Parental Language Input Predicts Neuroscillatory Patterns Associated with Language Development in Toddlers at Risk of Autism

Evaluating a novel high-density EEG sensor net structure for improving inclusivity in infants with curly or tightly coiled hair

Electroencephalography (EEG) is an important tool in the field of developmental cognitive neuroscience for indexing neural activity. However, racial biases persist in EEG research that limit the utility of this tool. One bias comes from the structure of EEG nets/caps that do not facilitate equitable data collection across hair textures and types. Recent efforts have improved EEG net/cap design, but these solutions can be time-intensive, reduce sensor density, and are more difficult to implement in younger populations. The present study focused on testing EEG sensor net designs over infancy. Specifically, we compared EEG data quality and retention between two high-density saline-based EEG sensor net designs from the same company (Magstim EGI, Whitland, UK) within the same infants during a baseline EEG paradigm. We found that within infants, the tall sensor nets resulted in lower impedances during collection, including lower impedances in the key online reference electrode for those with greater hair heights and resulted in a greater number of usable EEG channels and data segments retained during pre-processing. These results suggest that along with other best practices, the modified tall sensor net design is useful for improving data quality and retention in infant participants with curly or tightly-coiled hair.

The relationship between gamma-band neural oscillations and language skills in youth with Autism Spectrum Disorder and their first-degree relatives

BACKGROUND

Most children with Autism Spectrum Disorder (ASD) have co-occurring language impairments and some of these autism-specific language difficulties are also present in their non-autistic first-degree relatives. One of the possible neural mechanisms associated with variability in language functioning is alterations in cortical gamma-band oscillations, hypothesized to be related to neural excitation and inhibition balance.

METHODS

We used a high-density 128-channel electroencephalography (EEG) to register brain response to speech stimuli in a large sex-balanced sample of participants: 125 youth with ASD, 121 typically developing (TD) youth, and 40 unaffected siblings (US) of youth with ASD. Language skills were assessed with Clinical Evaluation of Language Fundamentals.

RESULTS

First, during speech processing, we identified significantly elevated gamma power in ASD participants compared to TD controls. Second, across all youth, higher gamma power was associated with lower language skills. Finally, the US group demonstrated an intermediate profile in both language and gamma power, with nonverbal IQ mediating the relationship between gamma power and language skills.

LIMITATIONS

We only focused on one of the possible neural contributors to variability in language functioning. Also, the US group consisted of a smaller number of participants in comparison to the ASD or TD groups. Finally, due to the timing issue in EEG system we have provided only non-phase-locked analysis.

CONCLUSIONS

Autistic youth showed elevated gamma power, suggesting higher excitation in the brain in response to speech stimuli and elevated gamma power was related to lower language skills. The US group showed an intermediate pattern of gamma activity, suggesting that the broader autism phenotype extends to neural profiles.

Patterns of spontaneous neural activity associated with social communication abilities among infants and toddlers showing signs of autism

Early disruptions to social communication development, including delays in joint attention and language, are among the earliest markers of autism spectrum disorder (autism, henceforth). Although social communication differences are a core feature of autism, there is marked heterogeneity in social communication-related development among infants and toddlers exhibiting autism symptoms. Neural markers of individual differences in joint attention and language abilities may provide important insight into heterogeneity in autism symptom expression during infancy and toddlerhood. This study examined patterns of spontaneous electroencephalography (EEG) activity associated with joint attention and language skills in 70 community-referred 12- to 23-month-olds with autism symptoms and elevated scores on an autism diagnostic instrument. Data-driven cluster-based permutation analyses revealed significant positive associations between relative alpha power (6-9 Hz) and concurrent response to joint attention skills, receptive language, and expressive language abilities. Exploratory analyses also revealed significant negative associations between relative alpha power and measures of core autism features (i.e., social communication difficulties and restricted/repetitive behaviors). These findings shed light on the neural mechanisms underlying typical and atypical social communication development in emerging autism and provide a foundation for future work examining neural predictors of social communication growth and markers of intervention response.

Resting Frontal Gamma Power is Associated with Both Expressive Language and Non-verbal Cognitive Abilities in Young Autistic Children

Previous research links resting frontal gamma power to key developmental outcomes in young neurotypical (NT) children and infants at risk for language impairment. However, it remains unclear whether gamma power is specifically associated with language or with more general cognitive abilities among young children diagnosed with autism spectrum disorder (ASD). The current study evaluates differences in resting frontal gamma power between young autistic and NT children and tests whether gamma power is uniquely associated with individual differences in expressive language, receptive language and non-verbal cognitive abilities in autistic and NT children. Participants included 48 autistic children and 58 age- and sex-matched NT children (ages 22-60 months). Baseline electroencephalography (EEG) recordings were acquired from each participant. Children also completed the Mullen Scales of Early Learning (MSEL). We found that frontal gamma power at rest did not differ between autistic and NT children. Among autistic children, reduced frontal gamma power was significantly associated with both higher expressive language skills and higher non-verbal cognitive skills, controlling for age and sex. The interaction between frontal gamma power and diagnostic status no longer explained unique variance in expressive language skills after controlling for variance associated with non-verbal cognitive skills across autistic and NT children. Together, these findings suggest that reduced gamma power is associated with both better expressive language and non-verbal cognitive skills among young autistic children. Moreover, associations between high frequency neural activity and cognition are not specific to verbal abilities but reflect neural mechanisms associated with general higher-order cognitive abilities in ASD.

