Precursors to language development in typically and ......exploring it. Before they can acquire...

Precursors to language development intypically and atypically developing

infants and toddlers: the importance ofembracing complexity*

DEAN D ’SOUZA

Centre for Brain & Cognitive Development, Birkbeck, University of London,London, UK, and UCL Institute of Education, University College London,

London, UK

HANA D ’SOUZA

Centre for Brain & Cognitive Development, Birkbeck, University of London,London, UK, and London Down Syndrome Consortium, University College

London, London, UK

AND

ANNETTE KARMILOFF-SMITH

Centre for Brain & Cognitive Development, Birkbeck, University of London,London, UK, and London Down Syndrome Consortium, University College

London, London, UK

(Received August –Revised December –Accepted February –

First published online April )

ABSTRACT

In order to understand how language abilities emerge in typically andatypically developing infants and toddlers, it is important to embracecomplexity in development. In this paper, we describe evidence thatearly language development is an experience-dependent process, shapedby diverse, interconnected, interdependent developmental mechanisms,

[*] D.D. is supported by Autour des Williams, The Waterloo Foundation, and GrantRPG-- from The Leverhulme Trust. H.D. and A.K-S. are funded byWellcome Trust Strategic Grant No. /Z//Z conferred upon The LonDownSConsortium UK. Address for correspondence: Dean D’Souza, Psychology & HumanDevelopment, UCL Institute of Education, University College London, WoburnSquare, London WCH AA, United Kingdom. e-mail: [email protected]

J. Child Lang. (), –. © Cambridge University Press doi:./SX

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processes, and abilities (e.g. statistical learning, sampling, functionalspecialization, visual attention, social interaction, motor ability). We alsopresent evidence from our studies on neurodevelopmental disorders (e.g.Down syndrome, fragile X syndrome, Williams syndrome) that variationsin these factors significantly contribute to language delay. Finally, wediscuss how embracing complexity, which involves integrating data fromdifferent domains and levels of description across developmental time,may lead to a better understanding of language development and,critically, lead to more effective interventions for cases when languagedevelops atypically.

INTRODUCTION

Many researchers express their surprise at the rapid pace and apparent easewith which most infants learn their native language (e.g. Kuhl, ).Indeed, it has often been taken as evidence that infants are DESIGNED forthe task – a top-down process whereby ‘evolution’ endows the humanneonate with structures DEDICATED TO THE ACQUISITION OF LANGUAGE

(Chomsky, , , ; Dehaene-Lambertz & Spelke, ).According to this PREDETERMINED EPIGENESIS perspective, some aspects oflanguage development are independent of other cognitive abilities, andwhen children struggle to develop language, it is because the ‘languagepart’ of the brain is impaired (Pinker, ). Over the past couple ofdecades, however, a new account of language development has beenchampioned which treats all linguistic knowledge as an emerging propertyof complex, experience-driven, self-organizing processes (Hockema &Smith, ; Mareschal, Johnson, Sirois, Spratling, Thomas &Westermann, ; Smith, ). According to this PROBABILISTIC

‘neuroconstructivist’ perspective, language learning is yoked with cognitivedevelopment, language emerges from progressive, context-dependentprocesses that are also associated with non-linguistic learning, andchildren who struggle to develop language are likely to havedomain-general impairments that affect their ability to constructnon-linguistic as well as linguistic knowledge. We will discuss evidence insupport of these claims; i.e. evidence of early (domain-general) processesthrough which language abilities emerge in typically and atypicallydeveloping infants and toddlers. Our paper is divided into three sections:the first outlines the neuroconstructivist approach we have adopted; thesecond discusses evidence of early processes (e.g. functional specialization)and mechanisms (e.g. neural plasticity, statistical learning) through whichlater-developing, higher-level language abilities emerge; and the thirdconsiders the theoretical and practical implications of the empiricalfindings we describe.

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THE NEUROCONSTRUCTIVIST APPROACH TO LANGUAGE

DEVELOPMENT

Crucial to neuroconstructivism (and other developmental systems approaches

such as dynamic systems theory) is the concept of control without a controller.On this view, no specific entity – genetic or otherwise – plans or controlsdevelopment. Instead, developmental processes (including those related tolanguage development) gradually emerge from complex cascades ofbiological and physical interactions. One way of conceptualizing this is toview development as experience-driven processes that occur within complexbiological and ecological systems – and thus as CONSTRAINED by internal andexternal factors at multiple levels (e.g. genetic, neural, behavioural, societal)and timescales (Mareschal et al., ).

Also crucial to neuroconstructivism (and other developmental systemsapproaches) is the concept of ‘interdependence’ between different, diversefactors. For example, language development varies as a function ofparental input (Hoff, Welsh, Place & Ribot, ), but parental inputvaries as a function of the child’s language performance (Zampini, Fasolo& D’Odorico, ). The interplay between diverse but INTERDEPENDENT

units often generates complex behaviours in living systems. On this view,developmental processes should not be studied in isolation.

Finally, neuroconstructivists (and other developmental systems theorists)argue that development is an EXPERIENCE-DRIVEN process, and thatdevelopmental systems (like the human infant) are ADAPTIVE systems (theychange in response to their environments, as they act on and learn aboutthem). On this view, language skills are developed THROUGH learningexperiences. Furthermore, the timing of developmental events is likely to

Although developmental systems theory differs from approaches such as dynamic systemstheory, connectionism, and neuroconstructivism, the core tenets of developmentalsystems theory are shared by these three (and other non-nativist) approaches. Therefore,for want of a better term, we (like Ulrich, ) use ‘developmental systems’ as anumbrella term for a group of approaches that view cognitive and motor processes as theemergent functions of a complex stochastic adaptive system. For example, dynamicsystems theory and connectionism both seek to explain how emergent (short-term anddevelopmental) dynamics arise from underlying mechanistic dynamics (dynamic systemstheorists tend to focus on bodily constraints, connectionists on constrains within thenervous system; Spencer, Thomas, and McClelland, ), and neuroconstructivism(which incorporates the connectionist approach [Elman et al., ]) seeks to understandhow partial representations (information states) in the brain emerge fromcontext-dependent processes and change over developmental time (Mareschal et al.,). Although all three approaches converge on problems in developmental psychologyfrom different sides, all three share the central tenet of developmental systems theory:developmental processes emerge from, and are controlled by, a complex web ofinteractions between diverse, interconnected factors (Blumberg, ).

Having DIVERSE, INTERDEPENDENT parts that ADAPT is what separates ‘complex’ (social,economic, political, ecological, biological) systems from complicated systems (Miller &Page, ).

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be an important constraining factor, because the formation of one functionmay shape (constrain) how later-developing functions emerge (seeD. D’Souza & Karmiloff-Smith, , for discussion).

Why would language skills be developed through learning experiences?Would it not be more advantageous to be born with a language module?Some argue that it is more adaptive to have neural circuits graduallydevelop over time to ensure that circuitry is appropriately shaped by thespecifics of the relevant input (e.g. Bates & Elman, ; D. D’Souza &Karmiloff-Smith, ; Elman, ; Elman, Bates, Johnson, Karmiloff-Smith, Parisi & Plunkett, ; Greenough, Black & Wallace, ;Johnson, ; Karmiloff-Smith, ; Stiles, ). In other words, notonly may the protracted period of brain development observed in humaninfants allow late-generated brain structures to emerge (Clancy, Darlington& Finlay, ), it may also provide time for the infant brain to calibrateor adjust its internal operations (connectivity and computations) to thespatial and temporal metrics of the external world (Buzsaki, ). Asystem that adaptively develops in interaction with its environmentmay also be more robust to perturbation than a system with fixed,predetermined structures and functions (Miller & Page, ). This mayexplain why an individual’s genes can be expressed differently dependingon his or her developmental environment (Lickliter, ).

