Biological Bases of Language Development

Eric Pakulak,1,2 PhD, Amanda Hampton Wray,3 PhD

1University of Oregon, USA

2Stockholm University, Sweden

3Michigan State University, USA

October 2018, Rev. ed.

Introduction and Subject

Advances in neuroimaging allow for the investigation of the neurobiological bases of language and the effects of environmental and genetic factors on neural organization for language in children. An understanding of the neurobiology of language has important implications for those seeking to optimize language development. Insights from this research may support practical, evidence-based advice for parents as well as the development of language and literacy curricula for first and second language learners.


A complex interaction between genetic and environmental factors produces substantial variation in rates of language development among children. Many behavioural studies illuminate the effects of environmental factors on language development; however, less is known about the neurobiological underpinnings of these effects. Most neurobiological research concerns individuals from middle and higher socioeconomic status (SES) backgrounds. 

Research Context

Research on the neurobiology of language uses neuroimaging techniques with exquisite temporal resolution (e.g., event-related potentials; ERPs) and complementary techniques with exquisite spatial resolution (e.g., functional magnetic resonance imaging; fMRI). ERPs are better suited for use with infants and children, although fMRI is also used with younger populations. Increasingly, these methods are being used to characterize the developmental timecourse of different language subsystems and to more precisely examine the effects of language experience, and the timing of these effects, on the development of different language functions and on the neural mechanisms which mediate these subsystems. 

Key Research Questions

Key research questions involve the use of neuroimaging techniques to characterize:

  1. the timecourse of the development of neural substrates of different subsystems of language, 
  2. the effects of environmental and genetic factors on the development of these neural substrates, and
  3. the time periods during which the effects of environmental and genetic factors are maximal (i.e., sensitive periods) for each subsystem. 

Recent Research Results

The neurobiological bases of three linguistic subsystems have been studied, specifically phonology (sound system of the language), semantics (vocabulary and word meanings), and syntax (grammar). This research shows that brain responses to language at early ages are predictive of later language proficiency. 

Within the first year of life infants become increasingly sensitive to speech sound contrasts important to their native language(s) and insensitive to unimportant phonetic contrasts.1 This sensitivity to native language contrasts is reflected in a brain response which has been shown in adults to be a neural index of phonetic discrimination: in 7.5-month-old infants the brain response to native language contrasts correlated with behavioural perception of these contrasts.2  Furthermore, an increased neural response at 7.5 months predicts word production and sentence complexity at 24 months and mean length of utterance at 30 months. The inverse relationship was noted for discrimination of non-native contrasts.2

ERP methodology has also been used to examine early word learning and associated changes in neural specialization. In 13-month-olds the brain response to known words differs from that to unknown words, with this effect broadly distributed over both the left and right hemispheres.3 By 20 months of age this effect was limited to the left hemisphere, a pattern more like that seen in adults and one associated with increased specialization for language processing. In addition, such increased brain specialization is also associated with greater language ability in children of the same chronological age.4

Developmental increases in neural specialization for language are associated with differences in SES.  For example, differences in the structure of left frontal brain areas important for language processing were found in five-year old children as a function of SES.5 Another study found that SES predicted brain volume in left frontal and posterior brain areas important for language; furthermore, these SES differences may increase with age.6 Lower SES was also associated with reduced surface area in multiple brain regions, including frontal regions supporting language.7 These relationships may endure into adulthood: in adults, socioeconomic deprivation predicts the degree of thinning in the cortex in posterior language areas.8 Retrospective childhood SES also predicts language proficiency and early neural response to syntax over left frontal brain areas in adults.9 

Neuroimaging studies of young children show increasingly adult-like brain activation patterns to printed letters and cortical thickening in language-relevant areas with differences in parental language input and following reading interventions with children at-risk for reading disorders and with children from lower SES backgrounds.10,11,12

