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Critical Period in Brain Development: Definition, Importance

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• When Does the Critical Period Begin and End?
• The Critical Period Hypothesis—What It States
• What Happens to the Brain in the Critical Period?
• What Kind of Events Impact the Brain During the Critical Period?
• How Do Adverse Events Impact the Brain?
• What's the Difference Between a Critical Period and a Sensitive Period?
• What Happens to the Brain When the Critical Period Ends?

The critical period in brain development is an immensely significant and specific time frame during which the brain is especially receptive to environmental stimuli and undergoes a series of rapid changes. 

These changes have lifelong effects as essential neural connections and pathways are established, playing a vital role in cognitive, emotional, and social development. 

This article will explore the timeline, impacting events, and subsequent consequences of the critical period on brain development. It also explores the distinction between critical periods and sensitive periods and what happens to the brain once the critical period ends.

When Does the Critical Period Begin and End? 

The starting point of the critical period is at conception. The brain starts to form and develop from the moment you are conceived. During pregnancy, a baby's brain is already beginning to shape itself for the world outside. The brain is gearing up and getting ready to absorb a massive amount of information.

The Early Years of a Child's Life

Once the baby is born, the brain kicks into high gear. The early years of a child's life, from birth to around the age of five, are generally considered the core of the critical period. The brain is incredibly absorbent during these years, taking in information rapidly. Everything from language to motor skills to social cues is being learned and processed extensively.

Different aspects of learning and development have different critical periods. For instance, the critical period for language acquisition extends into early adolescence. This means that while the brain is still very good at learning languages during early childhood, it continues to be relatively efficient at it until the teenage years.

The brain is incredibly absorbent during these years, taking in information rapidly. Everything from language to motor skills to social cues is being learned and processed extensively.

Vision Develops During This Period

On the other hand, for certain sensory abilities like vision, the critical period might end much earlier. This means that the brain is most receptive to developing visual abilities in the first few years of life, and after that, it becomes significantly harder to change or improve these abilities.

The Critical Period Hypothesis—What It States 

The brain has a certain time window when it's exceptionally good at learning new things, especially languages. This window of time is what is referred to as the "critical period."

Younger People Learn Languages Faster Than Older People

Eric Lenneberg, a neuropsychologist, introduced the Critical Period Hypothesis. He was very interested in how people learn languages . Through his observations and research, Lenneberg noticed that younger people were much more adept at learning languages than older people. This observation led him to the idea that there is a specific period during which the brain is highly efficient and capable of absorbing languages.

As You Age, It Becomes More Difficult to Absorb New Information

If the critical period is a wide open window in the early years of life, allowing the brain to take in an abundance of information quickly and efficiently, as time progresses, this window begins to close gradually. As it closes, the brain becomes less capable of easily absorbing languages.

This doesn't mean that learning becomes impossible as you age; it merely indicates that the ease and efficiency with which the brain learns start to decline.

What Happens to the Brain in the Critical Period? 

During the critical period, the brain experiences explosive growth. Let's take a look at some of the changes that happen in the brain during the critical period.

Neurons Form Connections

In the early stages, neurons in the brain start to form connections. These connections are called synapses.

Synapses are bridges that help different parts of the brain communicate with each other. In the critical period, the brain is building these bridges at an incredible pace.

Neuroplasticity Strengthens Brain Connections

As a baby interacts with the world, certain connections strengthen while others weaken. For instance, if a baby hears a lot of music, the parts of the brain associated with sounds and music will become stronger. This process of strengthening certain connections is known as brain plasticity because the brain molds itself like plastic.

Attachment to Primary Caregivers

An essential aspect of the critical period is the development of attachment to caregivers. During the early months and years, babies and toddlers form strong bonds with the people caring for them .

These attachments are critical for emotional development. When a caregiver responds to a baby's needs with warmth and care, the baby learns to form secure attachments . This lays the foundation for healthy relationships later in life.

What Happens When Children Are Not Given Attention?

What if a child is not given the attention and care they need during the critical period? This is a significant concern. Without proper attention and stimulation, the brain doesn't develop as effectively. The bridges or connections that should be built might not form properly. This can lead to various issues, including difficulty forming relationships, emotional problems, and learning difficulties.

When a child is given proper attention, stimulation, and care during the critical period, their brain thrives. The connections form rapidly and robustly. This sets the stage for better learning, emotional regulation, and relationship-building throughout life.

What Kind of Events Impact the Brain During the Critical Period? 

When a child is exposed to a rich, stimulating environment where they can play, explore, and learn, it tremendously impacts the brain. Engaging in interactive learning, being read to, and having supportive relationships with caregivers can significantly contribute to a well-developed brain.

Events such as abuse, neglect, head trauma , or extreme stress—collectively known as adverse childhood experiences (ACEs)—can be detrimental to brain development. These adverse events can impede the formation of neural connections and lead to behavioral, emotional, and cognitive difficulties later in life. "Unfortunately, disruptions to normal brain development due to environmental influences such as poverty, neglect, or exposure to toxins can cause lasting damage. This is why it is so important for children to receive adequate nutrition, stimulation, and parental care during these first few years of life; without it, they may suffer developmental delays and other issues that could potentially be avoided with proper attention,"  Harold Hong, MD , a board-certified psychiatrist says.

How Do Adverse Events Impact the Brain? 

When a child is neglected or abused, stress can impact how their brain develops. The parts of the brain involved in emotions and handling stress might not develop properly. This can make it hard for the person to manage their emotions later in life.

The hippocampus, involved in learning and memory, and the amygdala, which plays a role in emotion processing, are especially vulnerable. 

Similarly, if a child does not have enough food to eat or a safe place to live, the chronic stress of these conditions can impact brain development. The brain might focus on survival instead of other important areas of development, like learning and building relationships.

Even accidents that cause head injuries can impact the brain during the critical period. If a child experiences head trauma, it can affect the brain's development depending on the injury's severity and location.

What's the Difference Between a Critical Period and a Sensitive Period?

It is imperative to distinguish between critical periods and sensitive periods.

• Critical periods are specific windows of time during development when the brain is exceptionally receptive to certain types of learning and experiences. Once this period is over, acquiring those skills or attributes becomes significantly more challenging.
• Sensitive periods are phases in which the brain is more responsive to certain experiences. It's easier to learn or be influenced by specific experiences during sensitive periods, but unlike critical periods, missing this timeframe doesn't make it impossible to acquire those skills or traits later.

For example, while there is a critical period for acquiring native-like pronunciation and grammar, there is also a sensitive period for language learning. Children are more adept at learning new languages when they are young, but even if someone misses this window, they can still learn languages later in life.

One way to visualize the difference is to think of critical periods as a tightly defined window of time with a clear beginning and end, during which certain development must occur. In contrast, sensitive periods are more like a gradual slope, where learning at the beginning is optimal, but the ability doesn't disappear entirely over time.

What Happens to the Brain When the Critical Period Ends? 

It's essential to recognize that the end of the critical period does not mean the end of learning or brain development. Instead, it signifies a shift in how the brain learns and adapts. 

During the critical period, the brain is highly plastic, meaning it can change and form new connections rapidly. As this period ends, the brain doesn't lose this plasticity entirely, but the rate at which it can make new connections slows down. 

According to Hong, although some of these connections can still be altered by experiences later in life, such as learning a new language or practicing a skill, it is much harder to make significant changes after the critical period has ended. This highlights just how important it is for parents to provide proper care and nurture during those first few years.

The Brain Becomes More Specialized Via Adult Plasticity

The brain also becomes more specialized in the skills and information it has acquired as this period ends. During the critical period, the brain forms numerous connections, and as it ends, it starts to use these connections more efficiently for specialized tasks.

Even though the critical period ends, the brain still possesses a degree of plasticity and continues to learn throughout life. This is called adult plasticity.

Adult plasticity is not as robust during the critical period, but it allows for the continuous adaptation and learning necessary for us to navigate the ever-changing demands of life.

The conventional view is that critical periods close relatively tightly. However, research has started to challenge this rigid view. It's more accurate to say that the doors of critical periods close but do not necessarily lock.

While the brain's plasticity decreases after these periods, learning and adaptation can still take place, albeit with more effort and over a longer time. This phenomenon of 'metaplasticity'—the brain's ability to change its plasticity levels—remains an exciting area of ongoing research,  Dr. Ryan Sultan , a neuroscientist, child psychiatrist, and professor of psychiatry at Columbia University, says. 

What This Means For You

The critical period represents an invaluable window during which the foundations for cognitive, emotional, and social abilities are established. The environment, experiences, and attachments formed during this period have far-reaching consequences on a person's life.  Understanding the nuances of the critical period is essential for educators, parents, and policymakers to create nurturing environments that support healthy brain development. Providing support and early interventions for children exposed to adverse experiences is vital for ensuring their potential is not hindered by the circumstances of their early life.

Siahaan F. The critical period hypothesis of sla eric lenneberg’s . Journal of Applied Linguistics . 2022;2(1):40-45.

Nelson CA, Gabard-Durnam LJ. Early adversity and critical periods: neurodevelopmental consequences of violating the expectable environment. Trends in Neurosciences. 2020;43(3):133-143.

Colombo J, Gustafson KM, Carlson SE. Critical and sensitive periods in development and nutrition. Ann Nutr Metab . 2019;75(Suppl. 1):34-42.

Patton MH, Blundon JA, Zakharenko SS. Rejuvenation of plasticity in the brain: opening the critical period. Current Opinion in Neurobiology . 2019;54:83-89.

By Toketemu Ohwovoriole Toketemu has been multimedia storyteller for the last four years. Her expertise focuses primarily on mental wellness and women’s health topics.

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Age and the critical period hypothesis

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Christian Abello-Contesse, Age and the critical period hypothesis, ELT Journal , Volume 63, Issue 2, April 2009, Pages 170–172, https://doi.org/10.1093/elt/ccn072

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In the field of second language acquisition (SLA), how specific aspects of learning a non-native language (L2) may be affected by when the process begins is referred to as the ‘age factor’. Because of the way age intersects with a range of social, affective, educational, and experiential variables, clarifying its relationship with learning rate and/or success is a major challenge.

There is a popular belief that children as L2 learners are ‘superior’ to adults ( Scovel 2000 ), that is, the younger the learner, the quicker the learning process and the better the outcomes. Nevertheless, a closer examination of the ways in which age combines with other variables reveals a more complex picture, with both favourable and unfavourable age-related differences being associated with early- and late-starting L2 learners ( Johnstone 2002 ).

The ‘critical period hypothesis’ (CPH) is a particularly relevant case in point. This is the claim that there is, indeed, an optimal period for language acquisition, ending at puberty. However, in its original formulation ( Lenneberg 1967 ), evidence for its existence was based on the relearning of impaired L1 skills, rather than the learning of a second language under normal circumstances.

Furthermore, although the age factor is an uncontroversial research variable extending from birth to death ( Cook 1995 ), and the CPH is a narrowly focused proposal subject to recurrent debate, ironically, it is the latter that tends to dominate SLA discussions ( García Lecumberri and Gallardo 2003 ), resulting in a number of competing conceptualizations. Thus, in the current literature on the subject ( Bialystok 1997 ; Richards and Schmidt 2002 ; Abello-Contesse et al. 2006), references can be found to (i) multiple critical periods (each based on a specific language component, such as age six for L2 phonology), (ii) the non-existence of one or more critical periods for L2 versus L1 acquisition, (iii) a ‘sensitive’ yet not ‘critical’ period, and (iv) a gradual and continual decline from childhood to adulthood.