The upshot is that neuroconstructivists expect higher-level abilities(such as language) to emerge through a gradual process of adaptation thatincorporates mechanisms of change (e.g. neural PLASTICITY) anddevelopmental processes (e.g. progressive FUNCTIONAL SPECIALIZATION)across different (but interconnected) levels and domains. ‘Plasticity’ refersto the process by which neural connectivity and circuitry change as afunction of experience. It comprises different mechanisms, occurs ondifferent levels and timescales (from the nearly immediate local effects ofHebbian plasticity to gradual large-scale reorganization of the brain; Power &Schlaggar, ), and is associated with functional changes that includelearning and memory. ‘Functional specialization’ is the concept thatactivity-dependent interactions between different interdependent factors (e.g.neural plasticity, sensory input) hone the functions and response properties ofneural networks such that their activity becomes restricted to a narrower set ofcircumstances (Johnson, ). For example, neural networks that activate inresponse to, and can discriminate between, human infant, human adult, andmonkey faces may – after extensive experience with only human adult faces –become increasingly tuned to processing human adult face stimuli and losethe ability to discriminate well between human infant or monkey face stimuli(Macchi Cassia, Bulf, Quadrelli & Proietti, ; Pascalis, de Haan & Nelson,). Thus, at the behavioural level, developmental systems approachesexpect highly constrained, highly organized, structured activity to emerge

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gradually from widespread, uncoordinated, spontaneous activity; at the brainlevel, they expect increased neural tuning (specialization) in response to agiven stimulus or set of task demands (Johnson, ). Indeed, thisdevelopmental process – i.e. functional specialization – has been identified inseveral domains, including face perception (Pascalis et al., ), motor ability(H. D’Souza, Cowie, Karmiloff-Smith & Bremner, ), and – as we discussbelow – language ability.

SPECIALIZATION AS AN ACTIVE PROCESS

However, progressive specialization is not a passiveprocess; it requires the infantto calibrate its internal operations to the external world by actively exploring(selecting, acting on) and sampling it (Buzsaki, ). If the infant lacks thecognitive tools to intelligently explore or sample the environment, or isexposed to an atypical or restricted environment that hampers exploration,then this will constrain the process of specialization and the infant is morelikely to develop atypically (Johnson, Jones & Gliga, ). In other words,infants adapt to their environment, including the language environment, byexploring it. Before they can acquire language, they must be able to sampleand extract structure from the external world, as well as learn what aspects ofthe environment are relevant, i.e. worth directing their attention towards. Forexample, infants when lying on their back must redirect their attention from,say, the surface of a featureless ceiling to sample a novel talking face, and learnto extract patterns (units of speech) from the continuous streams of sound thatthey hear. They must also learn what aspects of their environment to focus on.For instance, if a preverbal infant were to focus their attention only onchanges in pitch, then they would miss important distributional (and otheracoustic) cues. Even if the preverbal infant were to appropriately select andact on the environment, such as orienting away from a ceiling towards aspeaking face to sample important audiovisual speech information, he or shewould also need to process that information appropriately (i.e. learn from it)or risk specializing atypically. These overlapping basic-level neurocognitiveprocesses and mechanisms – SAMPLING (gathering information), LEARNING

(extracting structure and integrating information), and ATTENTION (selectinginformation) – are important precursors to language acquisition, and thetopics of the following three subsections.

Sampling

Because progressive specialization reflects changes in neural connectivity andthe response properties of different neurons over developmental time(Johnson, ), and because it is an experience-dependent process (i.e.adaptive systems require input), the process of sampling the environmentaffects functional plasticity and the timing of developmental processes




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(Benasich, Choudhury, Realpe-Bonilla & Roesler, ; Frankenhuis &Panchanathan, a, b). For example, an absence of visual input canprolong the critical period during which visual information may shapecertain structures (e.g. ocular dominance columns) in primary visual cortex(Mower, Caplan, Christen & Duffy, ). In human infants, inter-individualvariation in sampling can occur as a result of (i) variation in the externalenvironment, (ii) differences between infants’ ‘internal’ environments(interactions between genes and their molecular and cellular environments),and (iii) interactions between the infant and external environment. We discussall three constraints in detail below, using examples from the literature onbilingualism (variation in the external world), neurodevelopmental disorders(internal differences), and how having a neurodevelopmental disorderinteracts with parenting (internal–external interaction).

Differences in sampling due to the external environment. Because sampling isa stochastic process (events can be statistically analyzed but not preciselypredicted), Frankenhuis and Panchanathan (b) hypothesize thatfunctional specialization is likely to vary as a function of samplingbehaviour. Specifically, infants who develop in highly variableenvironments are likely to specialize later in development than infants whodevelop in less variable ones. This is because sampling a less variableenvironment would allow the infant to quickly generate confidentestimates, build accurate models of the external world, and successfullyanticipate future events. By contrast, infants who develop in more variableenvironments may require more samples to generate confident estimatesand thus more time to specialize to their environments.

In the language domain, functional specialization starts early in life. Forexample, human neonates are sensitive to a wide range of phonologicalcontrasts, both native and non-native (e.g. Bertoncini, Bijeljac-Babic,Blumstein & Mehler, ; Eimas, Siqueland, Jusczyk & Vigorito, ;Streeter, ). However, between and months of age, theirsensitivity to non-native contrasts declines, while their ability todiscriminate between contrasts in their native language improves (Kuhl,Stevens, Hayashi, Deguchi, Kiritani & Iverson, ; Werker & Tees,; Werker, Yeung & Yoshida, ). In other words, the infant brainbecomes progressively SELECTIVE to its native language. This process ofspecialization, which involves neural commitment and thus co-occurs witha corresponding reduction in plasticity, increases the fit between infantsand their specific language environment (Kuhl, Conboy, Coffey-Corina,Padden, Rivera-Gaxiola & Nelson, ). But what would happen if achild were exposed to a multilingual environment? It is likely that, withinthe same time frame, the child would be provided with fewer samplesfrom each language than a child raised in a monolingual environmentwould receive from its one language (Byers-Heinlein & Fennell, ).

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Moreover, the presence of two or more languages would likely make themultilingual environment more variable (e.g. increased phonemicvariability) than the monolingual environment. Although the effects ofexposure to a more variable language environment can be offset by use ofpredictive cues (e.g. interlocutor identity; Martin, Molnar & Carreiras, ),for many children, language input from two different languages may originatein the same person, the same environment, and even the same sentence(Byers-Heinlein, ). Furthermore, bilingual input may be less accurate(and thus less consistent) than monolingual input. Bosch and Ramon-Casas() analyzed speech recordings from a group of Catalan–Spanish bilingualmothers who reported speaking predominantly Catalan at home. They foundthat the mothers who had been raised in Spanish–Catalan homes orSpanish-speaking homes with early exposure to Catalan made significantlymore errors when producing words that contain the Catalan /e/–/ϵ/ contrast(which is not present in Spanish) than the mothers who had been raised inCatalan-speaking homes. These additional constraints (e.g. more variability,less consistency) could make sampling the language environment morechallenging for bilingual infants, which may prolong the process of functionalspecialization in the language domain. Indeed, emerging evidence isconsistent with this proposal. Pi Casaus () has found that bilingualinfants maintain the capacity to discriminate non-native consonants for sixmonths longer than monolingual controls. Moreover, Sebastián-Gallés,Albareda-Castellot, Weikum, and Werker () found that -month-oldSpanish–Catalan bilinguals, but not -month-old Catalan or Spanishmonolinguals, can visually discriminate English from French when watchingsilent video clips of French–English bilingual speakers reciting sentences inFrench or English. Although children younger than months were not tested,this suggests that bilinguals maintain their sensitivity to non-native languagesfor longer. However, neither monolinguals nor bilinguals were able todiscriminate between unfamiliar languages in adulthood (Werker, ). Thisindicates that specialization in bilinguals is initially protracted, but leads to asimilar adult state. Yet even this state may be different in these twopopulations. Tremblay and Sabourin () showed that although bilingualadults do not differ in their ability to discriminate non-native contrasts frommonolingual controls, they show an enhanced ability to learn them. Thissuggests that the adult bilingual brain retains some of its early plasticity (i.e. itis extra-sensitive to changes in the environment), perhaps as a consequence ofa slower rate of specialization. Thus, we argue that language context may

Interestingly, Bosch and Sebastián-Gallés () found that bilingual Spanish–Catalaninfants could discriminate a contrast native to Catalan at months and months, butnot at months. This U-shaped developmental pattern is difficult to explain. However,




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affect brain and cognitive development via differences in the frequency,variability, and consistency of linguistic input. It is important to note,however, that we are not claiming that differences in neural plasticity orfunctional specialization are necessarily negative; differences in plasticity/specialization between bilinguals and monolinguals are likely to be adaptive,increasing the fit between the infant and its environment (D. D’Souza &H. D’Souza, ). They may even be the source of a purported cognitiveadvantage in bilinguals (D. D’Souza & H. D’Souza, ).

