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Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Trajectories of attention: the interplay between the attentive observer and the visual world
  5. How does attention go awry? Studying mechanisms of attention development through its disorders
  6. What is attention for? The interplay between attention, memory and learning over development
  7. Conclusions and future directions
  8. References

Attentional processes play a crucial role in prioritizing information for further processing and they therefore sit at the interface between internal goals and the challenges presented by the environment. How does attentional control interact with the changing constraints imposed by the developing cognitive system? Emerging work in this area has employed a range of complementary techniques, from increasingly refined neurocognitive measures in typically developing individuals, to the investigation of risk or protective factors influencing attention trajectories in developmental disorders. A growing corpus of data suggests that, while attentional biases for specific input characteristics (e.g. suddenly appearing stimuli, emotional expressions) are in place from infancy, it is the interplay between these predispositions, genetic and environmental factors that drives attention development over time. With the advent of multidisciplinary approaches to the developmental cognitive neuroscience of attention, unravelling these complex dynamics from infancy and their outcome on learning is increasingly within reach.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Trajectories of attention: the interplay between the attentive observer and the visual world
  5. How does attention go awry? Studying mechanisms of attention development through its disorders
  6. What is attention for? The interplay between attention, memory and learning over development
  7. Conclusions and future directions
  8. References

Dealing with a complex environment requires prioritizing certain stimuli over others according to one’s goals. These attentional biases gate information for further processing at multiple levels of analysis, from the perception of incoming stimuli, to memory encoding, to the control of actions. They are implemented by an extended frontoparietal network, whose coordinated activity influences competition amongst stimuli or responses represented in lower cortical or subcortical areas (Posner & Rothbart, 2007). To developmental cognitive neuroscientists, therefore, understanding what drives changes in attentional processes is critical for at least two reasons: first, on a moment-by-moment basis, it can reveal how slowly developing neurocognitive control mechanisms interact with salient perceptual characteristics of the sensory world; second, it provides insights into the cascading effects of attentional differences on action selection and learning over time. Three overarching themes shape new perspectives on the developmental science of attention: the interplay between stimulus-driven and endogenous factors over time; the extent to which developmental disorders inform mechanisms of typical attention development; and interactions between attention, memory and learning. This is by design a selective overview of the latest literature, dotted by references to fuller expositions of specific points. I focus primarily on attentional development in terms of its influence on visual processing, and less as the executive control of action (but see Crone, 2009, for a related review, and Hanania & Smith, 2010, for overlap across these processes). For each theme, I first describe findings from childhood to adulthood, to then highlight insights emerging from the study of attention in infants and younger children.

Trajectories of attention: the interplay between the attentive observer and the visual world

  1. Top of page
  2. Abstract
  3. Introduction
  4. Trajectories of attention: the interplay between the attentive observer and the visual world
  5. How does attention go awry? Studying mechanisms of attention development through its disorders
  6. What is attention for? The interplay between attention, memory and learning over development
  7. Conclusions and future directions
  8. References

Models of attention construe attention as an ensemble of highly related but distinguishable processes (e.g. alerting, orienting, selective, sustained and executive attention) that are influenced by, on the one hand, endogenous influences driven by internal representations of task goals, and, on the other, by exogenous influences representing the extent to which attention is captured by events in the environment (Corbetta & Shulman, 2002). How do these factors interact over developmental time?

Developmental trajectories of attentional processes: childhood and beyond

Iarocci, Enns, Randolph and Burack (2009) investigated the coordination of endogenous and exogenous influences by asking participants aged 5 to 81 years of age to detect the appearance of a peripheral target. These were preceded either by a central arrow cue that predicted target location on the majority of trials and was followed by a peripheral flash that did not, or by central and peripheral cues presented in isolation. The effects of peripheral flashes alone were similar across age groups, but 5-year-olds were heavily affected by arrows directing attention in the incorrect (invalid) location, consistent with the earlier developmental emergence of exogenous, compared to endogenous, effects on orienting. Critically, younger children and older seniors were more heavily affected than the intermediate age groups by peripheral flashes when combined with invalid arrow cues, suggesting additional changes in the ability to cope with interfering information. Ristic and Kingstone (2009) also asked how exogenous and endogenous factors operate in 3- to 6-year-olds compared to adults, by pitting against each other predictive and non-predictive arrow and shape cues. Predictive arrows resulted in orienting benefits, but so did non-predictive arrow cues for both age groups. However, only for adults were the benefits of predictive arrow cues larger than the benefits accrued with predictive shapes or non-predictive arrow cues, emphasizing both similarities and differences in the coordination of attentional selection: across age groups, cues like arrows combine both volitional and reflexive effects, but adults are better able to integrate endogenous and exogenous cues to select advantageously.

