Minimally-verbal children with autism show deficits in theta and gamma oscillations during processing of semantically-related visual information

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.

Extrahippocampal Contributions to Social Memory: The Role of Septal Nuclei

Social memory, the ability to recognize and remember individuals within a social group, is crucial for social interactions and relationships. Deficits in social memory have been linked to several neuropsychiatric and neurodegenerative disorders. The hippocampus, especially the circuit that links dorsal CA2 and ventral CA1 neurons, is considered a neural substrate for social memory formation. Recent studies have provided compelling evidence of extrahippocampal contributions to social memory. The septal nuclei, including the medial and lateral septum, make up a basal forebrain region that shares bidirectional neuronal connections with the hippocampus and has recently been identified as critical for social memory. The focus of our review is the neural circuit mechanisms that underlie social memory, with a special emphasis on the septum. We also discuss the social memory dysfunction associated with neuropsychiatric and neurodegenerative disorders.

Transcranial photobiomodulation in children aged 2-6 years: a randomized sham-controlled clinical trial assessing safety, efficacy, and impact on autism spectrum disorder symptoms and brain electrophysiology

Background

Small pilot studies have suggested that transcranial photobiomodulation (tPBM) could help reduce symptoms of neurological conditions, such as depression, traumatic brain injury, and autism spectrum disorder (ASD).

Objective

To examine the impact of tPBM on the symptoms of ASD in children aged two to six years.

Method

We conducted a randomized, sham-controlled clinical trial involving thirty children aged two to six years with a prior diagnosis of ASD. We delivered pulses of near-infrared light (40 Hz, 850 nm) noninvasively to selected brain areas twice a week for eight weeks, using an investigational medical device designed for this purpose (Cognilum™, JelikaLite Corp., New York, United States). We used the Childhood Autism Rating Scale (CARS, 2nd Edition) to assess and compare the ASD symptoms of participants before and after the treatment course. We collected electroencephalogram (EEG) data during each session from those participants who tolerated wearing the EEG cap.

Results

The difference in the change in CARS scores between the two groups was 7.23 (95% CI 2.357 to 12.107, p = 0.011). Seventeen of the thirty participants completed at least two EEGs and time-dependent trends were detected. In addition, an interaction between Active versus Sham and Scaled Time was observed in delta power (Coefficient = 7.521, 95% CI -0.517 to 15.559, p = 0.07) and theta power (Coefficient = -8.287, 95% CI -17.199 to 0.626, p = 0.07), indicating a potential trend towards a greater reduction in delta power and an increase in theta power over time with treatment in the Active group, compared to the Sham group. Furthermore, there was a significant difference in the condition (Treatment vs. Sham) in the power of theta waves (net_theta) (Coefficient = 9.547, 95% CI 0.027 to 19.067, p = 0.049). No moderate or severe side effects or adverse effects were reported or observed during the trial.

Conclusion

These results indicate that tPBM may be a safe and effective treatment for ASD and should be studied in more depth in larger studies.Clinical trial registration: https://clinicaltrials.gov/ct2/show/NCT04660552, identifier NCT04660552.

Predicting Communication Skills Outcomes for Preschool Children with Autism Spectrum Disorder Following Early Intervention

Purpose

This study aims to assess changes in the receptive and expressive language skills and to determine if the baseline characteristics such as communication, cognitive and motor skills, predict outcomes in preschool children with Autism Spectrum Disorder (ASD) following early intervention.

Methods

We recruited 64 children participating in the Early Start Denver Model (ESDM) early intervention program at an Autism Specific Early Learning and Care Center (ASELCC) in Australia. Baseline characteristics across various developmental domains was measured using the Mullen Scales of Early Learning (MSEL), Vineland Adaptive Behaviour Scales, 2nd Edition (VABS-II), and the ESDM Curriculum Checklist. Linear mixed-effects models were used to examine the effects of the intervention on outcomes. Fixed-effects such as time, groups (verbal and minimally verbal), and time-by-group interactions were assessed whilst adjusting for covariates. Further, multiple linear regression models were used to determine if the baseline characteristics were significant predictors of the outcomes following the early intervention.