Numerous ERP sentence processing studies of adults have shown that semantic and syntactic subsystems are processed by different brain systems across spoken, written and signed languages, which share these different subsystems.13 Studies of bilinguals of both spoken and signed languages show that these distinct subsystems display different degrees of plasticity with different sensitive periods.14,15,16 In these studies, a comparison is made between the brain responses to correct sentences versus sentences that violate semantic or syntactic expectations (e.g., “My uncle will blow the movie” or “My uncle will watching the movie”). In adults, specialized and efficient brain function is indexed by neural responses that originate from relatively focal brain areas whereas such responses in children may be more widespread in the brain.17-23 

The few ERP studies of sentence processing in children suggest that this specialization of different brain systems occurs early in development. A brain response similar to that elicited by semantic violations in adults has been reported reliably in five-year old children, and even in children as young as 19 months.17,20 This brain response predicted expressive language proficiency at 30 months of age and becomes faster and more specialized with age.18,19 ERP responses to syntactic violations in children are qualitatively different than the response to semantic violations. Though slower and more widely distributed, the response to syntactic violations found in children is similar to that found in adults.22-24 The neural response to semantic and syntactic violations in 3- to 8 year-old children has also been found to vary as a function of language proficiency, other cognitive skills, and SES.25 Longitudinal ERP studies suggest that, between ages four and five years, children from higher SES backgrounds exhibit more rapid maturation of ERP indices of both semantic and syntactic processing than peers from lower SES backgrounds.26

Recent ERP research has also examined a cognitive system shown to be important for the development of language skills: specifically selective attention to one auditory stimulus while ignoring a competing auditory stimulus. Selective attention is indexed by a larger brain response (ERP) to the attended auditory event compared with the competing auditory event. This attention effect is reduced in children diagnosed with specific language impairment27 and in typically developing children from lower SES environments.28,29,30 Differences in the effects of attention on neural processes in children from lower SES backgrounds have been found to be associated with genetic allelic differences, specifically in the serotonin system (i.e., 5-HTTLPR31). 

Importantly, this cognitive system is changeable with experience in young children. For example, high-intensity training was found to increase both language proficiency as well as the effects of attention on neural processing in 6-8 year-olds.32  Essentially, parents can change these cognitive systems:  a two-generation intervention study found changes specific to families who received a more parent-focused model of the program.  Parents increased conversational turn-taking with their children, and children improved language proficiency  as well as brain function for selective attention.33

Research Gaps

Further research on the neurobiology of language development is required to better understand underlying environmental and genetic factors; for example, studies of typically developing children from a wider range of SES backgrounds.  Additional studies with clinical populations will increase understanding of neurobiological changes that occur with different disorders.  For example, see emerging research on neurobiology of stuttering.34-36 Another important next step is to employ results from this research to design and implement evidence-based interventions which improve the skills necessary for the development of language and to determine the age(s) at which they are most effective.11,12,33 


Modern neuroimaging techniques are powerful tools for investigating the effects of environmental and genetic factors on the neurobiology of language development.  Research using these techniques with children from a wider range of SES backgrounds and other differences in early experience will lead to a more complete characterization of the developmental timecourse of language subsystems and effects of environmental factors on this development. 

Implications for Parents, Services and Policy

This basic research can drive the development of evidence-based policies and services which improve language and other cognitive skills important for academic achievement.e.g.,11,12,33 Such research can also provide specific, evidence-based suggestions for parents. This is the focus of a non-profit video program produced by the University of Oregon Brain Development Lab (