These studies revived classical questions about attention trajectories, albeit in response to very simple cues and target stimuli. Attention in the real world requires even further, and changing, integration across information sources, as illustrated in the case of multi-sensory processing (Barutchu, Crewther & Crewther, 2009). Fletcher-Watson, Collis, Findlay and Leekam (2009) investigated the development of change blindness in 6- to 12-year-olds and adults. Changes of different kinds (colour, presence/absence, location) were either semantically central to naturalistic scenes, or marginal to them. Participants of all ages were sensitive to semantic content, suggesting that prior knowledge aids attentional selection, at least from mild-childhood, although the efficiency of change detection improved steadily until 10–12 years. Location changes were the most difficult to detect, but interestingly for marginal changes only, and to a greater degree for the youngest children and adults. In contrast, these were really easy to spot for semantically central portions of the scene for all groups, suggesting that changes in attentional priorities for spatial information and semantic associations interact. In turn, the findings emphasize the interplay between salient perceptual input and an attentive observer’s knowledge when dealing with a complex world.

Understanding attentional biases in infants and toddlers: the role of predispositions and experience

Some stimuli gain attentional priority from infancy, but to what extent are these orienting responses pre-programmed, liable to low-level perceptual characteristics or experience? Teasing apart these influences has focused much of the literature in infancy on attention to faces. For example, neonates do not show a preference for fearful over neutral expressions and in contrast fixate for longer happy facial expressions (Farroni, Menon, Rigato & Johnson, 2007), whereas 7-month-olds disengage attention from a centrally presented fearful facial expression less easily than from control stimuli and happy facial expressions, although not significantly less than from a novel expression (Peltola, Leppanen, Palokangas & Hietanen, 2008). These differences may be reconciled by the coordination of visual salience and prior experience for at least some, though not all, facial expressions (LoBue, 2009; LoBue & DeLoache, 2010). Fast orienting may indeed index a bias to learn very quickly about stimulus valence: for example, DeLoache and LoBue (2009) found that although there are no baseline differences in 8- and 16-month-olds’ looking to videos or photos of snakes compared to other animals, videos of moving snakes were attended for longer when these were associated with a frightened rather than a happy human voice, suggesting fast and selective learning of the association between fear and snakes. Perceptual features were critical to this learning bias, as similar associations did not emerge for static photos of snakes. Low-level perceptual factors have also been suggested to account for newborns’ preferences for face-like stimuli (Cassia, Valenza, Simion & Leo, 2008), pointing to the idea that these attentional biases shape infant learning, but are in turn driven by perceptual characteristics of attended stimuli and experience.

Understanding perceptual influences on how infants attend to stimuli and events is not only relevant for highly salient stimuli, but also in the context of either ‘rich’ (conceptual) or ‘lean’ (perceptual) interpretations of looking (Aslin, 2007). Both the development of novel techniques and theoretical proposals are advancing this debate. For example, detailed measures of overt reaching and eye-movement patterns have aided the interpretation of the cognitive mechanisms underpinning performance in young children: Haddad, Kloos and Keen (2008) found that 3-year-olds’ search errors and eye-movements when searching for a ball rolling behind a transparent screen were guided by both spatiotemporal information and knowledge about solidity, although spatiotemporal cues dominated reaching decisions when cues were put into conflict. Further looking measures also enrich the interpretative toolkit of researchers studying infant attention: Jackson and Sirois (2009) showed that information on pupil dilation can help distinguish between otherwise equivocal looking behaviours in violation-of-expectancy paradigms. Regardless of the specific parameter used, what accounts for the primacy of certain cues in attracting visual attention during looking paradigms? Charles and Rivera (2009) explained clear dissociations in 5-month-olds’ looking time to objects’ disappearance and reappearance events depending on the specific mode of disappearance (e.g. failure to reappear by objects occluded by darkness did not result in increased looking, whereas failure to reappear after standard occlusion did) in terms of differential learning about the characteristics of occlusion events in the real world, and of how these differences in turn influence whether objects are likely to remain within reach or visible after reappearance (see Shinskey & Munakata, 2010, for an experience-driven account of familiarity/novelty preference shifts).

