Background: Magnetoencephalography (MEG) is used to measure the auditory evoked magnetic field (AEF), which reflects language-related performance. In young children, however, the simultaneous quantification of the bilateral auditory-evoked response during binaural hearing is difficult using conventional adult-sized MEG systems. Recently, a child-customised MEG device has facilitated the acquisition of bi-hemispheric recordings, even in young children. Using the child-customised MEG device, we previously reported that language-related performance was reflected in the strength of the early component (P50m) of the auditory evoked magnetic field (AEF) in typically developing (TD) young children (2 to 5 years old) [Eur J Neurosci2012,35:644–650]. The aim of this study was to investigate how this neurophysiological index in each hemisphere is correlated with language performance in autism spectrum disorder (ASD) and TD children.Methods: We used magnetoencephalography (MEG) to measure the auditory evoked magnetic field (AEF), which reflects language-related performance. We investigated the P50m that is evoked by voice stimuli (/ne/) bilaterally in 33 young children (3 to 7 years old) with ASD and in 30 young children who were typically developing (TD). The children were matched according to their age (in months) and gender. Most of the children with ASD were high-functioning subjects.Results: The results showed that the children with ASD exhibited significantly less leftward lateralisation in their P50m intensity compared with the TD children. Furthermore, the results of a multiple regression analysis indicated that a shorter P50m latency in both hemispheres was specifically correlated with higher language-related performance in the TD children, whereas this latency was not correlated with non-verbal cognitive performance or chronological age. The children with ASD did not show any correlation between P50m latency and language-related performance; instead, increasing chronological age was a significant predictor of shorter P50m latency in the right hemisphere.Conclusions: Using a child-customised MEG device, we studied the P50m component that was evoked through binaural human voice stimuli in young ASD and TD children to examine differences in auditory cortex function that are associated with language development. Our results suggest that there is atypical brain function in the auditory cortex in young children with ASD, regardless of language development.

Autism is hypothesized to result in a cortical excitatory and inhibitory imbalance driven by inhibitory interneuron dysfunction, which is associated with the generation of gamma oscillations. On the other hand, impaired motor control has been widely reported in autism. However, no study has focused on the gamma oscillations during motor control in autism. In the present study, we investigated the motor-related gamma oscillations in autism using magnetoencephalography. Magnetoencephalographic signals were recorded from 14 right-handed human children with autism (5 female), aged 5–7 years, and age- and IQ-matched 15 typically developing children during a motor task using their right index finger. Consistent with previous studies, the autism group showed a significantly longer button response time and reduced amplitude of motor-evoked magnetic fields. We observed that the autism group exhibited a low peak frequency of motor-related gamma oscillations from the contralateral primary motor cortex, and these were associated with the severity of autism symptoms. The autism group showed a reduced power of motor-related gamma oscillations in the bilateral primary motor cortex. A linear discriminant analysis using the button response time and gamma oscillations showed a high classification performance (86.2% accuracy). The alterations of the gamma oscillations in autism might reflect the cortical excitatory and inhibitory imbalance. Our findings provide an important clue into the behavioral and neurophysiological alterations in autism and a potential biomarker for autism. SIGNIFICANCE STATEMENT Currently, the diagnosis of autism has been based on behavioral assessments, and a crucial issue in the diagnosis of autism is to identify objective and quantifiable clinical biomarkers. A key hypothesis of the neurophysiology of autism is an excitatory and inhibitory imbalance in the brain, which is associated with the generation of gamma oscillations. On the other hand, motor deficits have also been widely reported in autism. This is the first study to demonstrate low motor performance and altered motor-related gamma oscillations in autism, reflecting a brain excitatory and inhibitory imbalance. Using these behavioral and neurophysiological parameters, we classified autism and control group with good accuracy. This work provides important information on behavioral and neurophysiological alterations in patients with autism.

Background: Elucidating developmental changes in the symptoms of autism spectrum disorder (ASD) is important to support individuals with ASD. However, no report has clarified the developmental changes in attention to social information for a broad age range. The aim of this study was to investigate the developmental changes in attention to social information from early childhood to adolescence in individuals with ASD and typically developed (TD) children. Methods: We recruited children with ASD (n = 83) and TD participants (n = 307) between 2 and 18 years of age. Using the all-in-one-eye-tracking system, Gazefinder, we measured the percentage fixation time allocated to areas of interest (AoIs) depicted in movies (the eyes and mouth in movies of a human face with/without mouth motion, upright and inverted biological motion in movies showing these stimuli simultaneously, people and geometry in preference paradigm movies showing these stimuli simultaneously, and objects with/without finger-pointing in a movie showing a woman pointing toward an object). We conducted a three-way analysis of variance, 2 (diagnosis: ASD and TD) by 2 (sex: male and female) by 3 (age group: 0–5, 6–11, and 12–18 years) and locally weighted the scatterplot smoothing (LOESS) regression curve on each AoI. Results: In the face stimuli, the percentage fixation time to the eye region for the TD group increased with age, whereas the one for the ASD group did not. In the ASD group, the LOESS curves of the gaze ratios at the eye region increased up to approximately 10 years of age and thereafter tended to decrease. For the percentage fixation time to the people region in the preference paradigm, the ASD group gazed more briefly at people than did the TD group. Limitations: It is possible that due to the cross-sectional design, the degree of severity and of social interest might have differed according to the subjects’ age. Conclusions: There may be qualitative differences in abnormal eye contact in ASD between individuals in early childhood and those older than 10 years.

