). Validity effects were not significantly different for onsets (50.6 ms) and color singletons (49.7 ms), F(1, 82) < 1, p > .10, ηp2 < .001. The interaction between irrelevant-cue type and age was also nonsignificant, F(1, 82) < 1, p > .10, ηp2 < .001.
Adults are generally adept at exerting top-down control to block distraction by irrelevant stimuli (e.g., Folk et al., 1992; Lien et al., 2010). It is unclear, however, when in the lifespan this top-down control over attention capture develops. In the modern age, a plethora of salient visual stimuli vie for children’s visual attention, such as highly luminous computer screens and brightly colored advertisements. A better understanding of attention capture in children would allow us to design more effective educational environments, both at home and in the classroom. To compare top-down control of attention in children and adults, we designed a precuing task with three key elements: We directly compared adults and children, we compared relevant and irrelevant salient stimuli, and we adjusted for
Error rates We performed the same ANOVA from the raw RT analysis on mean error rates (see Table 4). Error rates were higher in children (4.6 %) than in adults (1.5 %), F(1, 82) = 35.689, p < .001, ηp2 = .303. All other main effects and interactions were nonsignificant.
Table 2 Normalized response times (in milliseconds) and validity effects by age, cue relevance, and cue validity Adult
Invalid Valid Validity effect
Children
Relevant
Irrelevant
Relevant
Irrelevant
105.7 % 93.5 % 12.2 %
101.4 % 99.5 % 2.0 %
104.0 % 94.4 % 9.7 %
103.6 % 98.0 % 5.5 %
The normalized mean response time was calculated as a participant’s mean response time in a condition over the participant’s overall mean response time (multiplied by 100).
Fig. 4 Contingent-capture ratios (CCRs) plotted by age group. Error bars represent between-subjects standard errors of the means
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Children Onset
Singleton
Onset
Invalid
548.8
553.3
1,785.1
1,795.0
Valid Validity effect
543.3 5.5
530.8 22.5
1,691.3 93.8
1,716.3 78.7
children’s overall slowing. Importantly, the precuing task was painstakingly modified to be child-friendly by creating an engaging, space-themed game. Consistent with a goal-driven component of attention capture, validity effects were much greater for relevant than for irrelevant cues, in both adults and children. Children, however, were more susceptible to distraction by irrelevant stimuli than were adults. The raw validity effects for irrelevant cues were much larger in children (87.6 ms) than in adults (11.2 ms). Even after normalizing RTs to account for children’s overall slowing, validity effects for irrelevant cues were still almost three times larger for children (5.5 %) than for adults (2.0 %). Similarly, contingent-capture ratios (an index of top-down control) were much smaller in children (46.5 %) than in adults (83.2 %). Overall, the story is clear: Young children (4–5 years of age) are indeed more susceptible to visual distraction than are adults. Attention capture across the lifespan In the present study, we demonstrated that top-down attentional control is under development in preschool-aged children (Mage = 4.2 years). This development appears to continue throughout early childhood. Greenaway and Plaisted (2005) had older children (Mage = 11.5 years) perform a precuing paradigm roughly similar to the one in the present study. In their color target condition (similar to the present experiment), the CCR was approximately 50 % (estimated from their figures), close to that obtained here with much younger children (46.5 %). Paired with the results from the present study, this suggests that top-down attentional control develops after 11.5 years of age. This lack of top-down control over visual attention would manifest in broad deficits in attentional Table 4 Error rates by age, cue relevance, and cue validity Adult
Invalid Valid Validity effect
Children
Relevant
Irrelevant
Relevant
Irrelevant
2.0 % 0.8 % 1.1 %
1.4 % 1.9 % –0.5 %
4.4 % 4.8 % –0.4 %
4.3 % 5.1 % –0.8 %
filtering (Gaspelin, Ruthruff, & Jung, 2014) and visual search (Wolfe, 1994), including classroom contexts. Note, however, that capture by salience also has positive consequences. It allows visual attention to rapidly orient to warning signals and other salient stimuli that, although not relevant to the immediate goal, are potentially important. Because children frequently explore novel visual environments with limited prior knowledge, a more stimulus-driven strategy may often be adaptive. Once top-down control over spatial attention has developed, it appears to remain largely intact in later life. For example, some research suggests that elderly adults (e.g., over 60 years of age) continue to exert top-down control over visual attention to avoid attention capture by salient stimuli. Lien, Gemperle, and Ruthruff (2011) had participants perform in a precuing paradigm resembling ours. Older adults showed a CCR of 83.7 %, similar to that of the college-age adults in the present study (83.2 %), demonstrating preserved top-down control over spatial attention.
Relation to executive control Previous research has suggested a tight coupling of the ability to resist visual distraction and more general executive-control abilities. For example, in several attention-capture tasks, Fukuda and Vogel (2009) found that working memory span was highly correlated with the ability to avoid interference from salient distractor items. Executive control develops substantially from childhood (4–9 years old) to young adulthood (18–30 years old), as assessed by the task-switching paradigm (Cepeda et al., 2001) or the stop-signal paradigm (Williams et al., 1999). This development of executive control seems to be related to the development of the frontal cortex and the anterior cingulate cortex (Atkinson & Braddick, 2012).
Conclusions In the present study, we assessed the abilities of children and adults to exert top-down control to block attention capture by salient visual stimuli. To this end, we modified a precuing task to engage young children (a space mission). Adults showed the standard contingent-capture effect—large capture effects for relevant cues, but negligible capture effects for irrelevant cues. Although children showed some top-down control over visual attention (roughly 50 %), these results confirm the popular assumption that children are much more vulnerable to distraction by irrelevant stimuli than are adults. This finding justifies attempts to protect children against distraction (e.g., in educational contexts).