And yet, to date there is limited direct information on how perceptual experiences and other factors might vary over development and systematically affect changes in attention. Smith, Yu and Pereira (in press) mapped the visual world as observed from the viewpoint of adults (caregivers) as opposed to 17- to 19-month-old toddlers, revealing that a smaller workspace (imposed by toddlers’ body-size and arm length) has as a by-product the selection of much more restricted, often single-object, viewpoints that are perhaps ideal for constraining the task of selection in a cluttered visual world. In turn, these findings highlight how, because of the changing nature of the view of the world over development, perceptually identical stimuli will appear very differently salient, be acted upon and capture attention differently for younger compared to older attentive observers. Together with differences in how perceptual experiences are shaped by the changing developing system, growing research focuses on how attentional abilities can be influenced by training or altered experience (e.g. Tang & Posner, 2009). Genetic factors also mediate the efficiency of attentional control by modulating neurotransmitter systems key to the functioning of frontoparietal and frontostriatal circuits: Holmboe, Nemoda, Fearon, Csibra, Sasvari-Szekely and Johnson (2010) found that infants who are homozygote for a variant of the catechol-Omethyltransferase (COMT) gene that results in slower metabolism (and therefore greater availability) of dopamine in prefrontal cortex were less distracted by peripheral stimuli when engaged in fixating attractive central stimuli. Intriguingly, this effect was moderated by variants of the dopamine transporter gene (DAT1), critical in dopamine clearance in the basal ganglia, suggesting gene–gene interactions on circuits that mediate the efficiency of attentional selection. Finally, multifactorial variables influenced by both genetic predispositions and environmental differences, like socioeconomic status, also constrain attentional abilities. Stevens, Lauinger and Neville (2009) recorded event-related potentials while 3- to 8-year-olds attended one of two engaging narratives, and superimposed infrequent irrelevant auditory tones on both the attended and unattended narrative. Children whose mothers had lower levels of educational attainment showed reduced amplitude of event-related potentials as early as 100 milliseconds after the onset of auditory tones in the unattended narrative, suggesting that they do not filter irrelevant information as efficiently. Differences across individuals over developmental time have most clearly been studied in developmental disorders, to which we now turn.

How does attention go awry? Studying mechanisms of attention development through its disorders

  1. Top of page
  2. Abstract
  3. Introduction
  4. Trajectories of attention: the interplay between the attentive observer and the visual world
  5. How does attention go awry? Studying mechanisms of attention development through its disorders
  6. What is attention for? The interplay between attention, memory and learning over development
  7. Conclusions and future directions
  8. References

Just like patients with discrete brain lesions, developmental disorders of attention provide unique tools within which to study the neurocognitive mechanisms of attention, because they offer insights into how either genetically or behaviourally defined differences from the normal population influence attention development. Critically, unlike cases of brain damage received in adulthood, disorders identified in infancy or childhood modify the way in which the cognitive system interacts with its environment as development is taking place. Therefore, patterns of developmental change and stability need to be studied empirically in order to understand what drives cognitive differences at each point in development (Karmiloff-Smith, 2007, 2009). This emphasis on the careful examination of performance and its neural bases over developmental time is taking its hold on research on attention in developmental disorders.

