Language screening in the pediatric office setting

Social Brain Perspectives on the Social and Evolutionary Neuroscience of Human Language

Human language and social cognition are two key disciplines that have traditionally been studied as separate domains. Nonetheless, an emerging view suggests an alternative perspective. Drawing on the theoretical underpinnings of the social brain hypothesis (thesis of the evolution of brain size and intelligence), the social complexity hypothesis (thesis of the evolution of communication), and empirical research from comparative animal behavior, human social behavior, language acquisition in children, social cognitive neuroscience, and the cognitive neuroscience of language, it is argued that social cognition and language are two significantly interconnected capacities of the human species. Here, evidence in support of this view reviews (1) recent developmental studies on language learning in infants and young children, pointing to the important crucial benefits associated with social stimulation for youngsters, including the quality and quantity of incoming linguistic information, dyadic infant/child-to-parent non-verbal and verbal interactions, and other important social cues integral for facilitating language learning and social bonding; (2) studies of the adult human brain, suggesting a high degree of specialization for sociolinguistic information processing, memory retrieval, and comprehension, suggesting that the function of these neural areas may connect social cognition with language and social bonding; (3) developmental deficits in language and social cognition, including autism spectrum disorder (ASD), illustrating a unique developmental profile, further linking language, social cognition, and social bonding; and (4) neural biomarkers that may help to identify early developmental disorders of language and social cognition. In effect, the social brain and social complexity hypotheses may jointly help to describe how neurotypical children and adults acquire language, why autistic children and adults exhibit simultaneous deficits in language and social cognition, and why nonhuman primates and other organisms with significant computational capacities cannot learn language. But perhaps most critically, the following article argues that this and related research will allow scientists to generate a holistic profile and deeper understanding of the healthy adult social brain while developing more innovative and effective diagnoses, prognoses, and treatments for maladies and deficits also associated with the social brain.

Towards a model of language neurobiology in early development

Understanding language neurobiology in early childhood is essential for characterizing the developmental structural and functional changes that lead to the mature adult language network. In the last two decades, the field of language neurodevelopment has received increasing attention, particularly given the rapid advances in the implementation of neuroimaging techniques and analytic approaches that allow detailed investigations into the developing brain across a variety of cognitive domains. These methodological and analytical advances hold the promise of developing early markers of language outcomes that allow diagnosis and clinical interventions at the earliest stages of development. Here, we argue that findings in language neurobiology need to be integrated within an approach that captures the dynamic nature and inherent variability that characterizes the developing brain and the interplay between behavior and (structural and functional) neural patterns. Accordingly, we describe a framework for understanding language neurobiology in early development, which minimally requires an explicit characterization of the following core domains: i) computations underlying language learning mechanisms, ii) developmental patterns of change across neural and behavioral measures, iii) environmental variables that reinforce language learning (e.g., the social context), and iv) brain maturational constraints for optimal neural plasticity, which determine the infant's sensitivity to learning from the environment. We discuss each of these domains in the context of recent behavioral and neuroimaging findings and consider the need for quantitatively modeling two main sources of variation: individual differences or trait-like patterns of variation and within-subject differences or state-like patterns of variation. The goal is to enable models that allow prediction of language outcomes from neural measures that take into account these two types of variation. Finally, we examine how future methodological approaches would benefit from the inclusion of more ecologically valid paradigms that complement and allow generalization of traditional controlled laboratory methods.

[Development of speech disorders in children]

The function of the formation of speech skills is decisive in the development of a child in communication and assimilation of information. Early pediatric diagnosis should become a routine practice of monitoring children from infancy to school age for the timely correction of speech disorders and associated dysgraphia and dyslexia. According to the ICD-10 classification, speech developmental disorders are divided into the following options: articulation impairment, delay in expressive and impressive speech. Articulation disorders, stuttering, impaired expressive speech are the most common and most favorable prognosis for speech therapy interventions. The data on the effectiveness of disorders of the receptive (impressive) language are ambiguous, since there is a high likelihood of a combination with neurogenetic diseases and autism. The development of speech therapy programs will make it possible to broader coverage of those in need of treatment, including complex course therapy with neuropeptides (cortexin).

Fast screening for children's developmental language disorders via comprehensive speech ability evaluation-using a novel deep learning framework

Background

Developmental language disorders (DLDs) are the most common developmental disorders in children. For screening DLDs, speech ability (SA) is one of the most important indicators.

Methods

In this paper, we propose a solution for the fast screening of children’s DLDs based on a comprehensive SA evaluation and a deep framework of machine learning. Fast screening is crucial for promoting the prevalence and practicality of DLD screening which in turn is important for the treatment of DLDs and related social and behavioral abnormalities (e.g., dyslexia and autism). Our solution is focused on addressing the drawbacks existing in the previous DLD screening methods which include test failure due to text-based inducing material design and illiteracy of most young children, incomplete language evaluation indicators, and professional-reliant evaluation procedures. First, to avoid test failure, a novel comprehensive inducing procedure (CIP) with non-text (i.e., audio-visual) stimulus materials was designed that could cover a large range of modalities to adequately explore the comprehensive SA of the subjects. Second, to address incomplete language evaluation, a set of comprehensive evaluation indicators with full consideration of the characteristics of the children’s language acquisition is proposed; furthermore, to break the professional-reliant limitation, we specifically designed a deep framework for fast and accurate screening.

