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Background Complex neurodevelopmental disorders may be characterized by subtle brain function signatures early in life before behavioral symptoms are apparent. Such endophenotypes may be measurable biomarkers for later cognitive impairments. The nonlinear complexity of electroencephalography (EEG) signals is believed to contain information about the architecture of the neural networks in the brain on many scales. Early detection of abnormalities in EEG signals may be an early biomarker for developmental cognitive disorders. The goal of this paper is to demonstrate that the modified multiscale entropy (mMSE) computed on the basis of resting state EEG data can be used as a biomarker of normal brain development and distinguish typically developing children from a group of infants at high risk for autism spectrum disorder (ASD), defined on the basis of an older sibling with ASD. Methods Using mMSE as a feature vector, a multiclass support vector machine algorithm was used to classify typically developing and high-risk groups. Classification was computed separately within each age group from 6 to 24 months. Results Multiscale entropy appears to go through a different developmental trajectory in infants at high risk for autism (HRA) than it does in typically developing controls. Differences appear to be greatest at ages 9 to 12 months. Using several machine learning algorithms with mMSE as a feature vector, infants were classified with over 80% accuracy into control and HRA groups at age 9 months. Classification accuracy for boys was close to 100% at age 9 months and remains high (70% to 90%) at ages 12 and 18 months. For girls, classification accuracy was highest at age 6 months, but declines thereafter. Conclusions This proof-of-principle study suggests that mMSE computed from resting state EEG signals may be a useful biomarker for early detection of risk for ASD and abnormalities in cognitive development in infants. To our knowledge, this is the first demonstration of an information theoretic analysis of EEG data for biomarkers in infants at risk for a complex neurodevelopmental disorder.

The role of language in autism spectrum disorder (ASD), more specifically, its function in social communication and strong predictive power on future outcomes, warrants language assessments that have good psychometric properties that capture the heterogeneity of language ability found among diagnosed individuals. Given the rapid growth in intervention and treatment research, there is an urgent need for the development and implementation of outcome measures that are easily obtained and sensitive to change. In this commentary, we argue for the use of natural language samples as measures of expressive language and communication for this purpose and review the literature on their implementation in ASD research. Conceptual and measurement issues are discussed and future developments are outlined.

Long-range cortical functional connectivity is often reduced in autism spectrum disorders (ASD), but the nature of local cortical functional connectivity in ASD has remained elusive. We used magnetoencephalography to measure task-related local functional connectivity, as manifested by coupling between the phase of alpha oscillations and the amplitude of gamma oscillations, in the fusiform face area (FFA) of individuals diagnosed with ASD and typically developing individuals while they viewed neutral faces, emotional faces, and houses. We also measured task-related long-range functional connectivity between the FFA and the rest of the cortex during the same paradigm. In agreement with earlier studies, long-range functional connectivity between the FFA and three distant cortical regions was reduced in the ASD group. However, contrary to the prevailing hypothesis in the field, we found that local functional connectivity within the FFA was also reduced in individuals with ASD when viewing faces. Furthermore, the strength of long-range functional connectivity was directly correlated to the strength of local functional connectivity in both groups; thus, long-range and local connectivity were reduced proportionally in the ASD group. Finally, the magnitude of local functional connectivity correlated with ASD severity, and statistical classification using local and long-range functional connectivity data identified ASD diagnosis with 90% accuracy. These results suggest that failure to entrain neuronal assemblies fully both within and across cortical regions may be characteristic of ASD.

Atypical response to tactile input is associated with greater socio-communicative impairments in individuals with autism spectrum disorder (ASD). The current study examined overt orienting to caregiver-initiated touch in 12-month-olds at high risk for ASD (HRA) with (HRA+) and without (HRA−) a later diagnosis of ASD compared to low-risk comparison infants. Findings indicate that infants that go on to receive a diagnosis of ASD may more frequently fail to shift their attention in response to caregiver touch and when they do, they may be more likely to orient away from touch. Additionally, failure to respond to touch predicts ADOS severity scores at outcome suggesting that atypical response to touch may be an early indicator of autism severity.