Developmental trajectories from childhood into adulthood

Williams Syndrome (WS), a rare disorder associated with a microdeletion on chromosome 7, has attracted much interest for its uneven cognitive profile, with weaknesses in visuospatial cognition that some initially linked selectively to specific genes in the affected region of DNA. Recent work in this area has highlighted further a much more complex picture: first, aspects of visuospatial cognition are relatively more affected than others, ruling out a straightforward association between ‘all things spatial’ and WS; second, these ‘dorsal stream deficits’ are highly prevalent amongst diverse developmental disorders; and finally patterns of impairment interact dynamically with areas of relative cognitive strength. O’Hearn, Hoffman and Landau (2010) assessed the ability to track multiple moving objects or remember the spatial locations of static objects in 3- to 6-year-old typically developing children and in children and adults with WS (10- to 28-year-olds). People with WS tracked moving objects as well as 4-year-old typically developing children, whereas they remembered static locations at the same level as 6-year-olds (i.e. worse than expected given their chronological age for both tasks). The authors suggest that the differential impact on the two tasks for individuals with WS is because distinct mechanisms are involved in the two skills, but they also propose that this pattern could be driven by greater attentional demands for multiple object tracking. Reporting patterns of performance in relative rather than absolute terms is indeed critical in evaluating process-specific or general candidates accounting for weaker and better performance. A further consideration for researchers investigating pathways from genetic differences to cognitive profiles in WS is the fact that strengths and weaknesses are not cognitively impenetrable: Farran, Blades, Boucher and Tranter (2010) found that, although poorer than typically developing individuals and individuals with moderate learning difficulties at large-scale navigation tasks (like learning a route in an unfamiliar 1-km route), when given verbal instructions adults with WS learnt routes efficiently. Finally, ‘dorsal stream’ weaknesses in individual developmental disorders like WS need to be reconciled with (i.e. provide explicit mechanisms for) their high prevalence in many other developmental disorders that show very different neurocognitive and behavioural phenotypes in related but distinct cognitive domains (e.g. social cognition). For example, Farzin and Rivera (2010) reported spatiotemporal integration difficulties for moving objects for infants and toddlers with fragile X syndrome, a developmental disorder associated with the silencing of a single X-linked gene, in the context of strikingly different attentional and social cognitive profiles compared to WS. Accounts of the shared dorsal stream vulnerability across some of these disorders have been provided in terms of converging molecular pathways (e.g. Walter, Mazaika & Reiss, 2009), but these do not as yet encompass both diverging and converging cognitive-level developmental trajectories (Scerif & Steele, in press).

In a similar vein, recent perspectives have instead highlighted the heterogeneity of developmental pathways leading to inattention and hyperactivity in behaviourally defined disorders of attention like attention deficit hyperactivity disorder (ADHD), initially associated with a single core deficit of executive control. For some children inhibitory difficulties and for others atypical processing of rewards may underpin risk for ADHD (Sonuga-Barke, Auerbach, Campbell, Daley & Thompson, 2005). These suggestions have in turn motivated interest in whether inhibitory control is modulated by incentives (e.g. Groom, Scerif, Liddle, Batty, Liddle, Roberts, Cahill, Liotti & Hollis, 2010; Kohls, Peltzer, Herpertz-Dahlmann & Konrad, 2009; Liddle, Scerif, Hollis, Batty, Groom, Liotti & Liddle, 2009). For example, Groom and colleagues found that, in both typically developing children and children with ADHD, the amplitude of N200 and P300, event-related potentials modulated by inhibitory and attentional demands, is enhanced by motivational incentives. Other behaviourally defined disorders such as autistic spectrum disorders (ASD) have also been associated with atypical attention: factors underpinning superior visual search performance in this group remain debated, so Joseph, Keehn, Connolly, Wolfe and Horowitz (2009) used two tasks, a traditional visual search task and a dynamic search task in which changes occurred every 500 ms, to investigate whether the visual search advantage depends on superior memory for previously rejected distractors. Benefits compared to controls remained even when dynamic search was required and faster reaction times in ASD were measured across the two tasks, suggesting that perceptual discrimination factors (such as the ability to distinguish between targets and distractors at the locus of attention), rather than atypical distribution of attention per se, underpin superior visual search in individuals with autism. The authors went on to advocate the use of longitudinal studies to investigate whether, and if so how, atypical perceptual and attentional processes relate to the social-communicative difficulties that are characteristic of the spectrum. Indeed, recent work on attentional control in developmental disorders has emphasized the need to understand patterns of cognitive strength and weakness in terms of trajectories of change, and it is to novel insights from longitudinal trajectories of attention in individuals with developmental disorders that we now turn.