It therefore needs to be recognized that there is a marked contrast between the CPH as an issue of continuing dispute in SLA, on the one hand, and, on the other, the popular view that it is an invariable ‘law’, equally applicable to any L2 acquisition context or situation. In fact, research indicates that age effects of all kinds depend largely on the actual opportunities for learning which are available within overall contexts of L2 acquisition and particular learning situations, notably the extent to which initial exposure is substantial and sustained ( Lightbown 2000 ).

Thus, most classroom-based studies have shown not only a lack of direct correlation between an earlier start and more successful/rapid L2 development but also a strong tendency for older children and teenagers to be more efficient learners. For example, in research conducted in the context of conventional school programmes, Cenoz (2003) and Muñoz (2006) have shown that learners whose exposure to the L2 began at age 11 consistently displayed higher levels of proficiency than those for whom it began at 4 or 8. Furthermore, comparable limitations have been reported for young learners in school settings involving innovative, immersion-type programmes, where exposure to the target language is significantly increased through subject-matter teaching in the L2 ( Genesee 1992 ; Abello-Contesse 2006 ). In sum, as Harley and Wang (1997) have argued, more mature learners are usually capable of making faster initial progress in acquiring the grammatical and lexical components of an L2 due to their higher level of cognitive development and greater analytical abilities.

In terms of language pedagogy, it can therefore be concluded that (i) there is no single ‘magic’ age for L2 learning, (ii) both older and younger learners are able to achieve advanced levels of proficiency in an L2, and (iii) the general and specific characteristics of the learning environment are also likely to be variables of equal or greater importance.

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The Critical Period Hypothesis: Where Are We Now?

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The idea that children have a special talent for languages that is rarely, if ever, available to older learners is one that has much popular support. Among second language researchers, however, the related hypothesis of a maturationally delimited critical period for language acquisition has been a constant source of controversy. Not everyone accepts the view that young children have an inborn advantage over older learners, and even among those who take this position, debate continues as to what the causes of this advantage are, what the relevant age limits are, what aspects of language development it applies to, and what sort of empirical data provide a crucial test of the critical period hypothesis. In this chapter, we review relevant research findings and consider various proposed explanations of age-related differences in (second) language acquisition. We argue that, despite a number of unresolved problems and even some apparent counterevidence, the critical period concept, as it has evolved, continues to have considerable heuristic value in investigating the language development of learners whose exposure to a new language begins at different ages.

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Research Article

The Critical Period Hypothesis in Second Language Acquisition: A Statistical Critique and a Reanalysis

* E-mail: [email protected]

Affiliation Department of Multilingualism, University of Fribourg, Fribourg, Switzerland

• Jan Vanhove

• Published: July 25, 2013
• https://doi.org/10.1371/journal.pone.0069172
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17 Jul 2014: The PLOS ONE Staff (2014) Correction: The Critical Period Hypothesis in Second Language Acquisition: A Statistical Critique and a Reanalysis. PLOS ONE 9(7): e102922. https://doi.org/10.1371/journal.pone.0102922 View correction

In second language acquisition research, the critical period hypothesis ( cph ) holds that the function between learners' age and their susceptibility to second language input is non-linear. This paper revisits the indistinctness found in the literature with regard to this hypothesis's scope and predictions. Even when its scope is clearly delineated and its predictions are spelt out, however, empirical studies–with few exceptions–use analytical (statistical) tools that are irrelevant with respect to the predictions made. This paper discusses statistical fallacies common in cph research and illustrates an alternative analytical method (piecewise regression) by means of a reanalysis of two datasets from a 2010 paper purporting to have found cross-linguistic evidence in favour of the cph . This reanalysis reveals that the specific age patterns predicted by the cph are not cross-linguistically robust. Applying the principle of parsimony, it is concluded that age patterns in second language acquisition are not governed by a critical period. To conclude, this paper highlights the role of confirmation bias in the scientific enterprise and appeals to second language acquisition researchers to reanalyse their old datasets using the methods discussed in this paper. The data and R commands that were used for the reanalysis are provided as supplementary materials.

Citation: Vanhove J (2013) The Critical Period Hypothesis in Second Language Acquisition: A Statistical Critique and a Reanalysis. PLoS ONE 8(7): e69172. https://doi.org/10.1371/journal.pone.0069172

Editor: Stephanie Ann White, UCLA, United States of America

Received: May 7, 2013; Accepted: June 7, 2013; Published: July 25, 2013

Copyright: © 2013 Jan Vanhove. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: No current external funding sources for this study.

Competing interests: The author has declared that no competing interests exist.

Introduction

In the long term and in immersion contexts, second-language (L2) learners starting acquisition early in life – and staying exposed to input and thus learning over several years or decades – undisputedly tend to outperform later learners. Apart from being misinterpreted as an argument in favour of early foreign language instruction, which takes place in wholly different circumstances, this general age effect is also sometimes taken as evidence for a so-called ‘critical period’ ( cp ) for second-language acquisition ( sla ). Derived from biology, the cp concept was famously introduced into the field of language acquisition by Penfield and Roberts in 1959 [1] and was refined by Lenneberg eight years later [2] . Lenneberg argued that language acquisition needed to take place between age two and puberty – a period which he believed to coincide with the lateralisation process of the brain. (More recent neurological research suggests that different time frames exist for the lateralisation process of different language functions. Most, however, close before puberty [3] .) However, Lenneberg mostly drew on findings pertaining to first language development in deaf children, feral children or children with serious cognitive impairments in order to back up his claims. For him, the critical period concept was concerned with the implicit “automatic acquisition” [2, p. 176] in immersion contexts and does not preclude the possibility of learning a foreign language after puberty, albeit with much conscious effort and typically less success.

sla research adopted the critical period hypothesis ( cph ) and applied it to second and foreign language learning, resulting in a host of studies. In its most general version, the cph for sla states that the ‘susceptibility’ or ‘sensitivity’ to language input varies as a function of age, with adult L2 learners being less susceptible to input than child L2 learners. Importantly, the age–susceptibility function is hypothesised to be non-linear. Moving beyond this general version, we find that the cph is conceptualised in a multitude of ways [4] . This state of affairs requires scholars to make explicit their theoretical stance and assumptions [5] , but has the obvious downside that critical findings risk being mitigated as posing a problem to only one aspect of one particular conceptualisation of the cph , whereas other conceptualisations remain unscathed. This overall vagueness concerns two areas in particular, viz. the delineation of the cph 's scope and the formulation of testable predictions. Delineating the scope and formulating falsifiable predictions are, needless to say, fundamental stages in the scientific evaluation of any hypothesis or theory, but the lack of scholarly consensus on these points seems to be particularly pronounced in the case of the cph . This article therefore first presents a brief overview of differing views on these two stages. Then, once the scope of their cph version has been duly identified and empirical data have been collected using solid methods, it is essential that researchers analyse the data patterns soundly in order to assess the predictions made and that they draw justifiable conclusions from the results. As I will argue in great detail, however, the statistical analysis of data patterns as well as their interpretation in cph research – and this includes both critical and supportive studies and overviews – leaves a great deal to be desired. Reanalysing data from a recent cph -supportive study, I illustrate some common statistical fallacies in cph research and demonstrate how one particular cph prediction can be evaluated.

Delineating the scope of the critical period hypothesis

First, the age span for a putative critical period for language acquisition has been delimited in different ways in the literature [4] . Lenneberg's critical period stretched from two years of age to puberty (which he posits at about 14 years of age) [2] , whereas other scholars have drawn the cutoff point at 12, 15, 16 or 18 years of age [6] . Unlike Lenneberg, most researchers today do not define a starting age for the critical period for language learning. Some, however, consider the possibility of the critical period (or a critical period for a specific language area, e.g. phonology) ending much earlier than puberty (e.g. age 9 years [1] , or as early as 12 months in the case of phonology [7] ).

Second, some vagueness remains as to the setting that is relevant to the cph . Does the critical period constrain implicit learning processes only, i.e. only the untutored language acquisition in immersion contexts or does it also apply to (at least partly) instructed learning? Most researchers agree on the former [8] , but much research has included subjects who have had at least some instruction in the L2.

Third, there is no consensus on what the scope of the cp is as far as the areas of language that are concerned. Most researchers agree that a cp is most likely to constrain the acquisition of pronunciation and grammar and, consequently, these are the areas primarily looked into in studies on the cph [9] . Some researchers have also tried to define distinguishable cp s for the different language areas of phonetics, morphology and syntax and even for lexis (see [10] for an overview).

Fourth and last, research into the cph has focused on ‘ultimate attainment’ ( ua ) or the ‘final’ state of L2 proficiency rather than on the rate of learning. From research into the rate of acquisition (e.g. [11] – [13] ), it has become clear that the cph cannot hold for the rate variable. In fact, it has been observed that adult learners proceed faster than child learners at the beginning stages of L2 acquisition. Though theoretical reasons for excluding the rate can be posited (the initial faster rate of learning in adults may be the result of more conscious cognitive strategies rather than to less conscious implicit learning, for instance), rate of learning might from a different perspective also be considered an indicator of ‘susceptibility’ or ‘sensitivity’ to language input. Nevertheless, contemporary sla scholars generally seem to concur that ua and not rate of learning is the dependent variable of primary interest in cph research. These and further scope delineation problems relevant to cph research are discussed in more detail by, among others, Birdsong [9] , DeKeyser and Larson-Hall [14] , Long [10] and Muñoz and Singleton [6] .

Formulating testable hypotheses

Once the relevant cph 's scope has satisfactorily been identified, clear and testable predictions need to be drawn from it. At this stage, the lack of consensus on what the consequences or the actual observable outcome of a cp would have to look like becomes evident. As touched upon earlier, cph research is interested in the end state or ‘ultimate attainment’ ( ua ) in L2 acquisition because this “determines the upper limits of L2 attainment” [9, p. 10]. The range of possible ultimate attainment states thus helps researchers to explore the potential maximum outcome of L2 proficiency before and after the putative critical period.

One strong prediction made by some cph exponents holds that post- cp learners cannot reach native-like L2 competences. Identifying a single native-like post- cp L2 learner would then suffice to falsify all cph s making this prediction. Assessing this prediction is difficult, however, since it is not clear what exactly constitutes sufficient nativelikeness, as illustrated by the discussion on the actual nativelikeness of highly accomplished L2 speakers [15] , [16] . Indeed, there exists a real danger that, in a quest to vindicate the cph , scholars set the bar for L2 learners to match monolinguals increasingly higher – up to Swiftian extremes. Furthermore, the usefulness of comparing the linguistic performance in mono- and bilinguals has been called into question [6] , [17] , [18] . Put simply, the linguistic repertoires of mono- and bilinguals differ by definition and differences in the behavioural outcome will necessarily be found, if only one digs deep enough.