Results

Among the 64 children who participated in this study, 38 children were verbal, whereas 26 were deemed to have minimal verbal skills. The mean age of the sample was 4.1 years with a significant male predilection (83%) and from a culturally and linguistically diverse (CALD) background (64%). Findings of the linear mixed effects model showed significant within and between group differences in the ESDM subscales, indicating higher magnitude of changes in the verbal group compared to the minimally verbal group. Finally, the multiple linear regression models suggested that baseline MSEL visual reception and expressive language scores were predictive of changes in the ESDM receptive and expressive communication scores.

Conclusion

Understanding a child's baseline skill levels may provide valuable clues regarding what interventions would work best, or which interventions may be less suitable for individual preschool-aged children with ASD.

State-dependent coupling of hippocampal oscillations

Oscillations occurring simultaneously in a given area represent a physiological unit of brain states. They allow for temporal segmentation of spikes and support distinct behaviors. To establish how multiple oscillatory components co-vary simultaneously and influence neuronal firing during sleep and wakefulness in mice, we describe a multivariate analytical framework for constructing the state space of hippocampal oscillations. Examining the co-occurrence patterns of oscillations on the state space, across species, uncovered the presence of network constraints and distinct set of cross-frequency interactions during wakefulness compared to sleep. We demonstrated how the state space can be used as a canvas to map the neural firing and found that distinct neurons during navigation were tuned to different sets of simultaneously occurring oscillations during sleep. This multivariate analytical framework provides a window to move beyond classical bivariate pipelines for investigating oscillations and neuronal firing, thereby allowing to factor-in the complexity of oscillation-population interactions.

Language in autism: domains, profiles and co-occurring conditions

This article reviews the current knowledge state on pragmatic and structural language abilities in autism and their potential relation to extralinguistic abilities and autistic traits. The focus is on questions regarding autism language profiles with varying degrees of (selective) impairment and with respect to potential comorbidity of autism and language impairment: Is language impairment in autism the co-occurrence of two distinct conditions (comorbidity), a consequence of autism itself (no comorbidity), or one possible combination from a series of neurodevelopmental properties (dimensional approach)? As for language profiles in autism, three main groups are identified, namely, (i) verbal autistic individuals without structural language impairment, (ii) verbal autistic individuals with structural language impairment, and (iii) minimally verbal autistic individuals. However, this tripartite distinction hides enormous linguistic heterogeneity. Regarding the nature of language impairment in autism, there is currently no model of how language difficulties may interact with autism characteristics and with various extralinguistic cognitive abilities. Building such a model requires carefully designed explorations that address specific aspects of language and extralinguistic cognition. This should lead to a fundamental increase in our understanding of language impairment in autism, thereby paving the way for a substantial contribution to the question of how to best characterize neurodevelopmental disorders.

Intact memory storage but impaired retrieval in visual memory in autism: New insights from an electrophysiological study

In a recent study on visual episodic memory (Desaunay, Clochon, et al., 2020), we have shown event-related potentials (ERPs) differences associated with priming (150-300 msec), familiarity (350-470 msec), and recollection (600-700 msec), in young people with autism spectrum disorders (ASD) compared with typical development (TD). To go further into the study of the processes of storage and retrieval of the memory trace, we re-analyzed Desaunay, Clochon, et al's data using time-frequency analysis, that is, event-related synchronization and desynchronization (ERS/ERD). This allows a decomposition of the spectral power within frequency bands associated with these ERPs. We focused both on the same time windows and the same regions of interest as previously published. We mainly identified, in ASD compared with TD, reduced ERS in low-frequencies (delta, theta) in early time-windows, and non-significant differences in ERD in higher frequencies (alpha, beta1) in all time-windows. Reduced ERS during recognition confirmed previously reported diminution of priming effects and difficulties in manipulation and retrieval of both semantic and episodic information. Conversely, preserved ERD corroborates a preservation of memory storage processes. These observations are consistent with a cognitive model of memory in ASD, that suggests difficulties in cognitive operations or executive demand at retrieval, subsequent to successful long-term storage of information. LAY SUMMARY: We assessed the EEG synchronization and desynchronization, during visual episodic recognition. We observed, in youth with Autism, reduced synchronization in low-frequencies (delta, theta), suggesting reduced access to and manipulation of long-term stored information. By contrast, non-significant differences in desynchronization at higher frequencies (alpha, beta frequency bands), that support long-term stored semantic and episodic information, suggested preserved memory traces.