Insights from developmental trajectories and longitudinal change

Many have emphasized the need to chart how cognitive abilities change over development for individuals with genetic disorders, rather than limiting studies to the comparison to typically developing controls, the traditional mental age matching approach, as the latter strategy removes, rather than investigates, age-related changes (e.g. Thomas, Annaz, Ansari, Scerif, Jarrold & Karmiloff-Smith, 2009). Recent attention and control findings highlight the value of this approach. Children with WS (on average, 12-year-olds) performed more poorly than expected, given their level of cognitive functioning, on a task that required visuo-motor control, although they were also, though more subtly, impaired on a perceptual matching task, and in both tasks their performance was comparable to that of 4-year-old children (Dilks, Hoffman & Landau, 2008). Adults (on average, 23-year-olds) with WS did not differ from children with the condition on either task (and thus from typically developing 4-year-olds), a pattern that to the authors suggested ‘developmental arrest’. However, data from other genetic disorders suggest that such a conclusion may be premature without longitudinal insights. Cornish, Cole, Karmiloff-Smith and Scerif (in preparation) studied attentional control in a sample of 4- to 10-year-olds with FXS and typically developing children by asking them to monitor a rapidly presented stream of visual stimuli for infrequent targets under a number of attentionally demanding conditions. Children with FXS performed more poorly than expected given their chronological age and developmental level, and older children with FXS were no better than younger children in the group, a pattern that may have suggested not just severe developmental delay, but ‘developmental arrest’. However, when followed longitudinally, the same children showed improvements in performance that were comparable to those of typically developing children matched to their developmental level, underscoring the danger of drawing conclusions about developmental change (or none thereof), from cross-sectional data, as these intrinsically confound age-related and individual differences.

Longitudinal studies have also become increasingly used in the study of behaviourally defined developmental disorders affecting attention, as a way of mapping the interaction between genetic and environmental factors in predicting risk for a disorder (e.g. S.E. Stevens, Kumsta, Kreppner, Brookes, Rutter & Sonuga-Barke, 2009, for ADHD). In the case of ASD, cognitive development can be studied prospectively from infancy in the siblings of older children with autism, because siblings are at higher risk of developing ASD given high heritability estimates for the condition (Elsabbagh & Johnson, 2010). At 10 months, for example, siblings take longer to disengage attention from a central stimulus to a concurrently presented peripheral stimulus and electrophysiological recordings show atypical latency for the P400 and atypical gamma band activity when processing direct eye-gaze (e.g. Elsabbagh, Volein, Csibra, Holmboe, Garwood, Tucker, Krljes, Baron-Cohen, Bolton, Charman, Baird & Johnson, 2009a; Elsabbagh, Volein, Holmboe, Tucker, Csibra, Baron-Cohen, Bolton, Charman, Baird & Johnson, 2009b). Of note, as for disorders of known genetic origin, cognitive abilities need to be followed longitudinally, as illustrated by recent data: Young, Merin, Rogers and Ozonoff (2009) assessed outcomes at multiple time-points until the age of 24 months for toddlers who, at 6 months, had been assessed with a still face procedure. At that time-point, a significantly greater proportion of siblings at risk for autism than control infants had preferred looking at their mother’s mouth, compared to eyes, both during the still face episode and in baseline periods preceding and following it. When tested longitudinally, gaze preferences in infancy did not predict later likelihood of developing autistic symptoms, underscoring the need to re-evaluate the utility of such measures and/or discover protective factors leading to later absence of symptomatology. Surprisingly, greater preference for the mouth region predicted faster growth of expressive vocabulary, suggesting novel hypotheses about the role of attention to audiovisual events at the very onset of language acquisition. More broadly, these data challenge notions derived from studying the relationship between visual attention and other cognitive domains at single time-points, or even through cross-sectional comparisons.