A second strong prediction made by cph proponents is that the function linking age of acquisition and ultimate attainment will not be linear throughout the whole lifespan. Before discussing how this function would have to look like in order for it to constitute cph -consistent evidence, I point out that the ultimate attainment variable can essentially be considered a cumulative measure dependent on the actual variable of interest in cph research, i.e. susceptibility to language input, as well as on such other factors like duration and intensity of learning (within and outside a putative cp ) and possibly a number of other influencing factors. To elaborate, the behavioural outcome, i.e. ultimate attainment, can be assumed to be integrative to the susceptibility function, as Newport [19] correctly points out. Other things being equal, ultimate attainment will therefore decrease as susceptibility decreases. However, decreasing ultimate attainment levels in and by themselves represent no compelling evidence in favour of a cph . The form of the integrative curve must therefore be predicted clearly from the susceptibility function. Additionally, the age of acquisition–ultimate attainment function can take just about any form when other things are not equal, e.g. duration of learning (Does learning last up until time of testing or only for a more or less constant number of years or is it dependent on age itself?) or intensity of learning (Do learners always learn at their maximum susceptibility level or does this intensity vary as a function of age, duration, present attainment and motivation?). The integral of the susceptibility function could therefore be of virtually unlimited complexity and its parameters could be adjusted to fit any age of acquisition–ultimate attainment pattern. It seems therefore astonishing that the distinction between level of sensitivity to language input and level of ultimate attainment is rarely made in the literature. Implicitly or explicitly [20] , the two are more or less equated and the same mathematical functions are expected to describe the two variables if observed across a range of starting ages of acquisition.

But even when the susceptibility and ultimate attainment variables are equated, there remains controversy as to what function linking age of onset of acquisition and ultimate attainment would actually constitute evidence for a critical period. Most scholars agree that not any kind of age effect constitutes such evidence. More specifically, the age of acquisition–ultimate attainment function would need to be different before and after the end of the cp [9] . According to Birdsong [9] , three basic possible patterns proposed in the literature meet this condition. These patterns are presented in Figure 1 . The first pattern describes a steep decline of the age of onset of acquisition ( aoa )–ultimate attainment ( ua ) function up to the end of the cp and a practically non-existent age effect thereafter. Pattern 2 is an “unconventional, although often implicitly invoked” [9, p. 17] notion of the cp function which contains a period of peak attainment (or performance at ceiling), i.e. performance does not vary as a function of age, which is often referred to as a ‘window of opportunity’. This time span is followed by an unbounded decline in ua depending on aoa . Pattern 3 includes characteristics of patterns 1 and 2. At the beginning of the aoa range, performance is at ceiling. The next segment is a downward slope in the age function which ends when performance reaches its floor. Birdsong points out that all of these patterns have been reported in the literature. On closer inspection, however, he concludes that the most convincing function describing these age effects is a simple linear one. Hakuta et al. [21] sketch further theoretically possible predictions of the cph in which the mean performance drops drastically and/or the slope of the aoa – ua proficiency function changes at a certain point.

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The graphs are based on based on Figure 2 in [9] .

https://doi.org/10.1371/journal.pone.0069172.g001

Although several patterns have been proposed in the literature, it bears pointing out that the most common explicit prediction corresponds to Birdsong's first pattern, as exemplified by the following crystal-clear statement by DeKeyser, one of the foremost cph proponents:

[A] strong negative correlation between age of acquisition and ultimate attainment throughout the lifespan (or even from birth through middle age), the only age effect documented in many earlier studies, is not evidence for a critical period…[T]he critical period concept implies a break in the AoA–proficiency function, i.e., an age (somewhat variable from individual to individual, of course, and therefore an age range in the aggregate) after which the decline of success rate in one or more areas of language is much less pronounced and/or clearly due to different reasons. [22, p. 445].

DeKeyser and before him among others Johnson and Newport [23] thus conceptualise only one possible pattern which would speak in favour of a critical period: a clear negative age effect before the end of the critical period and a much weaker (if any) negative correlation between age and ultimate attainment after it. This ‘flattened slope’ prediction has the virtue of being much more tangible than the ‘potential nativelikeness’ prediction: Testing it does not necessarily require comparing the L2-learners to a native control group and thus effectively comparing apples and oranges. Rather, L2-learners with different aoa s can be compared amongst themselves without the need to categorise them by means of a native-speaker yardstick, the validity of which is inevitably going to be controversial [15] . In what follows, I will concern myself solely with the ‘flattened slope’ prediction, arguing that, despite its clarity of formulation, cph research has generally used analytical methods that are irrelevant for the purposes of actually testing it.

Inferring non-linearities in critical period research: An overview

Group mean or proportion comparisons.

[T]he main differences can be found between the native group and all other groups – including the earliest learner group – and between the adolescence group and all other groups. However, neither the difference between the two childhood groups nor the one between the two adulthood groups reached significance, which indicates that the major changes in eventual perceived nativelikeness of L2 learners can be associated with adolescence. [15, p. 270].

Similar group comparisons aimed at investigating the effect of aoa on ua have been carried out by both cph advocates and sceptics (among whom Bialystok and Miller [25, pp. 136–139], Birdsong and Molis [26, p. 240], Flege [27, pp. 120–121], Flege et al. [28, pp. 85–86], Johnson [29, p. 229], Johnson and Newport [23, p. 78], McDonald [30, pp. 408–410] and Patowski [31, pp. 456–458]). To be clear, not all of these authors drew direct conclusions about the aoa – ua function on the basis of these groups comparisons, but their group comparisons have been cited as indicative of a cph -consistent non-continuous age effect, as exemplified by the following quote by DeKeyser [22] :

Where group comparisons are made, younger learners always do significantly better than the older learners. The behavioral evidence, then, suggests a non-continuous age effect with a “bend” in the AoA–proficiency function somewhere between ages 12 and 16. [22, p. 448].

The first problem with group comparisons like these and drawing inferences on the basis thereof is that they require that a continuous variable, aoa , be split up into discrete bins. More often than not, the boundaries between these bins are drawn in an arbitrary fashion, but what is more troublesome is the loss of information and statistical power that such discretisation entails (see [32] for the extreme case of dichotomisation). If we want to find out more about the relationship between aoa and ua , why throw away most of the aoa information and effectively reduce the ua data to group means and the variance in those groups?

Comparison of correlation coefficients.

Correlation-based inferences about slope discontinuities have similarly explicitly been made by cph advocates and skeptics alike, e.g. Bialystok and Miller [25, pp. 136 and 140], DeKeyser and colleagues [22] , [44] and Flege et al. [45, pp. 166 and 169]. Others did not explicitly infer the presence or absence of slope differences from the subset correlations they computed (among others Birdsong and Molis [26] , DeKeyser [8] , Flege et al. [28] and Johnson [29] ), but their studies nevertheless featured in overviews discussing discontinuities [14] , [22] . Indeed, the most recent overview draws a strong conclusion about the validity of the cph 's ‘flattened slope’ prediction on the basis of these subset correlations:

In those studies where the two groups are described separately, the correlation is much higher for the younger than for the older group, except in Birdsong and Molis (2001) [ =  [26] , JV], where there was a ceiling effect for the younger group. This global picture from more than a dozen studies provides support for the non-continuity of the decline in the AoA–proficiency function, which all researchers agree is a hallmark of a critical period phenomenon. [22, p. 448].

In Johnson and Newport's specific case [23] , their correlation-based inference that ua levels off after puberty happened to be largely correct: the gjt scores are more or less randomly distributed around a near-horizontal trend line [26] . Ultimately, however, it rests on the fallacy of confusing correlation coefficients with slopes, which seriously calls into question conclusions such as DeKeyser's (cf. the quote above).

https://doi.org/10.1371/journal.pone.0069172.g002

Lower correlation coefficients in older aoa groups may therefore be largely due to differences in ua variance, which have been reported in several studies [23] , [26] , [28] , [29] (see [46] for additional references). Greater variability in ua with increasing age is likely due to factors other than age proper [47] , such as the concomitant greater variability in exposure to literacy, degree of education, motivation and opportunity for language use, and by itself represents evidence neither in favour of nor against the cph .

Regression approaches.

Having demonstrated that neither group mean or proportion comparisons nor correlation coefficient comparisons can directly address the ‘flattened slope’ prediction, I now turn to the studies in which regression models were computed with aoa as a predictor variable and ua as the outcome variable. Once again, this category of studies is not mutually exclusive with the two categories discussed above.

In a large-scale study using self-reports and approximate aoa s derived from a sample of the 1990 U.S. Census, Stevens found that the probability with which immigrants from various countries stated that they spoke English ‘very well’ decreased curvilinearly as a function of aoa [48] . She noted that this development is similar to the pattern found by Johnson and Newport [23] but that it contains no indication of an “abruptly defined ‘critical’ or sensitive period in L2 learning” [48, p. 569]. However, she modelled the self-ratings using an ordinal logistic regression model in which the aoa variable was logarithmically transformed. Technically, this is perfectly fine, but one should be careful not to read too much into the non-linear curves found. In logistic models, the outcome variable itself is modelled linearly as a function of the predictor variables and is expressed in log-odds. In order to compute the corresponding probabilities, these log-odds are transformed using the logistic function. Consequently, even if the model is specified linearly, the predicted probabilities will not lie on a perfectly straight line when plotted as a function of any one continuous predictor variable. Similarly, when the predictor variable is first logarithmically transformed and then used to linearly predict an outcome variable, the function linking the predicted outcome variables and the untransformed predictor variable is necessarily non-linear. Thus, non-linearities follow naturally from Stevens's model specifications. Moreover, cph -consistent discontinuities in the aoa – ua function cannot be found using her model specifications as they did not contain any parameters allowing for this.

Using data similar to Stevens's, Bialystok and Hakuta found that the link between the self-rated English competences of Chinese- and Spanish-speaking immigrants and their aoa could be described by a straight line [49] . In contrast to Stevens, Bialystok and Hakuta used a regression-based method allowing for changes in the function's slope, viz. locally weighted scatterplot smoothing ( lowess ). Informally, lowess is a non-parametrical method that relies on an algorithm that fits the dependent variable for small parts of the range of the independent variable whilst guaranteeing that the overall curve does not contain sudden jumps (for technical details, see [50] ). Hakuta et al. used an even larger sample from the same 1990 U.S. Census data on Chinese- and Spanish-speaking immigrants (2.3 million observations) [21] . Fitting lowess curves, no discontinuities in the aoa – ua slope could be detected. Moreover, the authors found that piecewise linear regression models, i.e. regression models containing a parameter that allows a sudden drop in the curve or a change of its slope, did not provide a better fit to the data than did an ordinary regression model without such a parameter.

To sum up, I have argued at length that regression approaches are superior to group mean and correlation coefficient comparisons for the purposes of testing the ‘flattened slope’ prediction. Acknowledging the reservations vis-à-vis self-estimated ua s, we still find that while the relationship between aoa and ua is not necessarily perfectly linear in the studies discussed, the data do not lend unequivocal support to this prediction. In the following section, I will reanalyse data from a recent empirical paper on the cph by DeKeyser et al. [44] . The first goal of this reanalysis is to further illustrate some of the statistical fallacies encountered in cph studies. Second, by making the computer code available I hope to demonstrate how the relevant regression models, viz. piecewise regression models, can be fitted and how the aoa representing the optimal breakpoint can be identified. Lastly, the findings of this reanalysis will contribute to our understanding of how aoa affects ua as measured using a gjt .