Differences in sampling due to the internal environment. As described above,the ability to discriminate contrasts in the native language improves overdevelopmental time (Kuhl et al., ), while sensitivity to non-nativecontrasts declines (Werker & Tees, ; Werker et al., ). Thisspecialization for native language increases the fit between infants and theenvironment. However, infants demonstrate considerable variability intheir ability to adapt to the environment. Moreover, these early individualdifferences are associated with later developmental outcomes. Specifically,infants who show more specialization for their native language (e.g. betternative, and/or worse non-native, phonetic perception skills) have onaverage better language outcomes as toddlers (Kuhl, Conboy, Padden,Nelson & Pruitt, ; Kuhl et al., ; Tsao, Liu & Kuhl, ).Assuming that there were no major differences in the amount and qualityof the linguistic input that the participants received, we could draw theconclusion that later emerging language abilities are at least partlyconstrained by individual differences in the ability to select or processenvironmental input.

If individual differences in sampling constrain development even intypically developing children, then might alterations in sampling inatypically developing populations affect developmental processes such asspecialization to an even greater extent? For example, there is someevidence that neurophysiological responses to speech input are initiallydiffuse (widespread and bilateral) in typically developing (TD) children

progressive specialization is likely to include changes between neural circuits as well aswithin neural circuits (Johnson, ). The U-shaped pattern may therefore reflect not acomplete loss and subsequent gain of an ability to discriminate the native contrast, butrather a reorganization of neural connectivity at around months that resulted in atemporary reduction in sensitivity to the contrast. By contrast (and as expected),monolingual Catalan infants could discriminate the contrast at all three ages, whilemonolingual Spanish infants could discriminate the contrast only at months.

We are currently testing the hypothesis that experience-driven adaptations to more variablelanguage input involve changes to basic learning mechanisms in infants that give rise to apurported cognitive advantage (e.g., task-switching, cognitive flexibility): <https://www.researchgate.net/project/Raising-bilingual-children-the-effects-of-exposure-to-a-bilingual-environment-on-cognitive-development-in-infants>.

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and only gradually become more focal (e.g. left hemisphere dominant) anddifferentiated (with regions fractionating and becoming more selectivelyactivated) over developmental time (Brauer & Friederici, ;Minagawa-Kawai, Mori, Naoi & Kojima, ; but see Brown, Petersen &Schlaggar, , for critical discussion). By contrast, twenty-four toddlerswith autism spectrum disorder (ASD) showed more diffuse patterns ofactivation in responses to speech input than twenty TD controls matchedon chronological age (Coffey-Corina, Padden & Kuhl, ). Moreover,when the toddlers with ASD were divided into ‘high’ and ‘low’functioning subgroups (by median split of Autism Diagnostic ObservationSchedule social scores; Lord et al., ), the twelve low functioningtoddlers with ASD showed more diffuse patterns of activation than thetwelve high functioning toddlers with ASD (Coffey-Corina et al., ).Johnson et al. () propose that synaptic dysfunction in ASD (e.g.perturbed synaptogenesis; Bourgeron, ; Gilman, Iossifov, Levy,Ronemus, Wigler & Vitkup, ; Zoghbi, ) results in increasedneural noise and poor sampling of the environment (reduced fidelity),which leads to prolonged specialization plus excessive plasticity and hencedevelopmental delay. Indeed, poor evoked (neural) response reliability (i.e.less consistency across trials), yielding weaker signal-to-noise ratios invisual, auditory, and somatosensory systems, has been identified infourteen adults with ASD relative to fourteen TD controls matched onchronological age and IQ (Dinstein, Heeger, Lorenzi, Minshew, Malach &Behrmann, ). A similar theory of autism suggests that excessiveneuronal information processing in local circuits (leading tohyper-perception, hyper-attention, hyper-memory, etc.) renders the worlduncomfortably intense for individuals with the disorder, leading to socialand environmental withdrawal (Markram, Rinaldi & Markram, ; seealso Rubenstein & Merzenich, , and Simmons, Robertson, McKay,Toal, McAleer & Pollick, , for similar theories). This would alsoresult in poor sampling of the environment. Although this has not yetbeen directly tested in toddlers with ASD, atypical patterns of brainactivity (e.g. reduced gamma phase-locking) in children with ASD looksimilar to patterns of brain activity in rats prenatally exposed to valproicacid (Gandal, Edgar, Ehrlichman, Mehta, Roberts & Siegel, ), achemical compound that causes hyper-reactivity, hyper-connectivity, andhyper-plasticity of glutamatergic synapses in local cortical microcircuitry(Markram et al., ), hinting at an association between developmentaldelay and excessive plasticity. Furthermore, infants who develop ASDattend less to people and their activities from months of age, and whiletheir social-communication skills are indistinguishable from those of TDinfants at months, clear differences emerge by months (see Jones,Gliga, Bedford, Charman & Johnson, , for a review).




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ASD is not the only disorder for which synaptic dysfunction has beenattributed, however. In fact, a number of other neurodevelopmentaldisorders also show widespread abnormalities in synaptic function andplasticity (Blanpied & Ehlers, ; Zoghbi, ). For example, dendriticspine abnormalities (which result in synaptic dysfunction; Nimchinsky,Sabatini & Svoboda, ) have been identified in Down, fragile X, Patau,Rett, and Williams syndromes (Chailangkarn et al., ; Irwin, Galvez &Greenough, ; Kaufmann & Moser, ). At the same time,functional specialization in one or more domains may be atypical in thesedisorders. For example, whereas music (vs. noise or rest) elicits reliable,robust, and focal activations in superior and middle parts of the temporallobe in TD adults, it elicits highly variable and diffuse activation in adultswith Williams syndrome that involves regions in the amygdala,cerebellum, and brainstem (Levitin et al., ).

Although more evidence is needed to establish a link between synapticabnormalities and protracted or atypical specialization, it is highlyprobable that synaptic disturbances affect development. This is becausesynapses enable neurons to communicate with one another. They are notfixed; rather, they are modifiable, constantly being created, pruned, andaltered throughout the lifespan. Although the development of neuronalcircuitry is constrained by epigenetic activity, the size, shape, number, andpattern of synaptic connections are governed by experience (Fiala, Spacek& Harris, ). Synaptic dysfunction could lead to sparser and lessreliable sampling of environment, and hence a worse signal-to-noise ratio,which in turn may result in protracted plasticity and atypical specializationof function (Rubenstein & Merzenich, ). Therefore, becauseindividuals with neurodevelopmental disorders present with synapticabnormalities, they may have difficulty sampling their environmentefficiently, and hence present with prolonged or atypical specializationearly in development.

Differences in sampling due to interactions between the external andinternal environments. Abnormal specialization in individuals with aneurodevelopmental disorder may not just be the result of individualdifferences at the genetic level, however. Atypically developing childrenalso develop within atypical environments. This can result fromstraightforward interactions; for example, a child with Williams syndromewho has difficulty reading may spend less time reading and thus receiveless linguistic input (fewer samples) than a TD child. But it can also resultfrom subtler interactions. For example, we have argued that the “momentthat a parent is informed that their child has a genetic disorder, theparent’s behaviour subtly changes . . . [and] as a result, the baby’sresponses within the dyadic interaction will also be subtly modified”(Karmiloff-Smith, D’Souza, et al., , p. ). In other words, a

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change at the genetic level may induce changes in the environment, whichmay have compounding effects on brain and cognitive development, whichwill affect gene expression and other gene–environment interactions. Wehave, for instance, observed that “parents of infants/toddlers with geneticsyndromes often find it difficult (compared with parents of TD infants) toallow their atypically developing offspring to freely mouth objects toexplore their properties with the sensitive nerve endings in the mouth orcrawl/walk uninhibited around the laboratory to fully discover theirenvironment” (Karmiloff-Smith, D’Souza, et al., , pp. –).Although the reticence of parents with vulnerable children isunderstandable, it will likely result in a less richly explored, less sampledenvironment.