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References Atkinson, J., & Braddick, O. (2012). Visual attention in the first years: Typical development and developmental disorders. Developmental Medicine and Child Neurology, 54, 589–595. Bacon, W. F., & Egeth, H. E. (1994). Overriding stimulus-driven attentional capture. Perception & Psychophysics, 55, 485–496. doi:10. 3758/BF03205306 Belopolsky, A. V., Schreij, D., & Theeuwes, J. (2010). What is top-down about contingent capture? Attention, Perception, & Psychophysics, 72, 326–341. doi:10.3758/APP.72.2.326 Bernstein, J. (2012, September 3). Liking the child you love. Psychology Today. Retrieved from www.psychologytoday.com/blog/liking-thechild-you-love/201209/helping-children-and-teens-distractibility Cepeda, N. J., Kramer, A. F., & Gonzalez de Sather, J. C. M. (2001). Changes in executive control across the life span: Examination of task-switching performance. Developmental Psychology, 37, 715– 730. Deltour, L., Barathon, M., Quaglino, V., Vernier, M.-P., Despretz, P., Boucart, M., & Berquin, P. (2007). Children with benign epilepsy with centrotemporal spikes (BECTS) show impaired attentional control: Evidence from an attentional capture paradigm. Epileptic Disorders, 9, 32–38. Fisher, A. V., Godwin, K. E., & Seltman, H. (2014). Visual environment, attention allocation, and learning in young children: When too much of a good thing may be bad. Psychological Science, 25, 1362–1370. doi:10.1177/0956797614533801 Folk, C. L., Leber, A. B., & Egeth, H. E. (2002). Made you blink! Contingent attentional capture produces a spatial blink. Perception & Psychophysics, 64, 741–753. doi: 10.3758/ BF03194741 Folk, C. L., Remington, R. W., & Johnston, J. C. (1992). Involuntary covert orienting is contingent on attentional control settings. Journal of Experimental Psychology: Human Perception and Performance, 18, 1030–1044. doi:10.1037/0096-1523.18.4.1030 Fukuda, K., & Vogel, E. K. (2009). Human variation in overriding attentional capture. Journal of Neuroscience, 29, 8726–8733. doi: 10.1523/JNEUROSCI.2145-09.2009 Gaspelin, N., Ruthruff, E., & Jung, K. (2014). Slippage theory and the flanker paradigm: An early-selection account of selective attention failures. Journal of Experimental Psychology: Human Perception and Performance, 40, 1257–1273. doi:10.1037/a0036179 Gaspelin, N., Ruthruff, E., Lien, M.-C., & Jung, K. (2012). Breaking through the attentional window: Capture by abrupt onsets versus color singletons. Attention, Perception, & Psychophysics, 74, 1461– 1474. doi:10.3758/s13414-012-0343-7
Greenaway, R., & Plaisted, K. (2005). Top-down attentional modulation in autistic spectrum disorders is stimulus-specific. Psychological Science, 16, 987–994. doi:10.1111/j.1467-9280.2005.01648.x Horowitz, T. S., Wolfe, J. M., Alvarez, G. A., Cohen, M. A., & Kuzmova, Y. I. (2009). The speed of free will. Quarterly Journal of Experimental Psychology, 62, 2262–2288. doi:10.1080/ 17470210902732155 Kail, R. V. (1991). Developmental change in speed of processing during childhood and adolescence. Psychological Bulletin, 109, 490–501. Kail, R. V., & Ferrer, E. (2007). Processing speed in childhood and adolescence: Longitudinal models for examining developmental change. Child Development, 78, 1760–1770. Leclercq, V., & Siéroff, E. (2013). Development of endogenous orienting of attention in school-age children. Child Neuropsychology, 19, 400–419. Lien, M.-C., Gemperle, A., & Ruthruff, E. (2011). Aging and involuntary attention capture: Electrophysiological evidence for preserved attentional control with advanced age. Psychology and Aging, 26, 188– 202. doi:10.1037/a0021073 Lien, M.-C., Ruthruff, E., Goodin, Z., & Remington, R. W. (2008). Contingent attentional capture by top-down control settings: Converging evidence from event-related potentials. Journal of Experimental Psychology: Human Perception and Performance, 34, 509–530. doi:10.1037/0096-1523.34.3.509 Lien, M.-C., Ruthruff, E., & Johnston, J. C. (2010). Attentional capture with rapidly changing attentional control settings. Journal of Experimental Psychology: Human Perception and Performance, 36, 1–16. doi:10.1037/a0015875 Mason, D. J., Humphreys, G. W., & Kent, L. (2004). Visual search, singleton capture, and the control of attentional set in ADHD. Cognitive Neuropsychology, 21, 661–687. Oh-Uchi, A., Kawahara, J., & Sugano, L. (2010). Attentional capture and meta-attentional judgment: A study of young children, parents, and university students. Psychologia, 53, 114–124. Theeuwes, J. (2010). Top-down and bottom-up control of visual selection. Acta Psychologica, 135, 77–99. doi:10.1016/j.actpsy.2010.02. 006 Waters, A. M., Lipp, O. V., & Spence, S. H. (2004). Attentional bias toward fear-related stimuli: An investigation with nonselected children and adults and children with anxiety disorders. Journal of Experimental Child Psychology, 89, 320–337. Williams, B. R., Ponesse, J. S., Schachar, R. J., Logan, G. D., & Tannock, R. (1999). Development of inhibitory control across the life span. Developmental Psychology, 35, 205–213. Wolfe, J. M. (1994). Guided Search 2.0: A revised model of visual search. Psychonomic Bulletin & Review, 1, 202–238. doi:10.3758/ BF03200774