What is attention for? The interplay between attention, memory and learning over development

  1. Top of page
  2. Abstract
  3. Introduction
  4. Trajectories of attention: the interplay between the attentive observer and the visual world
  5. How does attention go awry? Studying mechanisms of attention development through its disorders
  6. What is attention for? The interplay between attention, memory and learning over development
  7. Conclusions and future directions
  8. References

Much of the work reviewed thus far focused on how (primarily spatial) attentional biases operate over development in their influence on incoming perceptual stimuli. But what is the impact of these biases on what adults, children and infants encode, learn and remember? The rationale for recent studies investigating the relationships between attentional control, learning and memory is that it may be possible to understand attention development by studying its impact on learning and memory, and in turn how attentional control is influenced by them.

Attentional control and visual memory in childhood and beyond

Recent data on the adult neuroscience of attention and memory emphasize how spatial attentional biases influence not only one’s ability to encode, but also maintain and search for information in visual short-term memory, VSTM (e.g. Astle, Nobre & Scerif, 2009a; Astle, Scerif, Kuo & Nobre, 2009b). These findings are critical for developmentalists focused on spatial attentional biases: Astle, Nobre and Scerif (in press) asked 7-year-olds, 10-year-olds and adults to report whether a probe item had been part of a previously presented four-item array in situations in which this could either be preceded (‘precued’) or followed (‘retrocued’) by a centrally presented spatial cue orienting attention to one of the potential item locations. Performance across age groups was significantly improved by both cue types, but children benefited from attentional cues provided during encoding more than those during the maintenance period, in contrast with adults’ ability to benefit from both. In addition, individual differences in children’s attentional orienting to items in VSTM predicted their performance in traditional span tasks. The findings indicate that there are substantial developmental and individual differences in the ability to control attention to memory and that in turn these differences influence operations on VSTM, consistent with a substantial literature on how adults and children with either high or low VSTM capacity differ in their ability to control attention recruit overlapping frontoparietal circuits (Awh, Vogel & Oh, 2006; Olesen, Macoveanu, Tegner & Klingberg, 2007), even on tasks that do not have a memory component (Fukuda & Vogel, 2009).

Two notes of caution qualify this growing literature on the developmental cognitive neuroscience of the intimate link between visuospatial attention and memory. First, developmental and individual differences in attentional control do not necessarily recapitulate each other in their relations to other constructs (Michel & Anderson, 2009) and therefore need to be studied in the context of longitudinal designs to test whether individual differences predict differential rates of developmental change. Second, the data described above do not imply that the relationship between attentional control and VSTM is unidirectional, or that attentional control is the sole predictor of changes in VSTM capacity. Cowan, Morey, AuBuchon, Zwilling and Gilchrist (2010) tested whether attentional filtering abilities (indexed by the costs of being exposed to infrequent target dimensions on the accuracy of detecting a change in a memory array) account for differences in VSTM span between 7–8-year-olds, 12–13-year-olds and adults. They found that age groups differed in basic memory capacity, and that interference effects below the limit of capacity were similar across age groups, suggesting that attentional filtering processes are not the only drivers of differences in capacity across age groups. It is also clear that representations held in memory can influence spatial attention, and in turn that information held in memory can guide spatial attention, even when the former simply provides a context to the task at hand (e.g. Kim, Kim & Chun, 2010) or it is subliminally presented (Astle, Nobre & Scerif, 2010). Dixon, Zelazo and De Rosa (2010) examined the performance of 5- to 9-year-olds on an age-appropriate version of the contextual cueing paradigm (e.g. Chun & Jiang, 1999), in which children searched for a target among distractors in new displays and in ‘old’ visual scenes. Old displays repeated across blocks of trials, providing experience with the characteristics of those visual scenes. Children searched old displays increasingly faster than new displays, suggesting interactions between medial-temporal and frontoparietal networks akin to those measured in adults (Summerfield, Lepsien, Gitelman, Mesulam & Nobre, 2006) and, more broadly, that children’s remarkable sensitivity to statistical regularities of their visual environment can guide attentional deployment.