Another example of how interaction between external and internalenvironments constrains sampling comes from two studies on Downsyndrome (DS). Whereas parents of TD children often use basic-levelcategory terms to label objects in naming (e.g. ‘bird’ for magpie),Cardoso-Martins and Mervis () found that the parents of five childrenwith DS were more likely to use the precise names of objects (e.g.‘magpie’). This difference between parental linguistic inputs may stemfrom the fear that a child with a neurodevelopmental disorder may neverlearn the correct names for objects. But different input may havedeleterious effects. For instance, Karmiloff-Smith, D’Souza, et al. ()suggest that initial overgeneralization encourages category formation (e.g.by calling different animals ‘bird’, the child starts to create an implicitanimal category) and children with neurodevelopmental disorders havedifficulty with category formation. It is important to note, however, thatCardoso-Martins and Mervis () studied only five child–mother dyadswith DS, and also they did not establish a causal relationship betweenmaternal labelling behaviours and children’s language development (seeRondal & Docquier, , for a critical review). Nevertheless, unconsciousassumptions about what an atypical child can and cannot learn may leadparents to provide less variation in linguistic input (fewer samples) andthus a more impoverished linguistic environment. Indeed, a more recentstudy provides evidence that maternal input addressed to fourteen-month-olds with DS is simpler (contains fewer function words andmore onomatopoeic words/routines) than that addressed to twenty-eightTD controls matched on lexical skills (Zampini et al., ). Although itremains to be investigated whether children with DS may in fact benefitmore from simpler input, the study demonstrates how interaction betweenexternal and internal environments alters the frequency and quality oflinguistic input, which may constrain development by changing thelearning environment. Furthermore, because the cognitive and linguisticprofiles of children with neurodevelopmental disorders are often uneven




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(e.g. Karmiloff-Smith, Broadbent, et al., ), genetic vulnerabilities maymake it more difficult for caregivers to accurately assess their child’sdevelopmental level and adjust their expectations and input accordingly.This may especially be the case because neurodevelopmental disordersoften affect expressive language more than receptive language in infants/toddlers (e.g. D. D’Souza, ), and parents often tell us that expressivelanguage is easier to assess than receptive language, which hints at thepossibility that they are underestimating their child’s receptive languageability.

Learning

Accumulating samples is essential for adaptive behaviour, because an infantcan only adapt to the external world by gathering information about it.However, for the information to be useful, the infant must also be able tounderstand or extract structure from the samples. For example, they mustlearn to extract patterns (units of speech) from the continuous streams ofsound they hear. In the following sections, we discuss two importantlearning mechanisms in infancy: (i) habituation and (ii) statistical learning.

Habituation. Arguably, the most basic learning mechanism available to thehuman infant for proactive exploration is habituation. Habituation is anadaptive process by which the infant familiarizes itself with, and graduallybuilds up an internal representation of, an external stimulus (Rankin et al.,; Sokolov, ). Over repeated successive presentations of thestimulus, the internal representation comes to represent the stimulationincreasingly well, the stimulus becomes less relevant to the infant, andnovelty-seeking behaviour is triggered (see Sirois & Mareschal, , for abiologically plausible computation model of habituation to the familiar andnovelty preference). How might this relate to language? Habituation maybe a core mechanism by which the perinatal brain discriminates languagesand starts specializing to its language environment (Werker &Byers-Heinlein, ). Habituation measures are also believed to indexquality or speed of cognitive processing in infants (Colombo & Mitchell,; Colombo, Shaddy, Richman, Maikranz & Blaga, ), andcognitive processes are critical for learning – including word learning.Indeed, a large body of evidence suggests that habituation patterns ininfants predict developmental outcomes in language comprehension andproduction (Ruddy & Bornstein, ; Tamis-LeMonda & Bornstein,), as well as general intelligence (Bornstein & Sigman, ; Kavšek,; McCall & Carriger, ; Rose, Slater & Perry, ). For example,in the visual domain, Tamis-LeMonda and Bornstein () presentedthirty-seven typically developing -month-olds with a series of facestimuli. The mean duration of the infant’s first two looks constituted a

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baseline, and stimulus presentations continued until the infant had reached ahabituation criterion of two consecutive looks each less than % of thatbaseline. The researchers found that shorter baselines (the start level ofhabituation), steeper slopes (the decline in attention), and lower decrementscores (the asymptote of habituation) predicted better languagecomprehension (the number of words flexibly understood across contexts)at months. In the auditory domain, Choudhury and Benasich ()presented twenty-eight TD -month-olds with consecutive pairs of tones,of which % were ‘standard’ – Hz pairs and % were ‘deviant’– Hz pairs. In this auditory oddball paradigm, the auditory systemstarts to habituate to the consecutively presented standards, a process thatis punctuated at random intervals by presentation of the infrequentdeviant and resultant ‘mismatch’ brain response. Auditory evokedpotentials (AEPs) predicted language abilities at and months of age.Specifically, infants with larger and sharper (more transient) ‘mismatch’AEPs in response to the deviant stimuli had better receptive andexpressive language scores (measured using the Preschool Language Scale[Zimmerman, Steiner, & Pond, ] and Clinical Evaluation of LanguageFundamentals [Wiig, Secord, & Semel, ]).

Individual differences in habituation mechanisms may therefore constrainlanguage development. This may also be the case for children withneurodevelopmental disorders. Although no study has hitherto reported anassociation between variation in habituation and language development inatypically developing children, Guiraud et al. () found that auditoryevoked potentials to repeated (non-speech) sounds decrease over time intwenty-one TD infants but not in thirty-five infants at high risk ofdeveloping autism, which indicates impaired habituation. Furthermore,using an auditory oddball paradigm similar to the one described above,D. D’Souza () found that AEPs to repeated (speech) sounds are alsoatypical in Down syndrome, fragile X syndrome (FXS), and Williamssyndrome (WS): mismatch AEPs in response to deviant speech soundswere identified in TD infants (N = ) but attenuated in infants at highrisk of developing autism (N = ) or with DS (N= ), FXS (N = ), orWS (N = ). Although we have yet to relate these brain data to thelanguage data we collected from these children, the neurocognitiveprocesses indexed by mismatch AERs trigger novelty-seeking attentionalprocesses, such as the ‘P’ attentional orienting brain response, which weknow (i) is atypical in these particular children, and (ii) is significantlycorrelated with vocabulary size (especially in fragile X syndrome; seesection below on ‘Reallocating attention’ for details on the link betweenthe P and language ability). Finding the optimal balance betweenbuilding useful representations of the external world and exploring it iscritical for adaptive behaviour. If children with neurodevelopmental




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disorders require more time to consolidate their knowledge (due to impairedhabituation mechanisms), then they will have less time to proactively exploreand sample new information from their environment, which may also affecttheir language development.

Statistical learning. Another learning mechanism is STATISTICAL LEARNING,the process by which infants identify, and track over time, patterns insensory information. These patterns range from frequency count (‘thereare more sweets in the blue box than in the red one’), through frequencyof co-occurrence (‘mum often appears when I cry’), to conditionalprobability (‘bed-time is more likely to follow bath-time thandinner-time’) (Romberg & Saffran, ). They also differ in complexity(e.g. simple geometric shapes vs. complex faces) and concreteness (e.g.changes in pitch vs. syntactic categories) (Romberg & Saffran, ).Importantly for the field of language development, Saffran, Aslin, andNewport () demonstrated that -month-olds could discern recurrentsyllable sequences from syllable strings spanning word boundaries byattending to statistical regularities called TRANSITIONAL PROBABILITIES (theconditional probability of Y given X in the sequence XY). Sincepublication of that seminal paper, researchers have discovered that evensleeping neonates are sensitive to the statistical structure of fluent speech(Teinonen, Fellman, Näätänen, Alku & Huotilainen, ) and that manydifferent types of sequences can be learned (e.g. AcB, where c is anelement that can vary; Hsu & Bishop, ).

Although Saffran et al. () argued that statistical learning is the processthrough which infants segment words from fluent speech (a critical step inlanguage acquisition), they had in fact only demonstrated that-month-olds could distinguish between sound sequences of varyinginternal coherence (high vs. low transitional probability). Questionsremained unanswered, which prompted further research. For example,how do infants go from discriminating sound sequences of varyinginternal coherence to identifying words? Does their sensitivity to differentlevels of speech input (phonemes, syllables, onset, rime, lexical stress,prosody, grammatical structure, semantics, etc.) change overdevelopmental time? What process determines which statistics are used(frequency count, frequency of co-occurrence, mutual information, etc.)?It turns out that infants actually use a range of mechanisms to combineand extract structure from multiple sources of information – which is whyattentional processes (see ‘The role of attention in sampling’ sectionbelow) are so important (Kirkham, Slemmer & Johnson, ). For

An important part of habituation (and other learning mechanisms) is memory, which is alsoimpaired in infants with neurodevelopmental disorders (e.g., Down syndrome; Edgin,).