Caregiver linguistic alignment to autistic and typically developing children: A natural language processing approach illuminates the interactive components of language development

BACKGROUND

Language development is a highly interactive activity. However, most research on linguistic environment has focused on the quantity and complexity of linguistic input to children, with current models showing that complexity facilitates language in both typically developing (TD) and autistic children.

AIMS

After reviewing existing work on caregiver engagement of children's utterances, we aim to operationalize such engagement with automated measures of linguistic alignment, thereby providing scalable tools to assess caregivers' active reuse of their children's language. By assessing the presence of alignment, its sensitivity to the child's individual differences and how well it predicts language development beyond current models across the two groups, we showcase the usefulness of the approach and provide initial empirical foundations for further conceptual and empirical investigations.

METHODS

We measure lexical, syntactic and semantic types of caregiver alignment in a longitudinal corpus involving 32 adult-autistic child and 35 adult-TD child dyads, with children between 2 and 5 years of age. We assess the extent to which caregivers repeat their children's words, syntax, and semantics, and whether these repetitions predict language development beyond more standard predictors.

RESULTS

Caregivers tend to re-use their child's language in a way that is related to the child's individual, primarily linguistic, differences. Caregivers' alignment provides unique information improving our ability to predict future language development in both typical and autistic children.

CONCLUSIONS

We provide evidence that language development also relies on interactive conversational processes, previously understudied. We share carefully detailed methods, and open-source scripts so as to systematically extend our approach to new contexts and languages.

Associations Between Caregiver Stress and Language Outcomes in Infants With Autistic and Non-Autistic Siblings: An Exploratory Study

PURPOSE

Caregivers of autistic children present with high stress levels, which have been associated with poorer child outcomes in several domains, including language development. However, prior to this study, it was unknown whether elevated caregiver stress was associated with language development in infant siblings of autistic children (Sibs-autism), who are at increased likelihood of receiving a future diagnosis of autism and/or language impairment compared to infant siblings of non-autistic children. This study explored the degree to which, as well as the mechanisms by which, caregiver stress was linked with later language outcomes of Sibs-autism and infant siblings of non-autistic children (Sibs-NA).

METHOD

Participants were 50 infants (28 Sibs-autism; 22 Sibs-NA) aged 12-18 months at the first time point in this study (Time 1). Infants were seen again 9 months later, at 21-27 months of age (Time 2). Caregiver stress was measured via a validated self-report measure at Time 1. Caregiver language input, the putative mechanism by which caregiver stress may influence later language outcomes, was collected via two daylong recordings from digital recording (Language ENvironment Analysis) devices worn by the child at this same time point. Child language outcomes were measured via standardized and caregiver report measures at Time 2.

RESULTS

Several models testing hypothesized indirect effects of caregiver stress on later child language outcomes through caregiver language input were statistically significant. Specifically, significant indirect effects suggest that (a) caregivers with increased stress tend to speak less to their infants, and (b) this reduced language input tends to covary with reduced child language outcomes later in life for Sibs-autism and Sibs-NA.

CONCLUSIONS

This study provides new insights into links between caregiver stress, caregiver language input, and language outcomes in Sibs-autism and Sibs-NA. Further work is necessary to understand how to best support caregivers and optimize the language learning environments for infants.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.21714368.

Intellectually able adults with autism spectrum disorder show typical resting-state EEG activity

There is broad interest in discovering quantifiable physiological biomarkers for psychiatric disorders to aid diagnostic assessment. However, finding biomarkers for autism spectrum disorder (ASD) has proven particularly difficult, partly due to high heterogeneity. Here, we recorded five minutes eyes-closed rest electroencephalography (EEG) from 186 adults (51% with ASD and 49% without ASD) and investigated the potential of EEG biomarkers to classify ASD using three conventional machine learning models with two-layer cross-validation. Comprehensive characterization of spectral, temporal and spatial dimensions of source-modelled EEG resulted in 3443 biomarkers per recording. We found no significant group-mean or group-variance differences for any of the EEG features. Interestingly, we obtained validation accuracies above 80%; however, the best machine learning model merely distinguished ASD from the non-autistic comparison group with a mean balanced test accuracy of 56% on the entirely unseen test set. The large drop in model performance between validation and testing, stress the importance of rigorous model evaluation, and further highlights the high heterogeneity in ASD. Overall, the lack of significant differences and weak classification indicates that, at the group level, intellectually able adults with ASD show remarkably typical resting-state EEG.