Results

Experimental results showed that the proposed deep framework is effective and professional with a 92.6% accuracy on DLD screening. Additionally, to provide a benchmark for the novel problem, we provide a CIP dataset with about 2,200 responses from over 200 children, which may also be useful for further DLD studies and insightful for the fast screening design of other behavioral abnormalities.

Conclusions

Fast screening of children’s DLDs can be achieved at accuracy up to 92.6% by our proposed deep learning framework. For successful fast screening, an elaborated CIP with corresponding comprehensive evaluating indicators is necessary to be designed for children suspected to have DLDs.

Association between enterovirus infection and speech and language impairments: A nationwide population-based study

BACKGROUND AND AIMS

Delay and impairment in Speech and language are common developmental problems in younger populations. Hitherto, there has been minimal study of the association between common childhood infections (e.g. enterovirus [EV]) and speech and language. The impetus for evaluating this association is provided by evidence linking inflammation to neurodevelopmental disorders. Herein we sought to determine whether an association exists between EV infection and subsequent diagnoses of speech and language impairments in a nationwide population-based sample in Taiwan.

METHODS

Our study acquired data from the Taiwan National Health Insurance Research Database. The sample was comprised of individuals under 18 years of age with newly diagnosed EV infection during the period from January 1998 to December 2011. 39669 eligible cases were compared to matched controls and assessed during the study period for incident cases of speech and language impairments. Cox regression analyses were applied, adjusting for sex, age and other physical and mental problems.

RESULTS

In the fully adjusted Cox regression model for hazard ratios, EV infection as positively associated with speech and language impairments (HR = 1.14, 95% CI: 1.06-1.22) after adjusting for age, sex and other confounds. Compared to the control group, the hazard ratio for speech and language impairments was 1.12 (95% CI: 1.03-1.21) amongst the group of EV infection without hospitalization, and 1.26 (95% CI: 1.10-1.45) amongst the group of EV infection with hospitalization.

CONCLUSIONS

EV infection is temporally associated with incident speech and language impairments. Our findings herein provide rationale for educating families that EV infection may be associated with subsequent speech and language problems in susceptible individuals and that monitoring for such a presentation would be warranted. WHAT THIS PAPER ADDS?: Speech and language impairments associated with central nervous system infections have been reported in the literature. EV are medically important human pathogens and associated with select neuropsychiatric diseases. Notwithstanding, relatively few reports have mentioned the effects of EV infection on speech and language problems. Our study used a nationwide longitudinal dataset and identified that children with EV infection have a greater risk for speech and language impairments as compared with control group. Infected children combined other comorbidities or risk factors might have greater possibility to develop speech problems. Clinicians should be vigilant for the onset of language developmental abnormalities of preschool children with EV infection.

Failure to meet language milestones at two years of age is predictive of specific language impairment

AIM

This study established predictive properties of single language milestones for specific language impairment (SLI) after the age of four, as these had not previously been reported in the literature.

METHODS

In this nested case-control study, children attending special needs schools for severe speech and language difficulties were matched with children attending mainstream schools. Data covering the ages of zero to four years were retrieved from well-child care clinics and the outcomes of 23 language milestones in the Dutch Developmental Instrument were analysed. The predictive properties were expressed as positive likelihood ratios, sensitivity and specificity.

RESULTS

We included 253 pairs of children with and without SLI, aged from four to 11 years. The mean age was eight years and three months, and 77% were boys. From the age of 18 months, cases and controls differed significantly on all milestones (p < 0.01). After 24 months, the language milestones had positive likelihood ratios that ranging from 6 to 108. In general, language milestones had a high specificity (range 77-100%), but the sensitivity was relatively low (range 0-68%).

CONCLUSION

Failure to meet language milestones from the age of 24 months was predictive of SLI, but the use of separate milestones had limited value due to low sensitivity.

Screening in child health: studies of the efficacy and relevance of preventive care practices

BACKGROUND

Pediatric screening enables the prevention or early detection of diseases and developmental disturbances in infancy and childhood. Screening is a standard component of pediatric practice in many countries, but its scientific basis is not well known.

METHODS

The scientific justification for pediatric screening beyond the neonatal period is presented on the basis of a selective review of the literature on some aspects of pediatric screening.

RESULTS

The level of evidence varies highly among pediatric screening interventions and can be difficult to determine because of confounding variables. Parent counseling is associated with improvements in child-raising competence, accident prevention, and reading behavior. The early detection of abnormalities in a child's motor, linguistic, mental, or social development is possible and often leads to effective early interventions. Cyanotic congenital heart defects can be detected with 63% sensitivity and 99.8% specificity; cerebral palsy can be diagnosed with 33% to 100% sensitivity and 52.3% to 100% specificity (different figures from multiple studies). Physical therapy seems to improve some manifestations of cerebral palsy. Motor development at 90 days is correlated with motor development at 57 months (72% sensitivity, 91% specificity). A developmental quotient above 85 in a two-year-old child is correlated with an intelligence quotient above 85 when the child is 7 years old.

CONCLUSION

There is an increasing amount of scientific evidence in favor of pediatric screening. Nonetheless, further epidemiological studies are needed.