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example, by – months, infants use both prosodic information andstatistical information (e.g. transitional probabilities) to segment thespeech stream, but give more weight to the former (Echols, Crowhurst &Childers, ; Jusczyk, Houston & Newsome, ; Morgan & Saffran,). In other words, they segment speech at the boundary before strongsyllables, and group together syllables that frequently co-occur as long asthey do not cross a prosodically defined boundary. By · months, theweighting changes, with more emphasis on distributional, allophonic, andphonotactic cues than on prosody. Furthermore, Graf Estes, Evans,Alibali, and Saffran () found that -month-olds use distributionalinformation to create internal representations, which serve as ‘candidatewords’ that they can later map onto objects. In other words, children donot merely track patterns in the speech stream; they use the statisticalinformation to learn words and word meanings (Lany & Saffran, ;Saffran & Wilson, ; Sahni, Seidenberg & Saffran, ; Thiessen &Saffran, ).

What about statistical learning in atypical populations? This question hasrarely been examined to date. One study found that a group of nineteentoddlers with Williams syndrome (mean chronological age was months;mean mental age was months) had difficulty with speech segmentation;they could detect bisyllabic words with a strong–weak stress pattern (e.g.doctor) but not a weak–strong one (e.g. guitar) – even though a typicallydeveloping infant can do this by · months (Nazzi, Paterson &Karmiloff-Smith, ). A more recent paper found that a group of eighteen- to -month-old children with WS successfully demonstrated statisticallearning of transitional probabilities in continuous speech (Cashon, Ha,Estes, Saffran & Mervis, ). However, the mean chronological age of thechildren was · months and the study did not include a control group, soit is impossible to know whether statistical learning was typical or atypical(i.e. whether onset of statistical learning was developmentally late and/orwhether rate of development was slow). More research is clearly needed inthis domain.

The role of attention in sampling

Another problem that individuals with neurodevelopmental disorders mayhave – apart from extracting structure – is inadequate sampling as a resultof not focusing on relevant aspects of the environment. Previously, wehighlighted the need for infants to redirect their attention away from, say,featureless ceilings to speaking faces, or for infants to focus on changes inspeech sounds rather than pitch (see above). If infants fail to allocateattention appropriately, then they may miss important social cues andlinguistic input, which would make it harder for them to develop




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language. In the following two subsections, we review evidence of twoimportant attentional precursors to language acquisition: the ability to (i)reallocate attention, and (ii) attend to multiple sources of information andintegrate them.

Reallocating attention. Typically developing infants adapt to theirenvironment in part by learning how to shift the focus of their processingresources to the relevant aspects of a scene (Kanwisher & Wojciulik, ).This is important because it allows detailed analysis of relevant stimuli,while filtering out irrelevant (distracting) stimuli. A child who can flexiblyselect and attend to things in their environment, and use this ability toguide action, will interact with (and thus experience) the world differentlythan a child with an attentional deficit. As a consequence, irregularities inattention may have deleterious effects on development.

For example, some evidence suggests that an important attentionalprecursor of language development is TRIADIC INTERACTION, which is whena parent uses eye-contact and eye-gaze to direct their child’s focus ofattention to an object or event of interest (Brooks & Meltzoff, ;Morales, Mundy & Rojas, ; Mundy & Gomes, ; Trevarthen &Hubley, ; but see Yu & Smith, , for evidence that toddlers aremore likely to follow their parent’s hands than eyes, and that theinteraction is between equals rather than the parent taking the lead).Triadic interaction requires the infant to orient to speech sounds andflexibly shift their attentional focus between visual stimuli (the caregiverand an object of interest). TD infants learn to do this from as early as

months of age, developing robust triadic interaction skills by months(Striano & Stahl, ). However, the literature hints that triadicinteraction is impaired in at least some neurodevelopmental disorders. Forexample, Laing et al. () found that a group of eleven toddlers withWilliams syndrome (and a mean age of months) followed pointingbehaviour less frequently than a group of eleven TD infants matched onmental age ( months). Also, whereas pointing precedes speechproduction and is predictive of early vocabulary development in TD(Bates, Benigni, Bretherton, Camaioni & Volterra, ; Butterworth,), it appears after speech production in WS (Mervis & Bertrand,). In a longitudinal study of ten children with WS, Mervis andBertrand found that the children did not produce referential pointinggestures until well after the onset of language. Furthermore, they did notrespond appropriately to their mothers’ pointing gestures, even thoughthey were beginning to speak referentially. Directing and followingattention via pointing may therefore be under-utilized in WS. It is alsopossible that poor saccadic control in children with WS (Brown, Johnson,Paterson, Gilmore, Longhi & Karmiloff-Smith, ) affects gazefollowing (and hence may negatively impact language development).

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Although preliminary eye-tracking data from our lab tentatively suggest thata group of nine - to -year-olds with WS (and a mean age of months anda mean verbal age of months) MAY be able to follow gaze (unpublishedobservations), gaze following and its relationship to word learning has yetto be investigated in younger children with WS.

To further investigate how attention and language are related, wecompared attentional processes, and their relation to language ability, inTD -month-olds (N = ) with chronological- and mental-age-matchedinfants/toddlers who either had a neurodevelopmental disorder(Down syndrome [N = ], fragile X syndrome [N = ], Williamssyndrome [N = ]) or were at high risk of developing autism (N = )(D. D’Souza, ). The study included an eye-tracking version of theGAP-OVERLAP TASK (adapted from Atkinson, Hood, Braddick & Wattam-Bell,), which measures how quickly the participant DISENGAGES from, SHIFTS

to, and ENGAGES with visual stimuli. These children also participated in apassive auditory oddball experiment, where continuous electroencephalogram(EEG) was recorded from the infant while speech sounds (% standards,% speech deviants, % pitch deviants) were presented in the background(one every ms). We found that the chronological- and mental-age-matched children with DS were slower than the TD controls atdisengaging attention from a visual stimulus, while the chronological- (butnot older mental-) age-matched infants with WS were slower at engaging (orfully processing) a visual stimulus. Also, both chronological- andmental-age-matched children with WS were slower at shifting visualattention. Moreover, the electrophysiological response to speech sounds wasabnormal in all the atypically developing groups (and in the ‘at high risk ofdeveloping autism’ group) in one or more stages of processing: encodingauditory stimuli, discriminating between speech sounds, and orienting tochanges in speech sounds (vs. pitch). For example, the electrophysiologicalresponse that typically indexes ‘sound encoding’ did not significantly differbetween stimulus types (standards, speech deviants, pitch deviants) in any ofthe groups – except the TD control group.

How did the attentional measures we collected relate to language ability?Across all groups, infants/toddlers who were better at disengaging visualattention and/or showed a larger attentional orienting brain response tochanges in speech sounds had relatively large vocabularies (though it isimportant to note that the [statistically significant, medium-sized] effect ofdisengagement was largely driven by the TD control group, unlike the[medium-sized] effect of orienting which was highly significant across all

Stages of processing were not directly tested in this particular study but were inferred fromthe event-related potential (ERP) components established in previous research (seeD. D’Souza, , for details).




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groups). Between-group differences were also identified. For example, thetoddlers with FXS (mean chronological age = months) who had arelatively small orienting response (measured using the event-relatedpotential technique) had a significantly smaller expressive vocabulary size(equivalent only to TD -month-olds) than those who had a relativelylarge orienting response (expressive language equivalent to TD-month-olds). This relationship did not reach significance in the DSgroup. However, for children with DS (mean chronological age =

months), those who were relatively poor at disengaging attention had asignificantly smaller expressive vocabulary size (equivalent only to TD-month-olds) than those who were relatively good at disengagingattention (expressive language equivalent to TD -month-olds). Thisrelationship did not reach significance in the FXS group. Together, thesedata suggest at least two mechanisms for acquiring good language skills,one more relevant to FXS (social orienting), and one more relevant to DS(visual disengagement). We speculate that disengaging and shiftingattention facilitates exploration, which affects language development (seesections on ‘Social interaction’ and ‘Embodiment’ below), and thatshifting attention towards changes in speech sounds (measured using ERP)also contributes to language development.