Summary of DeKeyser et al. (2010)

I chose to reanalyse a recent empirical paper on the cph by DeKeyser et al. [44] (henceforth DK et al.). This paper lends itself well to a reanalysis since it exhibits two highly commendable qualities: the authors spell out their hypotheses lucidly and provide detailed numerical and graphical data descriptions. Moreover, the paper's lead author is very clear on what constitutes a necessary condition for accepting the cph : a non-linearity in the age of onset of acquisition ( aoa )–ultimate attainment ( ua ) function, with ua declining less strongly as a function of aoa in older, post- cp arrivals compared to younger arrivals [14] , [22] . Lastly, it claims to have found cross-linguistic evidence from two parallel studies backing the cph and should therefore be an unsuspected source to cph proponents.

The authors set out to test the following hypotheses:

• Hypothesis 1: For both the L2 English and the L2 Hebrew group, the slope of the age of arrival–ultimate attainment function will not be linear throughout the lifespan, but will instead show a marked flattening between adolescence and adulthood.
• Hypothesis 2: The relationship between aptitude and ultimate attainment will differ markedly for the young and older arrivals, with significance only for the latter. (DK et al., p. 417)

Both hypotheses were purportedly confirmed, which in the authors' view provides evidence in favour of cph . The problem with this conclusion, however, is that it is based on a comparison of correlation coefficients. As I have argued above, correlation coefficients are not to be confused with regression coefficients and cannot be used to directly address research hypotheses concerning slopes, such as Hypothesis 1. In what follows, I will reanalyse the relationship between DK et al.'s aoa and gjt data in order to address Hypothesis 1. Additionally, I will lay bare a problem with the way in which Hypothesis 2 was addressed. The extracted data and the computer code used for the reanalysis are provided as supplementary materials, allowing anyone interested to scrutinise and easily reproduce my whole analysis and carry out their own computations (see ‘supporting information’).

Data extraction

In order to verify whether we did in fact extract the data points to a satisfactory degree of accuracy, I computed summary statistics for the extracted aoa and gjt data and checked these against the descriptive statistics provided by DK et al. (pp. 421 and 427). These summary statistics for the extracted data are presented in Table 1 . In addition, I computed the correlation coefficients for the aoa – gjt relationship for the whole aoa range and for aoa -defined subgroups and checked these coefficients against those reported by DK et al. (pp. 423 and 428). The correlation coefficients computed using the extracted data are presented in Table 2 . Both checks strongly suggest the extracted data to be virtually identical to the original data, and Dr DeKeyser confirmed this to be the case in response to an earlier draft of the present paper (personal communication, 6 May 2013).

https://doi.org/10.1371/journal.pone.0069172.t001

https://doi.org/10.1371/journal.pone.0069172.t002

Results and Discussion

Modelling the link between age of onset of acquisition and ultimate attainment.

I first replotted the aoa and gjt data we extracted from DK et al.'s scatterplots and added non-parametric scatterplot smoothers in order to investigate whether any changes in slope in the aoa – gjt function could be revealed, as per Hypothesis 1. Figures 3 and 4 show this not to be the case. Indeed, simple linear regression models that model gjt as a function of aoa provide decent fits for both the North America and the Israel data, explaining 65% and 63% of the variance in gjt scores, respectively. The parameters of these models are given in Table 3 .

The trend line is a non-parametric scatterplot smoother. The scatterplot itself is a near-perfect replication of DK et al.'s Fig. 1.

https://doi.org/10.1371/journal.pone.0069172.g003

The trend line is a non-parametric scatterplot smoother. The scatterplot itself is a near-perfect replication of DK et al.'s Fig. 5.

https://doi.org/10.1371/journal.pone.0069172.g004

https://doi.org/10.1371/journal.pone.0069172.t003

To ensure that both segments are joined at the breakpoint, the predictor variable is first centred at the breakpoint value, i.e. the breakpoint value is subtracted from the original predictor variable values. For a blow-by-blow account of how such models can be fitted in r , I refer to an example analysis by Baayen [55, pp. 214–222].

Solid: regression with breakpoint at aoa 18 (dashed lines represent its 95% confidence interval); dot-dash: regression without breakpoint.

https://doi.org/10.1371/journal.pone.0069172.g005

Solid: regression with breakpoint at aoa 18 (dashed lines represent its 95% confidence interval); dot-dash (hardly visible due to near-complete overlap): regression without breakpoint.

https://doi.org/10.1371/journal.pone.0069172.g006

https://doi.org/10.1371/journal.pone.0069172.t004

https://doi.org/10.1371/journal.pone.0069172.g007

Solid: regression with breakpoint at aoa 16 (dashed lines represent its 95% confidence interval); dot-dash: regression without breakpoint.

https://doi.org/10.1371/journal.pone.0069172.g008

Solid: regression with breakpoint at aoa 6 (dashed lines represent its 95% confidence interval); dot-dash (hardly visible due to near-complete overlap): regression without breakpoint.

https://doi.org/10.1371/journal.pone.0069172.g009

https://doi.org/10.1371/journal.pone.0069172.t005

https://doi.org/10.1371/journal.pone.0069172.t006

https://doi.org/10.1371/journal.pone.0069172.t007

https://doi.org/10.1371/journal.pone.0069172.t008

In sum, a regression model that allows for changes in the slope of the the aoa – gjt function to account for putative critical period effects provides a somewhat better fit to the North American data than does an everyday simple regression model. The improvement in model fit is marginal, however, and including a breakpoint does not result in any detectable improvement of model fit to the Israel data whatsoever. Breakpoint models therefore fail to provide solid cross-linguistic support in favour of critical period effects: across both data sets, gjt can satisfactorily be modelled as a linear function of aoa .

On partialling out ‘age at testing’

As I have argued above, correlation coefficients cannot be used to test hypotheses about slopes. When the correct procedure is carried out on DK et al.'s data, no cross-linguistically robust evidence for changes in the aoa – gjt function was found. In addition to comparing the zero-order correlations between aoa and gjt , however, DK et al. computed partial correlations in which the variance in aoa associated with the participants' age at testing ( aat ; a potentially confounding variable) was filtered out. They found that these partial correlations between aoa and gjt , which are given in Table 9 , differed between age groups in that they are stronger for younger than for older participants. This, DK et al. argue, constitutes additional evidence in favour of the cph . At this point, I can no longer provide my own analysis of DK et al.'s data seeing as the pertinent data points were not plotted. Nevertheless, the detailed descriptions by DK et al. strongly suggest that the use of these partial correlations is highly problematic. Most importantly, and to reiterate, correlations (whether zero-order or partial ones) are actually of no use when testing hypotheses concerning slopes. Still, one may wonder why the partial correlations differ across age groups. My surmise is that these differences are at least partly the by-product of an imbalance in the sampling procedure.

https://doi.org/10.1371/journal.pone.0069172.t009

The upshot of this brief discussion is that the partial correlation differences reported by DK et al. are at least partly the result of an imbalance in the sampling procedure: aoa and aat were simply less intimately tied for the young arrivals in the North America study than for the older arrivals with L2 English or for all of the L2 Hebrew participants. In an ideal world, we would like to fix aat or ascertain that it at most only weakly correlates with aoa . This, however, would result in a strong correlation between aoa and another potential confound variable, length of residence in the L2 environment, bringing us back to square one. Allowing for only moderate correlations between aoa and aat might improve our predicament somewhat, but even in that case, we should tread lightly when making inferences on the basis of statistical control procedures [61] .

On estimating the role of aptitude

Having shown that Hypothesis 1 could not be confirmed, I now turn to Hypothesis 2, which predicts a differential role of aptitude for ua in sla in different aoa groups. More specifically, it states that the correlation between aptitude and gjt performance will be significant only for older arrivals. The correlation coefficients of the relationship between aptitude and gjt are presented in Table 10 .

https://doi.org/10.1371/journal.pone.0069172.t010

The problem with both the wording of Hypothesis 2 and the way in which it is addressed is the following: it is assumed that a variable has a reliably different effect in different groups when the effect reaches significance in one group but not in the other. This logic is fairly widespread within several scientific disciplines (see e.g. [62] for a discussion). Nonetheless, it is demonstrably fallacious [63] . Here we will illustrate the fallacy for the specific case of comparing two correlation coefficients.

Apart from not being replicated in the North America study, does this difference actually show anything? I contend that it does not: what is of interest are not so much the correlation coefficients, but rather the interactions between aoa and aptitude in models predicting gjt . These interactions could be investigated by fitting a multiple regression model in which the postulated cp breakpoint governs the slope of both aoa and aptitude. If such a model provided a substantially better fit to the data than a model without a breakpoint for the aptitude slope and if the aptitude slope changes in the expected direction (i.e. a steeper slope for post- cp than for younger arrivals) for different L1–L2 pairings, only then would this particular prediction of the cph be borne out.

Using data extracted from a paper reporting on two recent studies that purport to provide evidence in favour of the cph and that, according to its authors, represent a major improvement over earlier studies (DK et al., p. 417), it was found that neither of its two hypotheses were actually confirmed when using the proper statistical tools. As a matter of fact, the gjt scores continue to decline at essentially the same rate even beyond the end of the putative critical period. According to the paper's lead author, such a finding represents a serious problem to his conceptualisation of the cph [14] ). Moreover, although modelling a breakpoint representing the end of a cp at aoa 16 may improve the statistical model slightly in study on learners of English in North America, the study on learners of Hebrew in Israel fails to confirm this finding. In fact, even if we were to accept the optimal breakpoint computed for the Israel study, it lies at aoa 6 and is associated with a different geometrical pattern.

Diverging age trends in parallel studies with participants with different L2s have similarly been reported by Birdsong and Molis [26] and are at odds with an L2-independent cph . One parsimonious explanation of such conflicting age trends may be that the overall, cross-linguistic age trend is in fact linear, but that fluctuations in the data (due to factors unaccounted for or randomness) may sometimes give rise to a ‘stretched L’-shaped pattern ( Figure 1, left panel ) and sometimes to a ‘stretched 7’-shaped pattern ( Figure 1 , middle panel; see also [66] for a similar comment).

Importantly, the criticism that DeKeyser and Larsson-Hall levy against two studies reporting findings similar to the present [48] , [49] , viz. that the data consisted of self-ratings of questionable validity [14] , does not apply to the present data set. In addition, DK et al. did not exclude any outliers from their analyses, so I assume that DeKeyser and Larsson-Hall's criticism [14] of Birdsong and Molis's study [26] , i.e. that the findings were due to the influence of outliers, is not applicable to the present data either. For good measure, however, I refitted the regression models with and without breakpoints after excluding one potentially problematic data point per model. The following data points had absolute standardised residuals larger than 2.5 in the original models without breakpoints as well as in those with breakpoints: the participant with aoa 17 and a gjt score of 125 in the North America study and the participant with aoa 12 and a gjt score of 117 in the Israel study. The resultant models were virtually identical to the original models (see Script S1 ). Furthermore, the aoa variable was sufficiently fine-grained and the aoa – gjt curve was not ‘presmoothed’ by the prior aggregation of gjt across parts of the aoa range (see [51] for such a criticism of another study). Lastly, seven of the nine “problems with supposed counter-evidence” to the cph discussed by Long [5] do not apply either, viz. (1) “[c]onfusion of rate and ultimate attainment”, (2) “[i]nappropriate choice of subjects”, (3) “[m]easurement of AO”, (4) “[l]eading instructions to raters”, (6) “[u]se of markedly non-native samples making near-native samples more likely to sound native to raters”, (7) “[u]nreliable or invalid measures”, and (8) “[i]nappropriate L1–L2 pairings”. Problem No. 5 (“Assessments based on limited samples and/or “language-like” behavior”) may be apropos given that only gjt data were used, leaving open the theoretical possibility that other measures might have yielded a different outcome. Finally, problem No. 9 (“Faulty interpretation of statistical patterns”) is, of course, precisely what I have turned the spotlights on.