EEG based functional brain networks analysis in dyslexic children during arithmetic task

Developmental Dyslexia is a neuro-developmental disorder that often refers to a phonological processing deficit regardless of average IQ. The present study investigated the distinct functional changes in brain networks of dyslexic children during arithmetic task performance using an electroencephalogram. Fifteen dyslexic children and fifteen normally developing children (NDC) were recruited and performed an arithmetic task. Brain functional network measures such as node strength, clustering coefficient, characteristic pathlength and small-world were calculated using graph theory methods for both groups. Task performance showed significantly less performance accuracy in dyslexics against NDC. The neural findings showed increased connectivity in the delta band and reduced connectivity in theta, alpha, and beta band at temporoparietal, and prefrontal regions in dyslexic group while performing the task. The node strengths were found to be significantly high in delta band (T3, O1, F8 regions) and low in theta (T5, P3, Pz regions), beta (Pz) and gamma band (T4 and prefrontal regions) during the task in dyslexics compared to the NDC. The clustering coefficient was found to be significantly low in the dyslexic group (theta and alpha band) and characteristic pathlength was found to be significantly high in the dyslexic group (theta and alpha band) compared to the NDC group while performing task. In conclusion, the present study shows evidence for poor fact-retrieval mechanism and altered network topology in dyslexic brain networks during arithmetic task performance.

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

In this study we investigated the impact of parental language input on language development and associated neuroscillatory patterns in toddlers at risk of Autism Spectrum Disorder (ASD). Forty-six mother-toddler dyads at either high (n = 22) or low (n = 24) familial risk of ASD completed a longitudinal, prospective study including free-play, resting electroencephalography, and standardized language assessments. Input quantity/quality at 18 months positively predicted expressive language at 24 months, and relationships were stronger for high-risk toddlers. Moderated mediations revealed that input-language relationships were explained by 24-month frontal and temporal gamma power (30-50 Hz) for high-risk toddlers who would later develop ASD. Results suggest that high-risk toddlers may be cognitively and neurally more sensitive to their language environments, which has implications for early intervention.

Searching for a "Brain Signature" of Neurodevelopmental Disorders: Event-Related Potentials and the Quest for Biomarkers of Cognition

SUMMARY

This review summarizes main applications of event-related potentials (ERPs) to the study of cognitive processes in persons with neurodevelopmental disorders, for whom traditional behavioral assessments may not be suitable. A brief introduction to the ERPs is followed by a review of empirical studies using passive ERP paradigms to address three main questions: characterizing individual differences, predicting risk for poor developmental outcomes, and documenting treatment effects in persons with neurodevelopmental disorders. Evidence across studies reveals feasibility of ERP methodology in a wide range of clinical populations and notes consistently stronger brain-behavior associations involving ERP measures of higher-order cognition compared with sensory-perceptual processes. The final section describes the current limitations of ERP methodology that need to be addressed before it could be used as a clinical tool and highlights the needed steps toward translating ERPs from group-level research applications to individually interpretable clinical use.

Sex differences in neuronal systems function and behaviour: beyond a single diagnosis in autism spectrum disorders

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is associated with functional brain alterations that underlie the expression of behaviour. Males are diagnosed up to four times more than females, and sex differences have been identified in memory, cognitive flexibility, verbal fluency, and social communication. Unfortunately, there exists a lack of information on the sex-dependent mechanisms of ASD, as well as biological markers to distinguish sex-specific symptoms in ASD. This can often result in a standardized diagnosis for individuals across the spectrum, despite significant differences in the various ASD subtypes. Alterations in neuronal connectivity and oscillatory activity, such as is observed in ASD, are highly coupled to behavioural states. Yet, despite the well-identified sexual dimorphisms that exist in ASD, these functional patterns have rarely been analyzed in the context of sex differences or symptomology. This review summarizes alterations in neuronal oscillatory function in ASD, discusses the age, region, symptom and sex-specific differences that are currently observed across the spectrum, and potential targets for regulating neuronal oscillatory activity in ASD. The need to identify sex-specific biomarkers, in order to facilitate specific diagnostic criteria and allow for more targeted therapeutic approaches for ASD will also be discussed.