Attending to and integrating multiple sources of information. However, foroptimal learning, not only must an infant orient to a speaking face, theymust also look at the relevant parts of the face (e.g. the eyes [forgaze-following] or mouth [for disambiguating speech sounds]) andintegrate visual and auditory information. For example, watching lipmovements influences auditory (speech) perception (Alsius, Navarra,Campbell & Soto-Faraco, ; Burnham & Dodd, ; Kushnerenko,Teinonen, Volein & Csibra, ; McGurk & MacDonald, ;Rosenblum, Schmuckler & Johnson, ) and facilitates word learning(Teinonen, Aslin, Alku & Csibra, ). Visual cues may be particularlyuseful for speech perception under noisy conditions (Sumby & Pollack, ).

Could language delay in children with neurodevelopmental disorderspartly result from a deficit in integrating auditory and visual information?To find out, we used an eye-tracker to measure auditory-visual (AV)speech integration in ninety-five infants/toddlers with Down syndrome,fragile X syndrome, or Williams syndrome, whom we matched on eitherchronological or mental age to twenty-five TD -month-old controls(D. D’Souza, D’Souza, Johnson & Karmiloff-Smith, ). In thiswithin-subjects design, the participants were presented with two faces. Inone condition (Mismatch), the participants heard /ga/ while one facesilently mouthed ‘ga’ (congruent) and the other face silently mouthed ‘ba’(incongruent). The other condition (Fusion) was identical in all respectsexcept the participants were presented with the sound /ba/ rather than /ga/.

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We predicted that TD infants would discriminate between the congruent andincongruent faces in the Mismatch condition with their looking behaviour,because when participants hear /ga/ and see ‘ba’, they perceive amismatch – a combinatorial percept such as /bga/. We also predicted thatTD infants would not visually discriminate between the congruent andincongruent faces in the Fusion condition, because the sound /ba/ and sight‘ga’ fuses into the syllabic percept /da/ (the MCGURK EFFECT; McGurk &MacDonald, ), and participants with strong AV speech integrationskills would demonstrate a McGurk effect and therefore not discriminatebetween the faces because there is nothing to distinguish one syllabicpercept (/da/) from the other (/ba/). The TD controls showed the expectedoutcome. However, we found no evidence of AV speech integration ineither the chronological- or mental-age-matched atypically developinggroups (D. D’Souza, D’Souza, Johnson, & Karmiloff-Smith, ).Moreover, whereas AV speech integration predicted receptive languageability in the TD controls, it did not in any of the atypically developinggroups (D. D’Souza, D’Souza, Johnson, & Karmiloff-Smith, ).

Why would AV speech integration not predict language ability in theneurodevelopmental disorders? We explored the possibility that the atypicallydeveloping children were fixating on the wrong parts of the face. We foundthat, when presented with a speaking face that mouthed a different syllablefrom the one they could hear, the TD infants (N= ) with a relatively largevocabulary made more fixations to the mouth than eyes, while the toddlerswith FXS (N= ) or WS (N= ) and a relatively large vocabulary focusedmore on the eyes than mouth (D. D’Souza, D’Souza, Johnson &Karmiloff-Smith, ; see D. D’Souza, Cole, et al., , for more evidencethat toddlers with WS process faces atypically). In DS (N= ), by contrast,fixations to the speaker’s overall face (rather than to the mouth or eyes)predicted vocabulary size (D. D’Souza, D’Souza et al., ). This surprisingresult warrants further investigation. However, it suggests that children withthese neurodevelopmental disorders are not using visual speech cues tobootstrap their acquisition of language in the same way as TD infants.

BEYOND COGNITION: OTHER DEVELOPMENTAL CONSTRAINTS ON

LANGUAGE ACQUISITION

As shown above, under tightly controlled experimental conditions infantsdemonstrate an ability to assimilate information in ways that facilitateword learning. However, it is possible that they learn words in verydifferent ways outside the laboratory. This is because different affordancesmay result in different adaptive behaviours, with some behaviours moreoptimal in the unfamiliar, tightly constrained, simplified environment ofthe laboratory, and others more optimal in the familiar but complex and




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dynamic environment of the home. What constrains language developmentoutside the laboratory? In the following sections, we review evidence thatlanguage acquisition is constrained (among other things) by (i) socialinteraction and (ii) the infant’s physical body.

Social interaction

Understanding language within complex natural environments may requiredifferent skills than the ones that are identified in intramural studies.There is some evidence to suggest that extracting linguistic structure fromthe environment requires social interaction: Nine-month-old Americaninfants experienced twelve sessions of an unfamiliar language (Mandarin)through either live interaction with a Mandarin speaker or identicallinguistic information from the same speaker but delivered via a televisionor audiotape (Kuhl, Tsao & Liu, ). The American infants exposed toMandarin in the live interaction condition could discriminate Mandarinphonemes similarly to age-matched Chinese Mandarin monolinguals. Thisshows that -month-olds can learn and/or retain their early ability tobetter discriminate non-native contrasts. However, the American infantsexposed to Mandarin in the television and audiotape conditions failed tobetter discriminate between Mandarin phonemes than a group ofage-matched American controls who had been exposed only to English.

Kuhl et al.’s () data suggest that social interaction is important forlanguage learning (even if it is unnecessary for simpler statistical learningtasks presented in experimental situations; e.g. Saffran et al., ). Thereare parallels of this in the non-human animal literature. For example, theyoung male zebra finch needs to see or physically interact with a ‘tutor’ birdto learn song (Adret, ; Eales, ). Moreover, the song crystalizesduring a sensitive period of early life, but a recent study found that thissensitive period could be extended through social interaction(Derégnaucourt, Poirier, Van der Kant, Van der Linden & Gahr, ). Inthe study, after learning a song, young male zebra finches were moved to acommon aviary where they could freely interact with other males. Zebrafinches that had poorly imitated their song model during the sensitiveperiod were more likely to change their song than zebra finches that hadimitated their song model well. This highlights the importance of live socialinteraction on song learning in zebra finches. But what mechanismsunderpin ‘social learning’ in the human infant? The zebra finch offers aclue. Preliminary data suggest that it imitates song better when its tutor isfacing it (Ljubičić, Bruno & Tchernichovski, ). Perhaps an attentivetutor increases attention and arousal in the learner, enhancing its ability tolearn and memorize information. Indeed, Yu and Smith () found thathuman infants extend their sustained attention to an object when a parent

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attends to the same object. Kuhl () suggests that social learning mayfacilitate language acquisition by increasing attention/arousal and/orproviding additional sources of information (e.g. eye-contact, confirmatoryglances from the instructor).

Another example of how social interaction constrains language developmentcomes from Karmiloff-Smith, Aschersleben, de Schonen, Elsabbagh,Hohenberger, and Serres (). In this study, -month-old infants weretested on their ability to process speech, faces, and actions/events. Theywere also observed and videotaped for minutes as they played with theirmothers, and the quality of each mother–infant dyadic interaction wasrated. The infants were tested again at months. At the group level, theinfants displayed all of the expected effects found in previous research (e.g.the infants could discriminate both native and non-native contrasts at

months, but only native contrasts at months). However, whenKarmiloff-Smith and colleagues divided their data according to the mother–child interaction ratings, they found that the -month-old infants of highlysensitive (vs. controlling or unresponsive) mothers seemed to show earlierspecialization for the sounds of their native language (i.e. they failed tosignificantly discriminate between the non-native contrasts). One mightexpect that interactions high on sensitivity would foster child developmentacross cognitive domains generally. However, this was not the case. Theinfants from dyads highly rated for their sensitivity were in advance of theirpeers in speech processing at months and in processing physical events at months, but were actually worse at processing human goal-directedactions than infants who were judged to be compliant and who also hadmoderately controlling mothers. Karmiloff-Smith et al. () suggestedthat by imposing their own choice of toy on their infants and changing thetoys without showing sensitivity to the infants’ current focus of attention,the controlling mothers forced their compliant infants to frequently processtheir mothers’ goals rather than their own goals, leading to an advantage inunderstanding others’ goal-directed actions. Karmiloff-Smith et al., alsosuggested that, while sensitive mothers provide their infants withappropriate level linguistic input, controlling mothers speak less and are lesslikely to take into account the progressively changing nature of their child’svocalizations, leading to the differences in language development betweenthe two groups of infants. And whereas sensitive mothers leave their infantssufficient time to fully explore (and learn about) the properties of objects,controlling mothers are more likely to interrupt their infants’ exploration of

Kuhl () also suggests that social learning may facilitate language acquisition byactivating brain areas (e.g., ‘mirror neurons’ in Broca’s area; Kilner, Neal, Weiskopf,Friston, & Frith, ) that couple speech perception and action (Meister, Wilson,Deblieck, Wu, & Iacoboni, ). However, this would not by itself explain why infantslearn better from watching live instructors than instructors on television.