Conclusions

The critical period hypothesis remains a hotly contested issue in the psycholinguistics of second-language acquisition. Discussions about the impact of empirical findings on the tenability of the cph generally revolve around the reliability of the data gathered (e.g. [5] , [14] , [22] , [52] , [67] , [68] ) and such methodological critiques are of course highly desirable. Furthermore, the debate often centres on the question of exactly what version of the cph is being vindicated or debunked. These versions differ mainly in terms of its scope, specifically with regard to the relevant age span, setting and language area, and the testable predictions they make. But even when the cph 's scope is clearly demarcated and its main prediction is spelt out lucidly, the issue remains to what extent the empirical findings can actually be marshalled in support of the relevant cph version. As I have shown in this paper, empirical data have often been taken to support cph versions predicting that the relationship between age of acquisition and ultimate attainment is not strictly linear, even though the statistical tools most commonly used (notably group mean and correlation coefficient comparisons) were, crudely put, irrelevant to this prediction. Methods that are arguably valid, e.g. piecewise regression and scatterplot smoothing, have been used in some studies [21] , [26] , [49] , but these studies have been criticised on other grounds. To my knowledge, such methods have never been used by scholars who explicitly subscribe to the cph .

I suspect that what may be going on is a form of ‘confirmation bias’ [69] , a cognitive bias at play in diverse branches of human knowledge seeking: Findings judged to be consistent with one's own hypothesis are hardly questioned, whereas findings inconsistent with one's own hypothesis are scrutinised much more strongly and criticised on all sorts of points [70] – [73] . My reanalysis of DK et al.'s recent paper may be a case in point. cph exponents used correlation coefficients to address their prediction about the slope of a function, as had been done in a host of earlier studies. Finding a result that squared with their expectations, they did not question the technical validity of their results, or at least they did not report this. (In fact, my reanalysis is actually a case in point in two respects: for an earlier draft of this paper, I had computed the optimal position of the breakpoints incorrectly, resulting in an insignificant improvement of model fit for the North American data rather than a borderline significant one. Finding a result that squared with my expectations, I did not question the technical validity of my results – until this error was kindly pointed out to me by Martijn Wieling (University of Tübingen).) That said, I am keen to point out that the statistical analyses in this particular paper, though suboptimal, are, as far as I could gather, reported correctly, i.e. the confirmation bias does not seem to have resulted in the blatant misreportings found elsewhere (see [74] for empirical evidence and discussion). An additional point to these authors' credit is that, apart from explicitly identifying their cph version's scope and making crystal-clear predictions, they present data descriptions that actually permit quantitative reassessments and have a history of doing so (e.g. the appendix in [8] ). This leads me to believe that they analysed their data all in good conscience and to hope that they, too, will conclude that their own data do not, in fact, support their hypothesis.

I end this paper on an upbeat note. Even though I have argued that the analytical tools employed in cph research generally leave much to be desired, the original data are, so I hope, still available. This provides researchers, cph supporters and sceptics alike, with an exciting opportunity to reanalyse their data sets using the tools outlined in the present paper and publish their findings at minimal cost of time and resources (for instance, as a comment to this paper). I would therefore encourage scholars to engage their old data sets and to communicate their analyses openly, e.g. by voluntarily publishing their data and computer code alongside their articles or comments. Ideally, cph supporters and sceptics would join forces to agree on a protocol for a high-powered study in order to provide a truly convincing answer to a core issue in sla .

Supporting Information

Dataset s1..

aoa and gjt data extracted from DeKeyser et al.'s North America study.

https://doi.org/10.1371/journal.pone.0069172.s001

Dataset S2.

aoa and gjt data extracted from DeKeyser et al.'s Israel study.

https://doi.org/10.1371/journal.pone.0069172.s002

Script with annotated R code used for the reanalysis. All add-on packages used can be installed from within R.

https://doi.org/10.1371/journal.pone.0069172.s003

Acknowledgments

I would like to thank Irmtraud Kaiser (University of Fribourg) for helping me to get an overview of the literature on the critical period hypothesis in second language acquisition. Thanks are also due to Martijn Wieling (currently University of Tübingen) for pointing out an error in the R code accompanying an earlier draft of this paper.

Author Contributions

Analyzed the data: JV. Wrote the paper: JV.

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Rethinking the critical period for language: New insights into an old question from American Sign Language

Rachel i. mayberry.

Department of Linguistics, University of California San Diego

ROBERT KLUENDER

We thank the commentators for their thoughtful critiques, which we found both insightful and stimulating to our own thinking. Our first response is that, while debates about the CPL in theoretical contexts are important, the vigor and intensity of these debates should not overshadow the fact that the main goal of our article was to highlight a finding of vital importance: Sufficient language input in early childhood matters deeply because it has long-term consequences ( Lillo-Martin, 2018 ). Woll sums up this point both succinctly and poignantly in her report of a similar case of very late L1 exposure in adulthood who had decades of experience: “For a [deaf] child who, even in the context of early intervention, does not acquire a spoken language, the danger is that they will never have native-like mastery of any L1.” This is what truly matters. Our hope is that our keynote article and the accompanying commentaries might have a positive effect on clinical practice, educational policy, and even parental choice in this regard. In what follows, we discuss the main issues arising from the commentaries. First we note the points of agreement followed by a clarification of what we did not claim in our article. Researchers continue to debate what the shape of the AoA function looks like and its theoretical implications, which we address third. We then address the issues raised as to whether late L1 acquisition and late L2 learning differ in degree or kind, and last we discuss what we mean when we say that language acquisition during post-natal brain growth creates the capacity to learn language.

Points of agreement

The good news is that there is widespread agreement among language researchers about the CPL. Until recently, to our knowledge, no one has questioned that there is a steady decline in ultimate attainment the longer that exposure to any language – first, second, or N th – is delayed over the childhood years. This consensus may be in need of modification in light of the large-scale findings reported in Hartshorne, Tenenbaum, and Pinker (in press) with regard to L2 syntactic learning ability, as cited by Birdsong and Quinto-Pozos in their commentary. There are also questions about the exact slope of this decline at different levels of linguistic analysis ( Bley-Vroman, 2018 ; Lillo-Martin, 2018 ; Long & Granena, 2018 ; Veríssimo, 2018 ). However, there seems to be no dispute about the general phenomenon and that it affects sign language too ( Bialystok & Kroll, 2018 ; Birdsong & Quinto-Pozos, 2018 ; Bley-Vroman, 2018 ; DeKeyser, 2018 ; Hyltenstam, 2018 ; Lillo-Martin, 2018 ; Veríssimo, 2018 ; White, 2018 ). This in and of itself is a significant advance over Lenneberg’s (1967) original hypothesis, which made no such prediction, and we should not lose sight of this fact. Indeed, research conducted by several of the commentators helped establish the finding, and for this we can all be thankful. At the same time we recognize that this piece of scientific convergence has not made its way into public discourse, which behooves us to redouble our outreach efforts.

A major point of disagreement among the commentators centers on the question of whether there is a similar steady decline across the adult years. Regardless of which answer ends up being correct, we need to bear in mind what is at stake. Adults (at least those with a first language established during childhood) will simply continue to muddle through, learning an additional language one way or the other as they have always done. As White puts it, the L2 “ [...] acquisition task involves coming up with a linguistic system that allows the learner to use the L2 (in comprehension and production). The task is NOT to arrive at a grammar identical to that of a native speaker.” We would add that the L1 acquisition task is to come up with grammar in the first place, and that the ability to do so declines sharply the longer the child matures without language. Not all commentators agreed, however, about the differences between these two learning situations, which we address in detail below. Before discussing the shape and interpretation of the L2 AoA function, and comments about the L1 AoA function, we wish to set the record straight with regard to what we did not claim in our keynote article.

What we did not claim

For the sake of clarity, we would like to disavow certain positions that have been attributed to us in some of the commentaries, but that we do not in fact hold: Namely, that language learning ability functions flawlessly in adulthood, that L1 and L2 learning are the same, that L2 learners consistently perform on par with native speaker or signer controls, that all L2 learners attain near-native levels of proficiency, or that there are no differences between near-native and native-like language ability ( Abrahamsson, 2018 ; Hyltenstam, 2018 ; Birdsong & Quinto-Pozos, 2018 ). Some of these misconceptions may have arisen from our discussion of the possibility of L2 learners acquiring a native-like accent in section 2.1 ‘Phonological Effects.’ As native-like pronunciation has often been touted as the sine qua non of critical period studies, we chose to focus precisely on this aspect of L2 acquisition in some detail in order to ascertain the extent to which it may, in fact, be at all possible. In this vein, we hasten to add that the 4% figure cited in a footnote, which several commentators mentioned ( Abrahamsson, 2018 ; Lillo-Martin, 2018 ; Long & Granena, 2018 ), was merely the lowest percentage of participants claimed to have performed within native speaker accent norms by the authors of any of the L2 pronunciation studies that we reviewed. We fully recognize the limitations of subjective assessments of accent, which is why we also included acoustic studies of pronunciation in our review. By no means did we intend to claim that 4% of L2 learners in the studies we reviewed demonstrate equivalent proficiency to native speakers at all levels of linguistic analysis, nor that 4% of all L2 learners perform at native levels. Rather, we explicitly stated that “[w]e are not claiming [native-like accent] to be the norm in L2 acquisition. To the contrary, everyone is anecdotally aware of the difficulty of achieving native-like pronunciation in a language acquired after childhood.”

Some commentators also came away with the impression that – because we stated in our keynote article that “there is no animal model with which to study a CP for language (CPL)” – we must believe that the study of neuronal mechanisms underlying CP plasticity in various animal species is irrelevant to studies of the CPL ( Reh, Arredondo & Werker, 2018 ). To the contrary, we find such studies vitally important - and in fact cited one such study in our keynote article that showed effects of both critical period social isolation and corresponding knockout experiments in mice on oligodendrocyte maturation/myelination ( Makinodan, Rosen, Ito & Corfas, 2012 ). The relevance of this animal study is that myelination has been demonstrated to persist into the third decade of human life ( Miller, Duka, Stimpson, Schapiro, Baze, McArthur, Fobbs, Sousa, Sestan, Wildman, Lipovich, Kuzawa, Hof & Sherwood, 2012 ) and post-critical period L2 learning has been suggested to enhance myelination in college age populations (as measured by increases in fractional anisotropy and decreases in radial diffusivity) and thereby expand “the functionality of networks involved in learning by altering the underlying anatomy” ( Schlegel, Rudelson & Tse, 2012 , p. 1669). Moreover, even studies of adult songbirds have demonstrated plasticity of vocal learning late in life. After deafening and recovery from hair cell destruction, adult domesticated society finches were not only able to relearn their songs, but these relearned songs more closely matched those of cagemates with which they were housed during recovery than their own original songs before deafening ( Woolley & Rubel, 2002 ). Thus the claim that “the evolutionary function of a CP is [not] to develop language-learning skills to be utilized beyond the closure of the CP, no more than the function of a CP for birdsong is for the bird to develop skill for future birdsong learning” ( Abrahamsson, 2018 ) cannot stand, at least for this particular species.