Keep the Ball Rolling: Sustained Multiturn Conversational Episodes Are Associated With Child Language Ability

PURPOSE

The purpose of this study was to examine the relationship between interaction quality and child language ability. We focused on one promising interaction quality indicator-the rate of multiturn conversational episodes. We also explored whether the relationship between rate of single conversational turns and language ability changed when the child's nonverbal behaviors were considered in addition to verbal conversational turns. To limit the potential of socioeconomic status as a confounder, participants included only families living in underresourced households.

METHOD

Secondary analyses were conducted using baseline data (N = 41 dyads enrolled, N = 27 analyzed) from a longitudinal study. All families were living in low-income households (i.e., below 200% of the Federal Poverty Level) and 12 were English-Spanish bilingual (15 English-only). Mothers and their children (13 to 27 months) participated in video-recorded play and reading interactions at home. Trained observers transcribed and coded the child's and caregiver's verbal and nonverbal behaviors. Linear regression models examined the relationship between the number of conversational turns and child language ability.

RESULTS

Child language ability was significantly and positively associated with the number of verbal-nonverbal single turns and multiturn conversational episodes, but not single verbal-only turns.

CONCLUSIONS

For children still acquiring language, it is important to account for nonverbal contributions to conversation. Child language ability was significantly and positively associated only with the conversational turn variables that included the child's nonverbal behaviors. Further investigation is needed to understand whether number of turns within conversational episodes is a better indicator of interaction quality than sheer number of conversational turns. Implications for caregiver-implemented interventions are discussed.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.20452575.

Neural Tracking in Infancy Predicts Language Development in Children With and Without Family History of Autism

During speech processing, neural activity in non-autistic adults and infants tracks the speech envelope. Recent research in adults indicates that this neural tracking relates to linguistic knowledge and may be reduced in autism. Such reduced tracking, if present already in infancy, could impede language development. In the current study, we focused on children with a family history of autism, who often show a delay in first language acquisition. We investigated whether differences in tracking of sung nursery rhymes during infancy relate to language development and autism symptoms in childhood. We assessed speech-brain coherence at either 10 or 14 months of age in a total of 22 infants with high likelihood of autism due to family history and 19 infants without family history of autism. We analyzed the relationship between speech-brain coherence in these infants and their vocabulary at 24 months as well as autism symptoms at 36 months. Our results showed significant speech-brain coherence in the 10- and 14-month-old infants. We found no evidence for a relationship between speech-brain coherence and later autism symptoms. Importantly, speech-brain coherence in the stressed syllable rate (1-3 Hz) predicted later vocabulary. Follow-up analyses showed evidence for a relationship between tracking and vocabulary only in 10-month-olds but not in 14-month-olds and indicated possible differences between the likelihood groups. Thus, early tracking of sung nursery rhymes is related to language development in childhood.

Socioeconomic status and reading outcomes: Neurobiological and behavioral correlates

In this chapter, we examine reading outcomes and socioeconomic status (SES) using a developmental cognitive and educational neuroscience perspective. Our focus is on reading achievement and intervention outcomes for students from lower SES backgrounds who struggle with reading. Socioeconomic disadvantage is a specific type of vulnerability students experience, which is often narrowly defined based on parental income, education level, and/or occupational prestige. However, implications of socioeconomic status extend broadly to a suite of areas relevant for reading outcomes including a student's access to resources, experiences, language exposure, academic outcomes, and psychological correlates. Underlying this constellation of factors are brain systems supporting the processing of oral and written language as well as stress-related factors. We review the implications of SES and reading achievement, and their intersectionality, for the science and practice of reading instruction.

Language and Speech Characteristics in Autism

The aim of this paper is to provide information regarding diversity in speech and language profiles of individuals with Autism Spectrum Disorders (ASD) and try to classify these profiles according to the combination of the communication difficulties. Research findings confirm the existence of heterogeneity of communication challenges in ASD across the lifespan. A lot of children with ASD experience communication challenges and strengths across all language sub-systems including pragmatics, grammar, semantics, syntax, phonology, and morphology in both oral and written language, while some children with autism demonstrate exceptional language abilities incl. linguistic creativity. Communication issues vary on a continuum of severity so that some children may be verbal, whereas others remain non-verbal or minimally-verbal. The diversity of profiles in speech and language development stem from either the presence of comorbid factors, as a core symptom of autistic behavior without comorbidity or both, with the development of complex clinical symptoms. Difficulties with the semantic aspect of language affect the individual's skills in abstract thinking, multiple meanings of words, concept categorization, and so on. Finally, the coexistence of ASD with other communication difficulties such as a Language Disorder, Apraxia of Speech, Speech Sound Disorders or/and other neurodevelopmental disorders raises the need for examining more carefully the emergence of new clinical profiles and clinical markers useful in performing differential diagnosis and different intervention.