EEG/ERP as a pragmatic method to expand the reach of infant-toddler neuroimaging in HBCD: Promises and challenges

Though electrophysiological measures (EEG and ERP) offer complementary information to MRI and a variety of advantages for studying infants and young children, these measures have not yet been included in large cohort studies of neurodevelopment. This review summarizes the types of EEG and ERP measures that could be used in the HEALthy Brain and Cognitive Development (HBCD) study, and the promises and challenges in doing so. First, we provide brief overview of the use of EEG/ERP for studying the developing brain and discuss exemplar findings, using resting or baseline EEG measures as well as the ERP mismatch negativity (MMN) as exemplars. We then discuss the promises of EEG/ERP such as feasibility, while balancing challenges such as ensuring good signal quality in diverse children with different hair types. We then describe an ongoing multi-site EEG data harmonization from our groups. We discuss the process of alignment and provide preliminary usability data for both resting state EEG data and auditory ERP MMN in diverse samples including over 300 infants and toddlers. Finally, we provide recommendations and considerations for the HBCD study and other studies of neurodevelopment.

Update about "minimally verbal" children with autism spectrum disorder

OBJECTIVE

To review clinical and neurobiological features of minimally verbal children with autism spectrum disorder.

DATA SOURCE

We carried out a narrative review using the PubMed database. We considered the following search terms combined through the Boolean operator "AND": "autism spectrum disorder"; "minimally verbal."

DATA SYNTHESIS

To date, there is no shared definition of minimally verbal children with autism spectrum disorder. The heterogeneity in intellectual functioning and in linguistic abilities among these individuals suggests there is no single mechanism underlying their difficulties in learning to speak. However, the reasons why these children do not speak and the biological markers that can identify them are still unknown. Language impairment in these children can lead to several unfavorable consequences, including behavior problems (such as self-aggression, hetero-aggression, and property destruction), poorer daily living and social skills. Psychiatric comorbidities (including attention deficit/hyperactivity disorder, specific phobias, and compulsions) consist in a serious problem related to the lack of verbal language in individuals with autism spectrum disorder. Although in the literature there are very few evidence-based results, several findings suggest that an alternative and augmentative communication intervention, creating an extra-verbal communication channel, may be effective in these individuals.

CONCLUSIONS

The exact definition, clinical characteristics, associated disorders, etiology, and treatment of minimally verbal subjects with autism spectrum disorder must still be further studied and understood.

Psychophysiological and Eye-Tracking Markers of Speech and Language Processing in Neurodevelopmental Disorders: New Options for Difficult-to-Test Populations

It can be challenging to accurately assess speech and language processing in preverbal or minimally verbal individuals with neurodevelopmental disabilities (NDD) using standardized behavioral tools. Event-related potential and eye tracking methods offer novel means to objectively document receptive language processing without requiring purposeful behavioral responses. Working around many of the cognitive, motor, or social difficulties in NDDs, these tools allow for minimally invasive, passive assessment of language processing and generate continuous scores that may have utility as biomarkers of individual differences and indicators of treatment effectiveness. Researchers should consider including physiological measures in assessment batteries to allow for more precise capture of language processing in individuals for whom it may not behaviorally apparent.

Use of longitudinal EEG measures in estimating language development in infants with and without familial risk for autism spectrum disorder

Language development in children with autism spectrum disorder (ASD) varies greatly among affected individuals and is a strong predictor of later outcomes. Younger siblings of children with ASD have increased risk of ASD, but also language delay. Identifying neural markers of language outcomes in infant siblings could facilitate earlier intervention and improved outcomes. This study aimed to determine whether EEG measures from the first 2-years of life can explain heterogeneity in language development in children at low- and high-risk for ASD, and to determine whether associations between EEG measures and language development are different depending on ASD risk status or later ASD diagnosis. In this prospective longitudinal study EEG measures collected between 3-24 months were used in a multivariate linear regression model to estimate participants' 24-month language development. Individual baseline longitudinal EEG measures included (1) the slope of EEG power across 3-12 months or 3-24 months of life for 6 canonical frequency bands, (2) estimated EEG power at age 6-months for the same frequency bands, and (3) terms representing the interaction between ASD risk status and EEG power measures. Modeled 24-month language scores using EEG data from either the first 2-years (Pearson R = 0.70, 95% CI 0.595-0.783, P=1x10^-18) or the first year of life (Pearson R=0.66, 95% CI 0.540-0.761, P=2.5x10^-14) were highly correlated with observed scores. All models included significant interaction effects of risk on EEG measures, suggesting that EEG-language associations are different depending on risk status, and that different brain mechanisms effect language development in low-versus high-risk infants.