The shape of the L2 AoA function

One aspect of our keynote article that elicited comments from the greatest number of commentators concerned the shape of the AoA function, whether the linearity of the documented decline in ultimate attainment across the lifespan is continuous or discontinuous, and whether this decline reflects biological, L1 entrenchment, or socioenvironmental factors including L2 input ( Bialystok & Kroll, 2018 ; Birdsong & Quinto-Pozos, 2018 ; DeKeyser, 2018 ; Hyltenstam, 2018 ; Long & Granena, 2018 ; Newport, 2018 ; Veríssimo, 2018 ). Unsurprisingly, these are the commentators who have conducted studies investigating these questions. Opinions range all the way from the conclusion that there is no critical period at all ( Bialystok & Kroll, 2018 ) to the conclusion that there are multiple critical periods with different age cutoffs for different linguistic phenomena ( Bley-Vroman, 2018 ; Lillo-Martin, 2018 ; Long & Granena, 2018 ; Veríssimo, 2018 ).

Here we flesh out some of the ideas in our keynote article that we were unable to elaborate on for lack of space. First and foremost, we emphasize that we are, for the most part, consumers rather than producers of L2 AoA research, and therefore come to this literature as interested but reasonably dispassionate observers. One inference that seems apparent to us, as alluded to in our original article, is that it would be desirable for the field to agree on how much of a difference (in variance accounted for) is sufficient to warrant choosing one alternative hypothesis over the other.

The problem is exemplified by the analytical and interpretative differences across several of the L2 studies we reviewed. For example, Johnson and Newport (1989) reported correlation coefficients of −.77 for one linear function across all participants in their study with AoAs of 3–39 years, but of −.87 for participants with AoAs of 3–15 years, and no significant correlation for participants with AoAs of 17–39 years. Reanalyzing the data, Elman, Bates, Johnson, Karmiloff-Smith, Parisi, and Plunkett (1996) reported that Johnson and Newport’s two linear functions accounted for 39.25% of the variance in the distribution, while a curvilinear function accounted for 63.1%. As another example, when restricting the range of AoAs to 7–18 years in their analyses of morphosyntactic ability, Flege, Yeni-Komshian, and Liu (1999) reported that a sigmoid function accounted for 5% more of the variance than did a linear function, and conceded that this might be evidence for a discontinuity around an AoA of 12 years, although they also found linear correlations on either side of the 12–15 age range, with a more robust correlation before than after. In contrast, Granena and Long (2013) reported better fits with regression models incorporating two versus no AoA breakpoints for phonology, morphosyntax, and lexis/collocation alike, but then conceded that “the increase in variance accounted for, even if significant, was only around 5%. This could mean that the less complex (i.e. more parsimonious) model with no breakpoints is already a good enough fit to the data [...]” (pp. 326f). Note that both sets of authors argue against their own preferred hypotheses in this instance. We were also aware that when age at time of testing was partialed out in the DeKeyser, Alfi-Shabtay, and Ravid (2010) study, only L2 learners with an AoA of up to 18 years still showed a correlation with proficiency. This correlation disappeared when the group was split at age 12 (possibly for lack of statistical power, as the authors suggest), but mean scores on the grammaticality judgment task still differed significantly between those with an AoA above or below age 12. Our issue is that both the correlation and the mean split appear to be largely attributable to where the earliest cutoff was drawn in the data set, namely at age 18. It is not clear that either would hold up if the cutoff point had been changed to age 15, or for that matter age 19: Namely, the scores of the three U.S. participants with an AoA of 19 fell squarely in the middle of the distribution for those with AoAs of 15 or below, and well above those of participants with AoAs of 16 or 17. Similar problems exist in the Israeli data set.

Beyond debates about the shape of the AoA function, however, there is the question of what counts as ‘puberty’. As we noted in our original article, and discussed above, across L2 AoA studies, the cutoff points (for what might pass for puberty) span nearly a decade: age 12 ( DeKeyser et al., 2010 ), age 15 ( Flege et al., 1999 ), age 16 ( Abrahamsson & Hyltenstam, 2008 , 2009 ), age 17 ( Johnson & Newport, 1989 ), age 18 ( DeKeyser et al., 2010 ), and age 20 ( Birdsong & Molis, 2001 ). Obviously, the rate at which individuals reach sexual maturity varies widely from case to case, and if the goal is to fix a point at which childhood neural development officially ends, it might be worth trying to locate this point on an individual basis. This is not an academic exercise. It would parallel the Pena, Werker, and Dehaene-Lambertz (2012) study of premature babies in order to determine if the benchmarks of phonological organization in the first year of life are tied to neural development or to the extent of language exposure. This work shows that sensitivity to linguistic input, at least for phonological learning, is yoked to phases in brain development. As Newport points out in her commentary, we now know much more about the brain changes that occur throughout adulthood that may, or may not, relate to L2 AoA effects in adulthood. In their commentary, Reh, Arredondo, and Werker (2018) suggest that the slower maturation of the frontal lobe relative to the earlier maturation of posterior brain areas may play a role in L2 learning, as also proposed by Thompson-Schill, Ramscar, and Chrysikou (2009) .

Several commentators ( Abrahamsson, 2018 ; Hyltenstam, 2018 ; Veríssimo, 2018 ) suggested that the materials used to test L2 proficiency are often lacking in theoretical sophistication and empirical rigor, and that the results of such studies should be taken with a grain of salt. We could not agree more, not only with regard to studies of ultimate attainment, but also – and perhaps especially – in neuroimaging studies. L2 proficiency has been defined in mostly ad hoc ways in the literature. L2 researchers could avail themselves of already established, comprehensive and detailed systems for determining language proficiency levels, including near-native and native: the Interagency Language Roundtable (ILR) Oral Proficiency Interview (OPI), used across U.S. federal service agencies for decades now, and the Common European Framework of Reference (CEFR) for languages, in use within the EU since 1996. In fact, these two scales have been calibrated against each other for a decade now as well, so their neglect in L2 research is puzzling.

Language measurement and cognitive factors in late L1 acquisition

The fact that sign languages are subject to AoA effects prompted several commentators to conclude that sign languages are just like spoken languages ( Birdsong & Quinto-Pozos, 2018 ; Bialystok & Kroll, 2018 ; DeKeyser, 2018 ; Veríssimo, 2018 ) and we of course agree. We also agree with the commentators who pointed out that the stimuli and tasks for AoA studies need to be carefully selected to determine whether different critical periods may differentially affect varying levels or domains of linguistic structures ( Abrahamsson, 2018 ; Lillo-Martin, 2018 ; Veríssimo, 2018 ). In turn, these commentators would probably agree with us that the particular question under investigation and the formal linguistic descriptions available for the language under study determine how AoA experiments can be crafted. It is easy to lose sight of the fact that sign languages have only recently been distinguished from gesture and admitted into the family of human languages ( Goldin-Meadow & Brentari, 2015 ). Research detailing the grammar of sign languages, ASL in particular, remains in its infancy compared with the long-available descriptions of, for example, English, German, Turkish, or Swedish. Our initial studies had the goal of determining whether AoA effects were apparent in ASL at all – hence, our use of global processing measures like shadowing or sentence memory ( Veríssimo, 2018 ). While much progress has been made describing ASL grammar ( Sandler & Lillo-Martin, 2006 ), linguists disagree about such basic linguistic phenomena in ASL as syllabification, verb agreement, anaphora, or pronominal forms, among others ( Frederiksen & Mayberry, 2016 ; Lillo-Martin & Meier, 2011 ; Wilbur, 2011 ). Such ambiguities in formal linguistic description make it difficult, but not impossible, to ask whether late L1 acquisition affects particular domains of ASL grammar more than others.

We agree that all of a person’s language representations, which can include more than one language in more than one sensory-motor modality, come into play during language processing ( Bialystok & Kroll, 2018 ; Birdsong & Quinto-Pozos, 2018 ). Our working definition of late L1 acquisition is that the learner has few linguistic representations available at the onset of his or her initial ASL exposure. Deaf ASL signers who have linguistic representations available to them in other languages and forms that were established in early life perform at levels closer to those of earlier learners than late L1 learners. We were able to observe this in our original AoA studies. For example, when the task became difficult, one deaf signer began to reproduce ASL sentences entirely in fingerspelling, which formed the primary basis of this individual’s early education. Another participant began subvocalizing when the ASL sentence task became hard; this participant became deaf at age 4 rather than at birth. It was these observations of deaf participants using languages and forms other than ASL that led us to hypothesize that critical period primarily affects first language acquisition ( Mayberry, 1993 ; Mayberry & Lock, 2003 ; Mayberry, Lock & Kazmi, 2002 ). We do not pre-screen potential participants for their ASL skills. Instead we screen them for early language experience according to self-report. Some individuals who self-report as late L1 learners are clearly more akin to late “quasi-L2 ASL” learners. We believe this accounts for the individual variation apparent in some of our studies ( Emmorey, 2018 ).

In her commentary, Emmorey asks whether individual differences among late L1 learners might be due to varying levels of motivation or cognitive abilities. Although we have not attempted to measure it, the motivation of deaf individuals to learn ASL, including those who learn it after minimal childhood language experience, is extremely high. This is illustrated by the stories deaf signers tell about their ASL learning and how it has changed their lives ( Valli, Lucas, Farb & Kulick, 1992 ). The life transforming attributes of learning ASL are a common theme in ASL poetry and literature ( Perlmutter, 2008 ). The logical problem with attributing attenuated levels of ASL development to working memory is that its development is known to be inextricably tied to language development ( Gathercole & Baddeley, 1993 ). Working memory further relates to the development of executive function, which is also correlated with level of language development ( Botting, Jones, Marshall, Denmark, Atkinson & Morgan, 2017 ; Hall, Eigsti, Bortfeld & Lillo-Martin, 2017 ). In this sense, working memory and executive function might be considered as being comorbidities of acquiring a first language after early childhood.

With respect to general cognitive functioning, it is important to know that hundreds of studies of deaf individuals’ IQ – spanning more than a century – have repeatedly found the deaf population to score within the normal range of the hearing population on non-verbal IQ scales, despite widespread language deprivation in this population ( Braden, 1994 ; Mayberry, 2002 ). Among the cognitive skills tapped by various non-verbal IQ tasks, spatial cognition is a notable strength among late L1 learners. For example, many late L1 learners have excellent navigation and drawing skills. Consistent with spatial cognitive strengths, late L1 learners show greater proficiency with ASL classifier constructions that encode spatial relations in contrast to ASL syntactic constructions that do not ( Boudreault & Mayberry, 2006 ; Mayberry, Cheng, Hatrak & Ilkbasaran, in preparation ). These linguistic strengths begin to address the question of whether some aspects of linguistic structure are more sensitive to AoA than others ( Bley-Vroman, 2018 ; Lillo-Martin, 2018 ; Long & Granena, 2018 ; Veríssimo, 2018 ), an important question in need of further investigation.