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objects and offer them a succession of new toys, leading to differences in theirinfants’ ability to process physical events (Karmiloff-Smith et al., ). Ofcourse, these hypotheses need to be empirically tested, and we do notactually know whether the children were compliant (passive) because theirmothers were moderately controlling, or whether the mothers displayedcontrolling behaviours because their children were compliant, or whetherthere is a different explanation. Nevertheless, the data indicate thatdifferences in dyadic interaction are associated with differences in languagedevelopment.

Motivated by the observations of Karmiloff-Smith et al. (), wemeasured various aspects of dyadic interaction in parent–infant dyads withDown syndrome or Williams syndrome. The first phase of ourinvestigation found that, relative to eight chronological-age-matched TDdyads, sixteen dyads with DS or WS infants are lower in mutuality andengagement, parent responses are more controlling (directive) and lesssensitive, and infants are less attentive to their parents and show less jointactivity (Soukup-Ascençao, D’Souza, D’Souza & Karmiloff-Smith, ).However, because parents are not necessarily intrinsically directive orsensitive, but adapt to their child’s cognitive and linguistic characteristics(Hodapp, ), the second phase of our study will compare the DS/WSdata with data from mental age (MA) matched TD infants and theirparents. Because both syndromes present with uneven cognitive and socialprofiles (Karmiloff-Smith, Broadbent, et al., ; Moore, Oates, Hobson& Goodwin, ), it is reasonable to expect that these atypicalities will yielddifferent parental responses within the dyad in comparison to the parents ofTD MA-matched infants (Hodapp, ). However, atypical parenting stylesare not necessarily detrimental to infants with neurodevelopmental disorders;they could reflect adaptive processes and in fact facilitate languagedevelopment. For example, it is possible that atypically developing infantsmay be more passive and thus require (and benefit from) more direction fromtheir caregivers than typically developing infants. Therefore, in our futureresearch, we are planning to link our parent–infant interaction measures withmeasures such as spontaneous exploration, visual attention, AV speechintegration, and vocabulary size, to better understand how these complexsocial interactions constrain language development.

Embodiment

Most studies on early language development (including many of thosereviewed above) assume that the infant has the near-impossible task of

We are planning to collect these (and other measures) from a longitudinal sample of thirty-five children with Williams syndrome: <https://www.researchgate.net/project/Early-processes-that-impact-later-development-in-Williams-syndrome>.

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having to extract structure by flexibly selecting and attending to things inrelatively unconstrained, dynamically complex, cluttered, multimodalcontexts. Attentively orienting to, disengaging from, shifting between, andengaging with various spinning toys, unpredictable sounds, eyes, mouths,and pointing behaviours, etc., can be challenging for infants (Kannass,Oakes & Shaddy, ; Lansink, Mintz & Richards, ; Ruff, Capozzoli& Weissberg, ; Ruff & Lawson, ), but the learning space may notbe as unconstrained as many researchers assume. Learning is partlyconstrained by the environment, such as when the fetus hears its mother’svoice but low-pass filtered through amniotic fluid, accentuating therhythmic structure of speech (Smith, Gerhardt, Griffiths, Huang &Abrams, ). But also, the learner’s body constrains access tomoment-to-moment sensory information, and in this way guides learning.For example, the neonate’s short eyesight may restrict visual exploration toonly the most salient features of an object; the infant’s short arms mayrestrict exploration to only one object at a time; the toddler’s short legsmay restrict exploration to only part of a scene.

Furthermore, whereas researchers have focused on finding cognitivesolutions to word learning problems such as referential ambiguity in earlyobject naming (e.g. Xu & Tenenbaum, ), Pereira, Smith, and Yu() found that the occurrence of such ambiguous events might belimited by the sensorimotor constraints that underpin real-timefree-flowing interactions. Specifically, they used a head-mounted camera torecord gaze data from toddlers as they played with novel objects, and asthe parent spontaneously named them. The toddlers were later tested toascertain whether they had learned the names of the objects. This enabledthe researchers to identify the properties of visually optimal moments fortoddlers to learn the labels of objects: the toddlers learned best when thenamed object was visually larger and more centred than other objects, andwhen that visual advantage was sustained for several seconds before andafter the naming event. This suggests that learning is constrained by thesensory properties of naming moments. That is, from an adult-centricperspective, the number of possible meanings that a novel word in a novelscene may have is so great that it provides the infant with an almostinsurmountable problem of referential ambiguity, but research reflectingthe child’s perspective demonstrates that, during word learning, largenumbers of objects are not typically in view, and that factors like theinfant’s physical abilities or size of visual field constrain the problem space(Samuelson & McMurray, ). In other words, cluttered visual scenesmay provide the problem of referential ambiguity, but solutions that positlanguage-specific biases (e.g. Lidz, Waxman & Freedman, ), strategiesthat deductively or statistically narrow down the set of possible wordmeanings (e.g. Golinkoff & Hirsh-Pasek, ; Golinkoff, Mervis &




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Hirsh-Pasek, ; Xu & Tenenbaum, ), and/or social skills such asinferring others’ referential intent (e.g. Woodward & Markman, ),may be viable but are unnecessary; the active child creates moments ofminimal visual ambiguity (by bringing objects close to their face withtheir short arms; Smith, Yu & Pereira, ; Yu, Smith, Shen, Pereira &Smith, ), rendering the cognitive problem obsolete.

The flipside of Pereira et al.’s () findings is that they also point tovisual LIMITS on object name learning, which highlights the need forinfants to develop abilities that will enable them to learn in morechallenging environments. Changes in the ability to use one’s body (e.g.changes in posture, locomotion, object manipulation) help infants withthis. That is, they enable the infant to explore and experience the world innew ways (Iverson, ). For example, children who can more easily pickup toys (because they are wearing ‘sticky mittens’) are more likely to exploredifferent toys (Needham, Barrett & Peterman, ; cf. Williams, Corbetta& Guan, ), and the provision of toys for exploration is a significantpredictor of language development (Elardo, Bradley & Caldwell, ). Andby learning to walk, an infant can bring a distant object of interest to anadult who can subsequently label it (Karasik, Tamis-LeMonda & Adolph,). Indeed, in a longitudinal study of forty-four TD infants, Walle andCampos () found that acquisition of walking predicts vocabulary size(both receptive and expressive), and that vocabulary size (receptive,expressive) significantly increases as a function of walking experience,irrespective of chronological age. But not only do motor changes help thechild to sample more of its environment (and differently), they also requireand develop cognitive problem solving skills (Adolph, ). Moreover,they ‘prepare’ the child for talking and listening. For example, by sitting upwithout assistance, an infant can breathe more efficiently, maintainsubglottal pressure, and generate longer utterances in one breath (Iverson,). By bringing objects to an adult, the infant may increase the number,and extend periods, of social interactions, which provides opportunities tolearn important social behaviours such as turn-taking (Karasik et al., ;Walle & Campos, ). In a second observational study of forty-fourparent–infant dyads during a -minute free-play session (when parentslater reported that they did not remember they were being filmed), Walleand Campos () found that the more active (walking or crawling) infantshad larger receptive vocabulary sizes. They also found that, irrespective ofchronological age, various factors in the social environment predicted

Other factors that constrain the problem space include biases such as novelty preference (thechild is drawn to the most novel object in a context; Samuelson, Kucker, & Spencer, ;Samuelson & Smith, ) and social interaction (caregivers often label whatever the childis attending to; Tomasello & Todd, ).

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vocabulary size – in walking, but not crawling, infants. Specifically, walkinginfants who received more language input from the parent had largerreceptive and expressive vocabularies. Walking infants who spent more timeat a ‘medium’ distance from the parent (nearby but out of the parent’sphysical reach) had larger expressive vocabularies, perhaps because amedium distance encourages distal communication. And walking infantswhose parents moved around less frequently had larger receptive andexpressive vocabularies, perhaps reflecting better distal dyadiccommunication and less need for physical intervention from the parent.