Autism spectrum disorder (ASD) is a complex and heterogeneous disorder, diagnosed on the basis of behavioral symptoms during the second year of life or later. Finding scalable biomarkers for early detection is challenging because of the variability in presentation of the disorder and the need for simple measurements that could be implemented routinely during well-baby checkups. EEG is a relatively easy-to-use, low cost brain measurement tool that is being increasingly explored as a potential clinical tool for monitoring atypical brain development. EEG measurements were collected from 99 infants with an older sibling diagnosed with ASD, and 89 low risk controls, beginning at 3 months of age and continuing until 36 months of age. Nonlinear features were computed from EEG signals and used as input to statistical learning methods. Prediction of the clinical diagnostic outcome of ASD or not ASD was highly accurate when using EEG measurements from as early as 3 months of age. Specificity, sensitivity and PPV were high, exceeding 95% at some ages. Prediction of ADOS calibrated severity scores for all infants in the study using only EEG data taken as early as 3 months of age was strongly correlated with the actual measured scores. This suggests that useful digital biomarkers might be extracted from EEG measurements.

Multimodal communication may facilitate attention in infants. This study examined the presentation of caregiver touch-only and touch + speech input to 12-month-olds at high (HRA) and low risk for ASD. Findings indicated that, although both groups received a greater number of touch + speech bouts compared to touch-only bouts, the duration of overall touch that overlapped with speech was significantly greater in the HRA group. Additionally, HRA infants were less responsive to touch-only bouts compared to touch + speech bouts suggesting that their mothers may use more touch + speech communication to elicit infant responses. Nonetheless, the exact role of touch in multimodal communication directed towards infants at high risk for ASD warrants further exploration.

Background and aims Nongenerative speech is the rote repetition of words or phrases heard from others or oneself. The most common manifestations of nongenerative speech are immediate and delayed echolalia, which are a well-attested clinical feature and a salient aspect of atypical language use in autism. However, there are no current estimates of the frequency of nongenerative speech, and the individual characteristics associated with nongenerative speech use in individuals across the autistic spectrum are poorly understood. In this study, we aim to measure and characterize spontaneous and nongenerative speech use in minimally verbal and verbally fluent autistic children and adolescents. Methods Participants were 50 minimally verbal and 50 verbally fluent autistic individuals aged 6 to 21 years. Spontaneous and nongenerative speech samples were derived from SALT transcripts of ADOS-2 assessments. Participants’ intelligible speech utterances were categorized as spontaneous or nongenerative. Spontaneous versus nongenerative utterances were compared between language subgroups on frequency of use and linguistic structure. Associations between nongenerative speech use and a series of individual characteristics (ADOS-2 subscale scores, nonverbal IQ, receptive vocabulary, and chronological age) were investigated over the whole sample and for each language subgroup independently. Results Almost all participants produced some nongenerative speech. Minimally verbal individuals produced significantly more nongenerative than spontaneous utterances, and more nongenerative utterances compared to verbally fluent individuals. Verbally fluent individuals produced limited rates of nongenerative utterances, in comparison to their much higher rates of spontaneous utterances. Across the sample, nongenerative utterance rates were associated with nonverbal IQ and receptive vocabulary, but not separately for the two language subgroups. In verbally fluent individuals, only age was significantly inversely associated with nongenerative speech use such that older individuals produced fewer nongenerative utterances. In minimally verbal individuals, there were no associations between any of the individual characteristics and nongenerative speech use. In terms of linguistic structure, the lexical diversity of nongenerative and spontaneous utterances of both language subgroups was comparable. Morphosyntactic complexity was higher for spontaneous compared to nongenerative utterances in verbally fluent individuals, while no differences emerged between the two utterance types in minimally verbal individuals. Conclusions Nongenerative speech presents differently in minimally verbal and verbally fluent autistic individuals. Although present in verbally fluent individuals, nongenerative speech appears to be a major feature of spoken language in minimally verbal children and adolescents. Implications Our results advocate for more research on the expressive language profiles of autistic children and adolescents who remain minimally verbal and for further investigations of nongenerative speech, which is usually excluded from language samples. Given its prevalence in the spoken language of minimally verbal individuals, nongenerative speech could be used as a way to engage in and maintain communication with this subgroup of autistic individuals.