The quantity and quality of linguistic input, in various cognitive domains, and education may interact with L1 AoA effects, as several commentators suggested ( Birdsong & Quinto-Pozos, 2018 ; Emmorey, 2018 ; Flege, 2018 ; Long & Granena, 2018 ; Newport, 2018 ). We agree and note that studies of how linguistic frequency interacts with L1 AoA effects have yet to be conducted. The most common source of language input for deaf late learners is through education. Deaf late L1 learners who are able to attend school with other deaf signers receive more ASL input than those without such opportunities. The extent to which this increased input boosts ASL language levels remains to be investigated ( Henner, Caldwell-Harris, Novogrodsky & Hoffmeister, 2016 ).

Woll describes a case study of a deaf man, M, whose L1 acquisition began in his late 20s and who had 25 years of experience with British Sign Language. M’s language skills are consistent with those of our case study, Martin, who began to acquire sign language as an L1 at age 21 and had 30 years of experience with ASL ( Mayberry, Davenport, Roth & Halgren, 2018 ). Both cases showed limited morphological and syntactic ability and reduced abilities to comprehend and produce sign language, British Sign Language for M and ASL for Martin. Notably, both individuals are described as having excellent navigation skills. Unlike Bialystok and Kroll, we do not interpret the fact that individuals such as these cases are able to learn some sign language as evidence against a critical period for language. A modicum of vocabulary assembled in utterances with sparse morphology or syntax does not, in our view, constitute a functional language system, just as the ability to detect light, and the edges of objects after cataract removal in adulthood does not indicate a functional visual system. Nor do we think that late L1 learners are similar to heritage language learners ( Bialystok & Kroll, 2018 ; Birdsong & Quinto-Pozos, 2018 ; Lillo-Martin, 2018 ; White, 2018 ) for the simple reason that heritage language users have fully developed linguistic representations and processes available to them in the form of their dominant language.

Creating the capacity to learn language

A number of commentators noted that Johnson and Newport (1989) originally proposed two possible mechanisms to underlie AoA effects, maturation versus exercise. The later hypothesis is also referred to as the “use it or lose it” explanation ( Abrahamsson, 2018 ; Bley-Vroman, 2018 ; DeKeyser, 2018 ; Hyltenstam, 2018 ; Veríssimo, 2018 ; White, 2018 ). While our research with deaf late L1 learners suggests that the capacity to learn language diminishes with age ( Bley-Vroman, 2018 ; Hyltenstam, 2018 ; DeKeyser, 2018 ; Veríssimo, 2018 ), we think that a more accurate theoretical framing of the phenomenon is that a prolonged delay in language exposure leads to a diminished capacity to learn language. In the case of deaf late L1 learners, the infant brain was ready to interact with the environment linguistically, but the environment failed to yield the necessary language input. In his figure, Hyltenstam shows a steep decline in ultimate language outcome incorporating data from L2 learners with that of the late L1 learners reported in the literature. We think this figure summarizes these phenomena well, but our theoretical reframing would turn it upside down. All language learners begin with an intercept of zero. Reflecting the creation of language ability, individuals whose language experience begins in infancy show a steep upward trajectory in the acquisition of language structure. This language learning curve asymptotes at lower than native-speaker/signer levels, the older the onset of L2 learning. In addition, the probability that the learning curve will approach native-like levels declines sharply the longer the delay in L1 exposure. This framework illustrates the “hybrid” hypothesis proposed by Newport.

Studies of language acquisition in late L1 learners indicate that the outcome of language acquisition is not governed by cognitive maturation but by the cognitive processes of deciphering linguistic structure in synchrony with neural development. Despite being cognitively mature, adolescents acquiring language for the first time begin the process by learning vocabulary, which they subsequently combine into single predicate utterances. The older the age onset of L1 experience, the less likely the learner will progress to more complex morphological and syntactic structures ( Cheng & Mayberry, under review ; Mayberry, Cheng, Hatrak & Ilkbasaran, 2017 ). Although the infant brain shows activation in response to spoken language in the expected left hemisphere areas in response to language ( Dehaene-Lambertz, Dehaene & Hertz-Pannier, 2002 ), multiple neural changes that occur throughout childhood affect the brain language system as well. The infant brain matures from posterior to anterior regions, and this is evident in children’s language processing too ( Schlaggar, Brown, Lugar, Visscher, Miezin & Petersen, 2002 ). During childhood the brain language system becomes more lateralized and consolidated ( Berl, Mayo, Parks, Rosenberger, VanMeter, Ratner, Vaidya & Gaillard, 2014 ). The brain language system also becomes more robustly connected over childhood. Dorsal pathways connecting language areas in the temporal and frontal lobes become increasing myelinated ( Pujol, Soriano-Mas, Oritz, Sebastián-Gallés & Deus, 2006 ). Increased myelination of left hemisphere fiber tracts correlates with the onset of complex sentence comprehension in typically developing children during late childhood ( Skeide, Brauer & Friederici, 2016 ). Deaf signers who began to learn ASL after childhood show reduced myelination of these fiber tracts and show concomitant difficulty comprehending complex ASL sentences ( Cheng, Roth, Halgren & Mayberry, under review ). Thus the act of learning language may trigger neural development throughout varying stages in the development of the brain language system. This scenario of reciprocal linguistic input effects on postnatal brain growth and vice versa would create the ability to learn language by enlarging the information processing capacity of the neurolinguistic system to recognize and manipulate linguistic representations. The task of L2 learning would thus be facilitated when a lexicon, grammar, and a neural language network are either being developed simultaneously or already in place. The task of L1 learning at older ages is impeded when the requisite neural architecture is not in place.

More research is required to determine the specific links between language acquisition and the development of the brain language system and the extent to which they are reciprocally causal. In this way, the study of this atypical, but unfortunately all too common, situation of late L1 acquisition among individuals born deaf promises to illuminate basic acquisitional and neurodevelopmental processes that together create the faculty of human language.

Acknowledgments

The research reported in this publication with ASL signers was supported in part by NIH grant R01DC012797. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Contributor Information

RACHEL I. MAYBERRY, Department of Linguistics, University of California San Diego.

ROBERT KLUENDER, Department of Linguistics, University of California San Diego.

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• DOI: 10.7916/D82V2TPX
• Corpus ID: 37961682

The Critical Period Hypothesis: Support, Challenge, and Reconceptualization

• A. Schouten
• Published 31 May 2009
• Linguistics

22 Citations

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Cognitive scientists define critical period for learning language

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A great deal of evidence suggests that it is more difficult to learn a new language as an adult than as a child, which has led scientists to propose that there is a “critical period” for language learning. However, the length of this period and its underlying causes remain unknown.

A new study performed at MIT suggests that children remain very skilled at learning the grammar of a new language much longer than expected — up to the age of 17 or 18. However, the study also found that it is nearly impossible for people to achieve proficiency similar to that of a native speaker unless they start learning a language by the age of 10.

“If you want to have native-like knowledge of English grammar you should start by about 10 years old. We don’t see very much difference between people who start at birth and people who start at 10, but we start seeing a decline after that,” says Joshua Hartshorne, an assistant professor of psychology at Boston College, who conducted this study as a postdoc at MIT.

People who start learning a language between 10 and 18 will still learn quickly, but since they have a shorter window before their learning ability declines, they do not achieve the proficiency of native speakers, the researchers found. The findings are based on an analysis of a grammar quiz taken by nearly 670,000 people, which is by far the largest dataset that anyone has assembled for a study of language-learning ability.

“It’s been very difficult until now to get all the data you would need to answer this question of how long the critical period lasts,” says Josh Tenenbaum, an MIT professor of brain and cognitive sciences and an author of the paper. “This is one of those rare opportunities in science where we could work on a question that is very old, that many smart people have thought about and written about, and take a new perspective and see something that maybe other people haven’t.”

Steven Pinker, a professor of psychology at Harvard University, is also an author of the paper, which appears in the journal Cognition on May 1.

Quick learners

While it’s typical for children to pick up languages more easily than adults — a phenomenon often seen in families that immigrate to a new country — this trend has been difficult to study in a laboratory setting. Researchers who brought adults and children into a lab, taught them some new elements of language, and then tested them, found that adults were actually better at learning under those conditions. Such studies likely do not accurately replicate the process of long-term learning, Hartshorne says.

“Whatever it is that results in what we see in day-to-day life with adults having difficulty in fully acquiring the language, it happens over a really long timescale,” he says.

Following people as they learn a language over many years is difficult and time-consuming, so the researchers came up with a different approach. They decided to take snapshots of hundreds of thousands of people who were in different stages of learning English. By measuring the grammatical ability of many people of different ages, who started learning English at different points in their life, they could get enough data to come to some meaningful conclusions.

Hartshorne’s original estimate was that they needed at least half a million participants — unprecedented for this type of study. Faced with the challenge of attracting so many test subjects, he set out to create a grammar quiz that would be entertaining enough to go viral.

With the help of some MIT undergraduates, Hartshorne scoured scientific papers on language learning to discover the grammatical rules most likely to trip up a non-native speaker. He wrote questions that would reveal these errors, such as determining whether a sentence such as “Yesterday John wanted to won the race” is grammatically correct. 

To entice more people to take the test, he also included questions that were not necessary for measuring language learning, but were designed to reveal which dialect of English the test-taker speaks. For example, an English speaker from Canada might find the sentence “I’m done dinner” correct, while most others would not.

Within hours after being posted on Facebook, the 10-minute quiz “ Which English? ” had gone viral.

“The next few weeks were spent keeping the website running, because the amount of traffic we were getting was just overwhelming,” Hartshorne says. “That’s how I knew the experiment was sufficiently fun.”

A long critical period

After taking the quiz, users were asked to reveal their current age and the age at which they began learning English, as well as other information about their language background. The researchers ended up with complete data for 669,498 people, and once they had this huge amount of data, they had to figure out how to analyze it.

“We had to tease apart how many years has someone been studying this language, when they started speaking it, and what kind of exposure have they been getting: Were they learning in a class or were they immigrants to an English-speaking country?” Hartshorne says.

The researchers developed and tested a variety of computational models to see which was most consistent with their results, and found that the best explanation for their data is that grammar-learning ability remains strong until age 17 or 18, at which point it drops. The findings suggest that the critical period for learning language is much longer than cognitive scientists had previously thought.

“It was surprising to us,” Hartshorne says. “The debate had been over whether it declines from birth, starts declining at 5 years old, or starts declining starting at puberty.”

The authors note that adults are still good at learning foreign languages, but they will not be able to reach the level of a native speaker if they begin learning as a teenager or as an adult.

"Although it has long been observed that learning a second language is easier early in life, this study provides the most compelling evidence to date that there is a specific time in life after which the ability to learn the grammar of a new language declines," says Mahesh Srinivasan, an assistant professor of psychology at the University of California at Berkeley, who was not involved in the study. “This is a major step forward for the field. The study also opens surprising, new questions, because it suggests that the critical period closes much later than previously thought."