  1. Kuhl P, Rivera-Gaxiola M. Neural substrates of language acquisition. Annual review of neuroscience2008;31:511-534.
  2. Kuhl PK, Conboy BT, Coffey-Corina S, Padden D, Rivera-Gaxiola M, Nelson T. Phonetic learning as a pathway to language: new data and native language magnet theory expanded (NLM-e). Philosophical transactions of the Royal Society of London - Series B: Biological sciences 2008;363(1493):979-1000.
  3. Mills DL, Coffey-Corina S, Neville HJ. Language comprehension and cerebral specialization from 13 to 20 months. Developmental Neuropsychology 1997;13(3):397-445.
  4. Mills DL, Coffey-Corina SA, Neville HJ. Language acquisition and cerebral specialization in 20-month-old infants. Journal of Cognitive Neuroscience 1993;5(3):317-334.
  5. Raizada RD, Richards TL, Meltzoff A, Kuhl PK. Socioeconomic status predicts hemispheric specialisation of the left inferior frontal gyrus in young children. Neuroimage 2008;40(3):1392-1401.
  6. Noble KG, Houston SM, Kan E, Sowell ER. Neural correlates of socioeconomic status in the developing human brain. Developmental science 2012;15(4):516-527.
  7. Noble KG, Houston SM, Brito NH, et al. Family income, parental education and brain structure in children and adolescents. Nature neuroscience 2015;18(5):773-778.
  8. Krishnadas R, McLean J, Batty GD, et al. Socioeconomic deprivation and cortical morphology: psychological, social, and biological determinants of ill health study. Psychosomatic medicine 2013;75(7):616-623.
  9. Pakulak E, Neville H. Proficiency differences in syntactic processing of monolingual native speakers indexed by event-related potentials. Journal of Cognitive Neuroscience 2010;22(12):2728-2529.
  10. Romeo RR, Leonard JA, Robinson ST, et al. Beyond the 30-Million-Word Gap: Children’s Conversational Exposure Is Associated With Language-Related Brain Function. Psychological science. 2018;29(5):700-710.
  11. Yamada Y, Stevens C, Harn B, Chard D, Neville H. Emergence of the neural network for reading in five-year-old beginning readers: A longitudinal fMRI study. NeuroImage 2011;57:704-713.
  12. Romeo RR, Christodoulou JA, Halverson KK, et al. Socioeconomic status and reading disability: Neuroanatomy and plasticity in response to intervention. Cerebral Cortex 2017;28(7):2297-2312.
  13. Neville HJ, Nicol JL, Barss A, Forster KI, Garrett MF. Syntactically based sentence processing classes: Evidence from event-related brain potentials. Journal of Cognitive Neuroscience 1991;3(2):155-170.
  14. Capek CM, Grossi G, Newman AJ, McBurney SL, Corina D, Roeder B, Neville HJ. Brain systems mediating semantic and syntactic processing in deaf native signers: biological invariance and modality specificity.Proceedings of the National Academy of Sciences of the United States of America 2009;106(21):8784-8789.
  15. Weber-Fox C, Neville HJ. Maturational constraints on functional specializations for language processing: ERP and behavioral evidence in bilingual speakers. Journal of Cognitive Neuroscience1996;8(3):231-256.
  16. Pakulak E, Neville H. Maturational constraints on the recruitment of early processes for syntactic processing. Journal of Cognitive Neuroscience 2011;23(10):2752-2765.
  17. Neville HJ, Coffey SA, Lawson DS, Fischer A, Emmorey K, Bellugi U. Neural systems mediating American sign language: effects of sensory experience and age of acquisition. Brain and Language1997;57(3):285-308.
  18. Holcomb PJ, Coffey SA, Neville HJ. Visual and auditory sentence processing: A Developmental analysis using event-related brain potentials. Developmental Neuropsychology 1992;8(2-3):203-241.
  19. Hahne A, Eckstein K, Friederici AD. Brain signatures of syntactic and semantic processes during children's language development. Journal of Cognitive Neuroscience 2004;16(7):1302-1318.
  20. Neville HJ, Coffey SA, Holcomb PJ, Tallal P. The neurobiology of sensory and language processing in language-impaired children. Journal of Cognitive Neuroscience 1993;5(2):235-253.