Attention and learning in infants and young children: relationships and longitudinal changes

The close-coupling between attentional cues and memory have also been recently traced for younger children and infants, primarily in the context of salient social attentional cues, like adults’ direction of attention. For example, 14-month-olds observed an adult look at a target in front of and behind a barrier (Chow, Poulin-Dubois & Lewis, 2008). Infants who had previously observed an adult expressing happiness to locating an object inside a box were more likely to search for a target hidden behind a barrier compared to infants who had previously seen the adult act similarly toward an empty container. Therefore, 14-month-olds can learn very quickly from attention cues, and part of what they learn is the reliability of someone’s looking behaviour. Of course, it has long been known that the direction of adults’ gaze can direct even younger infants’ attention, but do these orienting episodes in infants have functional effects? Hoehl, Reid, Mooney and Striano (2008) explored electrophysiological markers involved when 4-month-olds perceived adult eye-gaze directed to objects, compared to eye-gaze directed elsewhere. They found that both early and late event-related potentials differentiate these situations, providing converging neural evidence that infants attend to and process the relationship between adults’ gaze and other objects well before they can engage in complex search behaviours. What do young infants learn from such relationships? Wu and Kirkham (in press) asked whether adults’ attention direction aids infants’ learning about multimodal events in their environment. They presented 4- and 8-month-olds with arbitrary pairs of animated characters and sounds that, in a simplified format (i.e. presenting single characters and sounds), had previously elicited learning even in 3-month-olds (Kirkham, Richardson, Wu & Johnson, submitted). They preceded these pairings with either social attentional cues (an adult’s face orienting towards the location of the appropriate pairing) or colourful peripheral flashes. Despite attending for equal duration to the cued locations across the different training conditions, only 8-month-olds exposed to the social cue showed specific learning of audio-visual pairings, suggesting a primacy of social attentional cues as an aid to learning, but one that is established as a function of experience.

In this context, longitudinal and training studies are increasingly playing a highly informative role, because they can reveal temporal relationships between distinct attentional processes and domain-specific learning, and how influencing one mechanism can change the other. For example, Steele, Cornish, Karmiloff-Smith and Scerif (in preparation) found that the ability to control spatial conflict predicted 3- to 6-year-olds’ concurrent ability to understand cardinality, letter knowledge and vocabulary size, but the ability to sustain visual attention and select targets amongst distractors was a stronger predictor of numerical (but not single word reading) a year later. Thorell, Lindqvist, Nutley, Bohlin and Klingberg (2009) found that training working memory in preschoolers is associated with improvements in sustained attention, although the reverse effects (whether training attention improves working memory) has not been studied in this age group. As specific training programmes predict improvements in specific academic outcomes in school-aged children at risk for poor learning (e.g. Holmes, Gathercole & Dunning, 2009, for working memory training improving outcomes in mathematics scores 6 months later), understanding the neurocognitive mechanisms for baseline longitudinal relationships between attention and memory, as well as their malleability by intervention, can play a pivotal role in developmental theories of attention.

Conclusions and future directions

  1. Top of page
  2. Abstract
  3. Introduction
  4. Trajectories of attention: the interplay between the attentive observer and the visual world
  5. How does attention go awry? Studying mechanisms of attention development through its disorders
  6. What is attention for? The interplay between attention, memory and learning over development
  7. Conclusions and future directions
  8. References

When asking about what drives developmental trajectories of attention, initial developmental theories had emphasized a simple maturational account of their changes over time, with exogenous influences emerging long before endogenous control processes. While maintaining this distinction, recent work in this area paints a much more complex picture of the interplay between attentional biases and experience. Recent studies have also increasingly asked about bi-directional relationships between attentional processes and other aspects of developing cognition, and novel findings on attention in individuals with developmental disorders illustrate clearly the need to study gene × environment × time interactions across domains. Prospective longitudinal and training studies are also playing a critical role in theory development. The future developmental science of attention will most likely integrate the three components reviewed here: drivers of developmental trajectories in typically developing individuals, how these can be modified by genetically or behaviourally defined developmental disorders, and their impact on learning and memory across domains. Throughout this enterprise, an increasing emphasis on developmental processes has made, and will continue to make, for groundbreaking science.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Trajectories of attention: the interplay between the attentive observer and the visual world
  5. How does attention go awry? Studying mechanisms of attention development through its disorders
  6. What is attention for? The interplay between attention, memory and learning over development
  7. Conclusions and future directions
  8. References