If individual differences inmotordevelopment constrain language acquisitionin TD children, they have arguably an even greater effect on languagedevelopment in atypically developing infants with genetic vulnerabilities.Motor difficulties are present early in development across variousneurodevelopmental disorders. For example, infants with DS experiencehypotonia, joint laxity, and hypermobility (Ulrich & Ulrich, ). Andvarious motor skills, including walking, are delayed in DS. While the averageage of walking in TD children is months and the age range is from to

months, most children with DS only learn to walk between and years ofage – with some children unable to walk at years of age (Palisano et al.,). Even when children with DS learn a new motor skill, they tend topractise it less. For example, de Campos, da Costa, Savelsbergh, and Rocha() found that, even after onset of reaching, infants with DS (N= )produce significantly fewer spontaneous reaches than TD controls (N= ).This may constrain their exploration of objects (and require more input fromthe caregiver), which could further contribute to language delay. However,interventions can hasten the late onset of motor skills. For example, infantswith DS who underwent a home-based stepping training interventionachieved independent walking days earlier (on average) than infants withDS who had not taken part in the intervention (Ulrich, Ulrich,Angulo-Kinzler & Yun, ). We hypothesize that, because the motordomain does not exist in isolation (see above), early intervention in the motordomain may also have cascading effects on connected, interdependentdomains, such as language.

IMPLICATIONS, CHALLENGES, AND NEW DIRECTIONS: EMBRACING

COMPLEXITY

Several decades of infant research demonstrate that word learning isconstrained by multiple factors (some of which were discussed above)that range from the amount and quality of linguistic input they receive to

Social interaction and motor activity constrain sampling, learning, and attentionalprocesses during the waking day. But infants spend most of their time asleep




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the length of their arms. It is important to note, however, that arguably all ofthe developmental processes, domains, and levels of description discussed inthis paper are INTERCONNECTED. For example, habituation processes are likelyto constrain language development through learning andmemory, but also theyare yoked to attentional processes that trigger novelty-seeking behaviour, andconstrain exploratory behaviour (more time spent consolidating knowledgeis likely to result in less time exploring). Many of the developmentalprocesses, domains, and levels of description are also INTERDEPENDENT. Forexample, Down syndrome affects how an infant develops partly through thecomplex interactions the infant has with its parent; parenting constrains theinfant’s development, but the infant’s development affects parenting. Andbecause interactions between diverse, interdependent units give rise tonon-linear dynamics, in order to understand how the system develops wecannot study the components of the system in isolation. Understanding howinfants acquire language therefore necessitates multidisciplinary researchacross multiple interdependent domains (e.g. sampling, learning, attention),modalities (e.g. haptic, auditory, visual), and levels of description (from genesto social context) over developmental time.

Furthermore, to study how complex systems adapt to their environments,it is important to study them in their environment. Moreover, becauselanguage development is a probabilistic process, there are likely to bemultiple ways to an adaptive fit. Arguably, researchers should thereforeabandon attempts to find ONE developmental pathway to languageacquisition and instead identify co-varying factors that significantlyconstrain development. This is crucial if we want to understand how

(Iglowstein, Jenni, Molinari, & Largo, ). Do variations in sleep patterns impactlanguage development? In a study of sixty infants/toddlers with DS, FXS, or WS, andsixty age-matched TD controls, we found that sleep variables (e.g., sleep duration) areassociated with vocabulary size in typical and atypical development – especially in WS(D. D’Souza, D’Souza, Horvath, & Karmiloff-Smith, ). Sleep development and itsimpact on language in neurodevelopmental disorders will be an important area of focusin the future.

As a rough rule of thumb, the interaction of INDEPENDENT units gives rise to a normaldistribution and linear dynamics (e.g., if vocabulary size increases as a function ofmaturational age), while the interaction of INTERDEPENDENT units gives rise to a powerdistribution and non-linear dynamics (e.g., if language development increasesopportunities for social interaction, and social interaction facilities languagedevelopment) (Miller & Page, ).

An example of this is the London Down Syndrome Consortium, which seeks tounderstand the link between Down syndrome and Alzheimer’s disease, and comprisesclinicians, developmental psychologists, psychiatrists, cellular scientists, humangeneticists, and mouse geneticists. This example highlights one of the challenges ofembracing complexity: because it involves large numbers of variables, multiple methods,and experts at different levels of description, it requires the coordination of largemultidisciplinary collaborations and a shared theoretical perspective (H. D’Souza &Karmiloff-Smith, ).

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language development goes awry in infants with neurodevelopmentaldisorders.

How can we hope to understand language development if it requires anunderstanding of the multiple ways in which different but interdependentdomains, modalities, and levels of description interact with each other overdevelopmental time? Technological and methodological innovations willaid the process. For example, new or improving technologies such ashead-mounted eye-trackers for infants will enable more naturalisticstudies. And the increasing size and complexity of datasets collectedduring studies that, e.g. involve moment-by-moment gaze data fromeye-trackers mounted on the heads of infants as they explore their homeenvironment, are being paralleled by increases in computational power andthe development of tools that can store, catalogue, and analyze massivedatasets (see Arzi et al., , for discussion). These tools may also helpresearchers from around the world to share and collate data such as thespeech corpus contained within the Child Language Data ExchangeSystem (CHILDES), a central repository for language acquisition data, orthe digital data library (Databrary) which facilitates the sharing andrepurposing of video data. Creating a similar platform for data gatheredfrom infants with a neurodevelopmental disorder would enable us torepurpose data and gain more insight into how learning happensmoment-by-moment in these often difficult-to-study populations.

Theoretical and conceptual advancements are also important because theyguide what scientists decide to study and how they study it (H. D’Souza &Karmiloff-Smith, ). Furthermore, they lead to better explanatory andpredictive models of language development, and can shape social practice,education, and intervention. Take intervention, for example. To tacklelanguage delay in children with neurodevelopmental disorders,paediatricians often target the purported malfunctioning ‘languagemodule’ with specific outcomes in mind, such as teaching the child toproduce a set of words. However, the developmental studies discussed inthis paper suggest that, because language emerges gradually from theinteraction of many diverse interdependent units over time, any delay maybe the result of cascading effects of early impairments in non-linguisticdomains (e.g. in selective attention). In this case, successful interventionwould require targeting mechanisms and domains that are not necessarilydirectly related to the language domain and which could be on differentlevels of description (e.g. emotional dysregulation). Moreover, because thechild is a complex adaptive system, timely intervention is likely to becritical (D. D’Souza & Karmiloff-Smith, ). That is, teaching a child

The developmental trajectory of a complex adaptive system is largely dependent on its firstfew ‘steps’ (PATH DEPENDENCE; Miller & Page, ).




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to learn words may be particularly challenging if the child has not, forexample, developed adequate oro-motor abilities. Furthermore, becausethe child is a complex adaptive system, rather than attempt to restructureone particular domain such as language (e.g. by providing the child withmore language lessons), it would be better to focus on creating anenvironment for optimal learning. This may involve various strategiessuch as keeping the child on the edge of the boundary betweenconsolidating knowledge (e.g. allowing the child time to process astimulus) and searching for new knowledge (e.g. providing the child withnovel stimuli). In other words, new theoretical perspectives view the childas a complex adaptive system and suggest that it would be best to gain anunderstanding of, and build interventions around, the interdependency ofvarious factors.

CONCLUSION

We have reviewed evidence for the existence of several diverse, interacting,interdependent (linguistic and non-linguistic) constraints on languagedevelopment. This evidence suggests that many aspects of language areconstructed piecemeal via the complex and dynamic interactions of partswithin the infant as well as between the infant and its social and physicalenvironments. Language delay is at least in part due to variations in theseconstraints. Future research on language development should therefore notonly focus on single cues (e.g. prosodic patterns, stress patterns, the socialcontext of the interaction) or on single domains (e.g. attention, learning,social interaction); it should integrate data from different domains andlevels of description. These cues/domains are neither individuallysufficient nor independent of each other, but rather they are used incombination to constrain the learning space and allow probabilisticknowledge to emerge. Future studies should therefore investigate howinfants integrate multiple sources of information in naturalistic contextsand across developmental time. This may lead to a better understanding oflanguage development and, critically, lead to more effective interventionsfor cases when language develops atypically.

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