  21. Friedrich M, Friederici AD. N400-like semantic incongruity effect in 19-month-olds: processing known words in picture contexts. Journal of Cognitive Neuroscience 2004;16(8):1465-1477.
  22. Silva Pereyra JF, Klarman L, Lin LJ, Kuhl PK. Sentence processing in 30-month-old children: An event-related potential study. Neuroreport 2005;16(6):645-648.
  23. Silva-Pereyra J, Rivera-Gaxiola M, Kuhl PK. An event-related brain potential study of sentence comprehension in preschoolers: semantic and morphosyntactic processing. Cognitive Brain Research 2005;23(2-3):247-258.
  24. Oberecker R, Friederici AD. Syntactic event-related potential components in 24-month-olds' sentence comprehension. Neuroreport 2006;17(10):1017-1021.
  25. Hampton Wray A, Weber-Fox C. Specific aspects of cognitive and language proficiency account for variability in neural indices of semantic and syntactic processing in children. Developmental cognitive neuroscience 2013;5:149-171.
  26. Hampton Wray A, Pakulak E, Yamada Y, Weber C, Neville H. Development of neural processes underlying language subsystems in young children from higher and lower socioeconomic status environments. Cognitive Neuroscience Society 2016; New York City.
  27. Stevens C, Sanders L, Neville H. Neurophysiological evidence for selective auditory attention deficits in children with specific language impairment. Brain Research 2006;1111(1):143-152.
  28. Stevens C, Lauinger B, Neville H. Differences in the neural mechanisms of selective attention in children from different socioeconomic backgrounds: An event-related brain potential study. Developmental Science 2009;12(4):634-646.
  29. Hampton Wray A, Stevens C, Pakulak E, Isbell E, Bell T, Neville H. Development of selective attention in preschool-age children from lower socioeconomic status backgrounds. Developmental cognitive neuroscience 2017;26:101-111.
  30. Giuliano RJ, Karns CM, Roos LE, Bell TA, Petersen S, Skowron EA, Neville HJ, Pakulak E. Effects of early adversity on neural mechanisms of distractor suppression are mediated by sympathetic nervous system activity in preschool-aged children. Development Psychology 2018;54(9):1674-1686. doi: 10.1037/dev0000499
  31. Isbell E, Stevens C, Wray AH, Bell T, Neville HJ. 5-HTTLPR polymorphism is linked to neural mechanisms of selective attention in preschoolers from lower socioeconomic status backgrounds. Developmental cognitive neuroscience 2016;22:36-47.
  32. Stevens C, Fanning J, Coch D, Sanders L, Neville H. Neural mechanisms of selective auditory attention are enhanced by computerized training: Electrophysiological evidence from language-impaired and typically developing children. Brain Research 2008(1205):55-69.
  33. Neville H, Stevens C, Pakulak E, et al. Family-based training program improves brain function, cognition, and behavior in lower socioeconomic status preschoolers. Proceedings of the National Academy of Sciences 2013.
  34. Cuadrado EM, Weber-Fox CM. Atypical syntactic processing in individuals who stutter: Evidence from event-related brain potentials and behavioral measures. Journal of Speech, Language, and Hearing Research 2003;46(4):960-976.
  35. Hampton A, Weber-Fox C. Non-linguistic auditory processing in stuttering: evidence from behavior and event-related brain potentials. Journal of Fluency Disorders 2008;33(4):253-273.
  36. Kreidler K, Wray AH, Usler E, Weber C. Neural indices of semantic processing in early childhood distinguish eventual stuttering persistence and recovery. Journal of Speech, Language, and Hearing Research 2017;60(11):3118-3134.

How to cite this article:

Pakulak E, Hampton Wray A. Biological Bases of Language Development. In: Tremblay RE, Boivin M, Peters RDeV, eds. Rvachew S, topic ed. Encyclopedia on Early Childhood Development [online]. Updated October 2018. Accessed October 3, 2018.