Background and aims Developmental motor speech impairment has been suspected, but rarely systematically examined, in low- and minimally verbal individuals with autism spectrum disorder. We aimed to investigate the extent of motor speech impairment in this population and its relation to number of different words produced during a semi-structured language sample. Methods Videos of 54 low-verbal and minimally verbal individuals (ages 4;4–18;10) performing portions of a speech praxis test were coded for signs of motor speech impairment (e.g., childhood apraxia of speech). Age, autism spectrum disorder severity, nonspeech oral-motor ability, speech production ability, nonverbal IQ, and receptive vocabulary were compared between groups. Results Four groups emerged: (1) speech within normal limits (n = 12), (2) non-childhood apraxia of speech impairment (n = 16), (3) suspected childhood apraxia of speech (n = 13), and (4) insufficient speech to rate (n = 13). Groups differed significantly in nonspeech oral-motor ability, speech production ability, nonverbal IQ, and receptive vocabulary. Overall, only speech production ability and receptive vocabulary accounted for significant variance in number of different words. Receptive vocabulary significantly predicted number of different words only in Groups 1 and 2, while speech production ability significantly predicted number of different words only in Groups 3 and 4. Conclusions and implications If replicated, our findings have important implications for developing much-needed spoken language interventions in minimally verbal individuals with autism spectrum disorder.

Two decades ago, the theory-of-mind hypothesis of autism was introduced by Baron-Cohen and his colleagues; this theory provided a unified cognitive explanation for the key social and communication symptoms in that disorder. I evaluate the theory-of-mind hypothesis in light of studies that have addressed several key questions: Do children with autism develop theory-of-mind concepts? How can we explain why some children with autism pass theory-of-mind tasks? Do deficits in theory of mind account for the major impairments that characterize autistic disorder? Current research supports the view that autism involves delays and deficits not only in the development of a theory of mind but also in additional aspects of social-affective information processing that extend beyond the traditional boundaries of theory of mind.

Background and aims Prior work has examined how children and adolescents with autism spectrum disorder who are minimally verbal use their spoken language abilities during interactions with others. However, social communication includes other aspects beyond speech. To our knowledge, no studies have examined how minimally verbal children and adolescents with autism spectrum disorder are using their gestural communication during social interactions. Such work can provide important insights into how gestures may complement their spoken language abilities. Methods Fifty minimally verbal children and adolescents with autism spectrum disorder participated (Mage = 12.41 years; 38 males). Gestural communication was coded from the Autism Diagnostic Observation Schedule. Children (n = 25) and adolescents (n = 25) were compared on their production of gestures, gesture–speech combinations, and communicative functions. Communicative functions were also assessed by the type of communication modality: gesture, speech, and gesture–speech to examine the range of communicative functions across different modalities of communication. To explore the role gestures may play the relation between speech utterances and gestural production was investigated. Results Analyses revealed that (1) minimally verbal children and adolescents with autism spectrum disorder did not differ in their total number of gestures. The most frequently produced gesture across children and adolescents was a reach gesture, followed by a point gesture (deictic gesture), and then conventional gestures. However, adolescents produced more gesture–speech combinations (reinforcing gesture-speech combinations) and displayed a wider range of communicative functions. (2) Overlap was found in the types of communicative functions expressed across different communication modalities. However, requests were conveyed via gesture more frequently compared to speech or gesture–speech. In contrast, dis/agree/acknowledging and responding to a question posed by the conversational partner was expressed more frequently via speech compared to gesture or gesture–speech. (3) The total number of gestures was negatively associated with total speech utterances after controlling for chronological age, receptive communication ability, and nonverbal IQ. Conclusions Adolescents may be employing different communication strategies to maintain the conversational exchange and to further clarify the message they want to convey to the conversational partner. Although overlap occurred in communicative functions across gesture, speech, and gesture–speech, nuanced differences emerged in how often they were expressed across different modalities of communication. Given their speech production abilities, gestures may play a compensatory role for some individuals with autism spectrum disorder who are minimally verbal. Implications Findings underscore the importance of assessing multiple modalities of communication to provide a fuller picture of their social communication abilities. Our results identified specific communicative strengths and areas for growth that can be targeted and expanded upon within gesture and speech to optimize social communication development.