Still unknown is what causes the critical period to end around age 18. The researchers suggest that cultural factors may play a role, but there may also be changes in brain plasticity that occur around that age.

“It’s possible that there’s a biological change. It’s also possible that it’s something social or cultural,” Tenenbaum says. “There’s roughly a period of being a minor that goes up to about age 17 or 18 in many societies. After that, you leave your home, maybe you work full time, or you become a specialized university student. All of those might impact your learning rate for any language.”

Hartshorne now plans to run some related studies in his lab at Boston College, including one that will compare native and non-native speakers of Spanish. He also plans to study whether individual aspects of grammar have different critical periods, and whether other elements of language skill such as accent have a shorter critical period.

The researchers also hope that other scientists will make use of their data, which they have posted online , for additional studies.

“There are lots of other things going on in this data that somebody could analyze,” Hartshorne says. “We do want to draw other scientists’ attention to the fact that the data is out there and they can use it.”

The research was funded by the National Institutes of Health and MIT’s Center for Minds, Brains, and Machines.

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Bucking conventional wisdom, research co-authored by Prof. Josh Tenenbaum shows that “picking up the subtleties of grammar in a a second language does not fade until well into the teens,” writes Dana G. Smith for Scientific American . “To become completely fluent, however, learning should start before the age of 10.”

New research suggests “children are highly skilled at learning the grammar of a new language up until the age of 17 or 18, much longer than previously thought,” reports Kashmira Gander in Newsweek. “We may need to go back to the drawing board in trying to explain why adults have trouble learning language,” Joshua Hartshorne, who co-wrote the study as a postdoc at MIT, tells Gander.

A study co-authored by Prof. Josh Tenenbaum finds that learning a new language should start before age 10 to achieve a native-like grasp of the grammar, reports BBC News . People remain highly skilled language learners until about 17 or 18, but then fall off, which Tenenbaum says could be due to “a biological change” or “something social or cultural.”

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Critical Period

• Reference work entry
• First Online: 01 January 2021
• pp 1588–1590
• Cite this reference work entry

• Yan Wang 3 &
• Jing Guo 3  

422 Accesses

Crucial time ; Sensitive period

A maturational stage during the lifespan of an organism in which the organism’s nervous system is especially sensitive to certain environmental stimuli. The organism is more sensitive to environmental stimulation during a critical period than at other times during its life.

Introduction

The phenomenon of critical period was first described by William James ( 1899 ) as “the transitoriness of instincts.” The term “critical period” was proposed by the Austrian ecologist based on his observations that newly hatched poultries, such as chicks and geese, would follow the object, usually their mother, if exposed to within a certain short time after birth.

According to Lorenz, if the young animal was not exposed to the particular stimulus during the “critical period” to learn a given skill or trait, it would become extremely struggling to develop particular behavioral pattern in the later life.

A vast of existing literature has identified the...

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Wang, Y., Guo, J. (2021). Critical Period. In: Shackelford, T.K., Weekes-Shackelford, V.A. (eds) Encyclopedia of Evolutionary Psychological Science. Springer, Cham. https://doi.org/10.1007/978-3-319-19650-3_1060

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Language Acquisition Theory

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On This Page:

Language is a cognition that truly makes us human. Whereas other species do communicate with an innate ability to produce a limited number of meaningful vocalizations (e.g., bonobos) or even with partially learned systems (e.g., bird songs), there is no other species known to date that can express infinite ideas (sentences) with a limited set of symbols (speech sounds and words).

This ability is remarkable in itself. What makes it even more remarkable is that researchers are finding evidence for mastery of this complex skill in increasingly younger children.

Infants as young as 12 months are reported to have sensitivity to the grammar needed to understand causative sentences (who did what to whom; e.g., the bunny pushed the frog (Rowland & Noble, 2010).

After more than 60 years of research into child language development, the mechanism that enables children to segment syllables and words out of the strings of sounds they hear and to acquire grammar to understand and produce language is still quite an enigma.

Behaviorist Theory of Language Acquisition

One of the earliest scientific explanations of language acquisition was provided by Skinner (1957). As one of the pioneers of behaviorism , he accounted for language development using environmental influence, through imitation, reinforcement, and conditioning.

In this view, children learn words and grammar primarily by mimicking the speech they hear and receiving positive feedback for correct usage.

Skinner argued that children learn language based on behaviorist reinforcement principles by associating words with meanings. Correct utterances are positively reinforced when the child realizes the communicative value of words and phrases.

For example, when the child says ‘milk’ and the mother smiles and gives her some. As a result, the child will find this outcome rewarding, enhancing the child’s language development (Ambridge & Lieven, 2011).

Over time, through repetition and reinforcement, they refine their linguistic abilities. Critics argue this theory doesn’t fully explain the rapid pace of language acquisition nor the creation of novel sentences.

Chomsky Theory of Language Development

However, Skinner’s account was soon heavily criticized by Noam Chomsky, the world’s most famous linguist to date.

In the spirit of the cognitive revolution in the 1950s, Chomsky argued that children would never acquire the tools needed for processing an infinite number of sentences if the language acquisition mechanism was dependent on language input alone.

Noam Chomsky introduced the nativist theory of language development, emphasizing the role of innate structures and mechanisms in the human brain. Key points of Chomsky’s theory include:

Language Acquisition Device (LAD): Chomsky proposed that humans have an inborn biological capacity for language, often termed the LAD, which predisposes them to acquire language.

Universal Grammar: He suggested that all human languages share a deep structure rooted in a set of grammatical rules and categories. This “universal grammar” is understood intuitively by all humans.

Poverty of the Stimulus: Chomsky argued that the linguistic input received by young children is often insufficient (or “impoverished”) for them to learn the complexities of their native language solely through imitation or reinforcement. Yet, children rapidly and consistently master their native language, pointing to inherent cognitive structures.

Critical Period: Chomsky, along with other linguists, posited a critical period for language acquisition, during which the brain is particularly receptive to linguistic input, making language learning more efficient.

Critics of Chomsky’s theory argue that it’s too innatist and doesn’t give enough weight to social interaction and other factors in language acquisition.

Universal Grammar

Consequently, he proposed the theory of Universal Grammar: an idea of innate, biological grammatical categories, such as a noun category and a verb category, that facilitate the entire language development in children and overall language processing in adults.

Universal Grammar contains all the grammatical information needed to combine these categories, e.g., nouns and verbs, into phrases. The child’s task is just to learn the words of her language (Ambridge & Lieven).

For example, according to the Universal Grammar account, children instinctively know how to combine a noun (e.g., a boy) and a verb (to eat) into a meaningful, correct phrase (A boy eats).

This Chomskian (1965) approach to language acquisition has inspired hundreds of scholars to investigate the nature of these assumed grammatical categories, and the research is still ongoing.

Contemporary Research

A decade or two later, some psycho-linguists began to question the existence of Universal Grammar. They argued that categories like nouns and verbs are biologically, evolutionarily, and psychologically implausible and that the field called for an account that can explain the acquisition process without innate categories.

Researchers started to suggest that instead of having a language-specific mechanism for language processing, children might utilize general cognitive and learning principles.

Whereas researchers approaching the language acquisition problem from the perspective of Universal Grammar argue for early full productivity, i.e., early adult-like knowledge of the language, the opposing constructivist investigators argue for a more gradual developmental process. It is suggested that children are sensitive to patterns in language which enables the acquisition process.

An example of this gradual pattern learning is morphology acquisition. Morphemes are the smallest grammatical markers, or units, in language that alter words. In English, regular plurals are marked with an –s morpheme (e.g., dog+s).

Similarly, English third singular verb forms (she eat+s, a boy kick+s) are marked with the –s morpheme. Children are considered to acquire their first instances of third singular forms as entire phrasal chunks (Daddy kicks, a girl eats, a dog barks) without the ability to tease the finest grammatical components apart.

When the child hears a sufficient number of instances of a linguistic construction (i.e., the third singular verb form), she will detect patterns across the utterances she has heard. In this case, the repeated pattern is the –s marker in this particular verb form.

As a result of many repetitions and examples of the –s marker in different verbs, the child will acquire sophisticated knowledge that, in English, verbs must be marked with an –s morpheme in the third singular form (Ambridge & Lieven, 2011; Pine, Conti-Ramsden, Joseph, Lieven & Serratrice, 2008; Theakson & Lieven, 2005).

Approaching language acquisition from the perspective of general cognitive processing is an economic account of how children can learn their first language without an excessive biolinguistic mechanism.

However, finding a solid answer to the problem of language acquisition is far from being over. Our current understanding of the developmental process is still immature.

Investigators of Universal Grammar are still trying to convince that language is a task too demanding to acquire without specific innate equipment, whereas constructivist researchers are fiercely arguing for the importance of linguistic input.

The biggest questions, however, are yet unanswered. What is the exact process that transforms the child’s utterances into grammatically correct, adult-like speech? How much does the child need to be exposed to language to achieve the adult-like state?

What account can explain variation between languages and the language acquisition process in children acquiring very different languages to English? The mystery of language acquisition is granted to keep psychologists and linguists alike astonished decade after decade.

What is language acquisition?

Language acquisition refers to the process by which individuals learn and develop their native or second language.

It involves the acquisition of grammar, vocabulary, and communication skills through exposure, interaction, and cognitive development. This process typically occurs in childhood but can continue throughout life.

What is Skinner’s theory of language development?

Skinner’s theory of language development, also known as behaviorist theory, suggests that language is acquired through operant conditioning. According to Skinner, children learn language by imitating and being reinforced for correct responses.

He argued that language is a result of external stimuli and reinforcement, emphasizing the role of the environment in shaping linguistic behavior.

What is Chomsky’s theory of language acquisition?

Chomsky’s theory of language acquisition, known as Universal Grammar, posits that language is an innate capacity of humans.

According to Chomsky, children are born with a language acquisition device (LAD), a biological ability that enables them to acquire language rules and structures effortlessly.

He argues that there are universal grammar principles that guide language development across cultures and languages, suggesting that language acquisition is driven by innate linguistic knowledge rather than solely by environmental factors.

Ambridge, B., & Lieven, E.V.M. (2011). Language Acquisition: Contrasting theoretical approaches . Cambridge: Cambridge University Press.

Chomsky, N. (1965). Aspects of the Theory of Syntax . MIT Press.

Pine, J.M., Conti-Ramsden, G., Joseph, K.L., Lieven, E.V.M., & Serratrice, L. (2008). Tense over time: testing the Agreement/Tense Omission Model as an account of the pattern of tense-marking provision in early child English. Journal of Child Language , 35(1): 55-75.

Rowland, C. F.; & Noble, C. L. (2010). The role of syntactic structure in children’s sentence comprehension: Evidence from the dative. Language Learning and Development , 7(1): 55-75.

Skinner, B.F. (1957). Verbal behavior . Acton, MA: Copley Publishing Group.

Theakston, A.L., & Lieven, E.V.M. (2005). The acquisition of auxiliaries BE and HAVE: an elicitation study. Journal of Child Language , 32(2): 587-616.

Further Reading

An excellent article by Steven Pinker on Language Acquisition

Pinker, S. (1995). The New Science of Language and Mind . Penguin.

Tomasello, M. (2005). Constructing A Language: A Usage-Based Theory of Language Acquisition . Harvard University Press.