Verbal interaction and imitation are essential for language learning and development in young children. However, it is unclear how mother–child dyads synchronize oscillatory neural activity at the cortical level in turn-based speech interactions. Our study investigated interbrain synchrony in mother–child pairs during a turn-taking paradigm of verbal imitation. A dual-MEG (magnetoencephalography) setup was used to measure brain activity from interactive mother–child pairs simultaneously. Interpersonal neural synchronization was compared between socially interactive and noninteractive tasks (passive listening to pure tones). Interbrain networks showed increased synchronization during the socially interactive compared to noninteractive conditions in the theta and alpha bands. Enhanced interpersonal brain synchrony was observed in the right angular gyrus, right triangular, and left opercular parts of the inferior frontal gyrus. Moreover, these parietal and frontal regions appear to be the cortical hubs exhibiting a high number of interbrain connections. These cortical areas could serve as a neural marker for the interactive component in verbal social communication. The present study is the first to investigate mother–child interbrain neural synchronization during verbal social interactions using a dual-MEG setup. Our results advance our understanding of turn-taking during verbal interaction between mother–child dyads and suggest a role for social “gating” in language learning.

Children make rapid transitions in their neural and intellectual development. Compared to other brain regions, the auditory cortex slowly matures, and children show immature auditory brain activity. This auditory neural plasticity largely occurs as a response to human‐voice stimuli, which are presented more often than other stimuli, and can even be observed in the brainstem. Early psychologists have proposed that sensory processing and intelligence are closely related to each other. In the present study, we identified brain activity related to human‐voice processing and investigated a crucial neural correlate of child development and intelligence. We also examined the neurophysiological activity patterns during human‐voice processing in young children aged 3 to 8 years. We investigated auditory evoked fields (AEFs) and oscillatory changes using child‐customized magnetoencephalography within a short recording time (<6 min). We examined the P1m component of AEFs, which is a predominant component observed in young children. The amplitude of the left P1m was highly correlated with age, and the amplitude of the right P1m was highly correlated with the intelligence quotient. For auditory‐related oscillatory changes, we found a positive correlation between the intelligence quotient and percent change of gamma increase relative to baseline in the right auditory cortex. We replicated the finding of age‐related changes in auditory brain activity in young children, which is related to the slow maturation of the auditory cortex. In addition, these results suggest a close link between intelligence and auditory sensory processing, especially in the right hemisphere.

Parent-child book reading is important for fostering the development of various lifelong cognitive and social abilities in young children. Despite numerous reports describing the effects of familiarity on shared reading for children, the exact neural basis of the functional network architecture remains unclear. We conducted Magnet-Encephalographic (MEG) experiments using graph theory to elucidate the role of familiarity in shared reading in a child's brain network and to measure the connectivity dynamics of a child while Listening to Storybook Reading (LSBR), which represents the daily activity of shared book reading between the child and caregiver. The LSBR task was performed with normally developing preschool- and school-age children (N = 15) under two conditions: reading by their own mother (familiar condition) vs. an experimenter (unfamiliar condition). We used the phase lag index (PLI), which captures synchronization of MEG signals, to estimate functional connectivity. For the whole brain network topology, an undirected weighted graph was produced using 68 brain regions as nodes and interregional PLI values as edges for five frequency bands. Behavioral data (i.e., the degree of attention and facial expressions) were evaluated from video images of the child's face during the two conditions. Our results showed enhanced widespread functional connectivity in the alpha band during the mother condition. In the mother condition, the whole brain network in the alpha band exhibited topographically high local segregation with high global integration, indicating an increased small-world property. Results of the behavioral analysis revealed that children were more attentive and showed more positive facial expressions in the mother condition than in the experimenter condition. Behavioral data were significantly correlated with graph metrics in the mother condition but not in the experimenter condition. In this study, we identified the neural correlates of a familiarity effect in children's brain connectivity dynamics during LSBR. Furthermore, these familiarity-related brain dynamics were closely linked to the child's behavior. Graph theory applied to MEG data may provide useful insight into the familiarity-related child brain response in a naturalistic setting and its relevance to child attitudes.