Language and sensory characteristics are reflected in voice-evoked responses in low birth weight children.

BACKGROUND: Children born with very low birth weight (VLBW) are at higher risk for cognitive impairment, including language deficits and sensorimotor difficulties. Voice-evoked response (P1m), which has been suggested as a language development biomarker in young children, remains unexplored for its efficacy in VLBW children. Furthermore, the relation between P1m and sensory difficulties in VLBW children remains unclear. METHODS: 40 children with VLBW were recruited at 5-to-6 years old (26 male, 14 female, mean age of months ± SD, 80.0 ± 4.9). We measured their voice-evoked brain response using child-customized magnetoencephalography (MEG) and examined the relation between P1m and language conceptual inference ability and sensory characteristics. RESULTS: The final sample comprised 36 children (23 boys, 13 girls; ages 61-86 months; gestational ages 24-36 weeks). As a result of multiple regression analysis, voice-evoked P1m in the left hemisphere was correlated significantly with language ability (ß = 0.414 P = 0.015) and sensory hypersensitivity (ß = 0.471 P = 0.005). CONCLUSION: Our findings indicate that the relation between P1m and language conceptual inference ability observed in term children in earlier studies is replicated in VLBW children, and suggests P1m intensity as a biomarker of sensory sensitivity characteristics. IMPACT: We investigated brain functions related to language development and sensory problems in very low birth-weight children. In very low birth weight children at early school age, brain responses to human voices are associated with language conceptual inference ability and sensory hypersensitivity. These findings promote a physiological understanding of both language development and sensory characteristics in very low birth weight children.

Dual-MEG interbrain synchronization during turn-taking verbal interactions between mothers and children.

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.

Effects of familiarity on child brain networks when listening to a storybook reading: A magneto-encephalographic study.

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.

Effect of intranasal oxytocin on the core social symptoms of autism spectrum disorder: a randomized clinical trial.

Although small-scale studies have described the effects of oxytocin on social deficits in autism spectrum disorder (ASD), no large-scale study has been conducted. In this randomized, parallel-group, multicenter, placebo-controlled, double-blind trial in Japan, 106 ASD individuals (18-48 y.o.) were enrolled between Jan 2015 and March 2016. Participants were randomly assigned to a 6-week intranasal oxytocin (48IU/day, n = 53) or placebo (n = 53) group. One-hundred-three participants were analyzed. Since oxytocin reduced the primary endpoint, Autism Diagnostic Observation Schedule (ADOS) reciprocity, (from 8.5 to 7.7; P < .001) but placebo also reduced the score (8.3 to 7.2; P < .001), no between-group difference was found (effect size -0.08; 95% CI, -0.46 to 0.31; P = .69); however, plasma oxytocin was only elevated from baseline to endpoint in the oxytocin-group compared with the placebo-group (effect size -1.12; -1.53 to -0.70; P < .0001). Among the secondary endpoints, oxytocin reduced ADOS repetitive behavior (2.0 to 1.5; P < .0001) compared with placebo (2.0 to 1.8; P = .43) (effect size 0.44; 0.05 to 0.83; P = .026). In addition, the duration of gaze fixation on socially relevant regions, another secondary endpoint, was increased by oxytocin (41.2 to 52.3; P = .03) compared with placebo (45.7 to 40.4; P = .25) (effect size 0.55; 0.10 to 1.0; P = .018). No significant effects were observed for the other secondary endpoints. No significant difference in the prevalence of adverse events was observed between groups, although one participant experienced temporary gynecomastia during oxytocin administration. Based on the present findings, we cannot recommend continuous intranasal oxytocin treatment alone at the current dose and duration for treatment of the core social symptoms of high-functioning ASD in adult men, although this large-scale trial suggests oxytocin's possibility to treat ASD repetitive behavior.

Shorter P1m Response in Children with Autism Spectrum Disorder without Intellectual Disabilities.

(1) Background: Atypical auditory perception has been reported in individuals with autism spectrum disorder (ASD). Altered auditory evoked brain responses are also associated with childhood ASD. They are likely to be associated with atypical brain maturation. (2) Methods: This study examined children aged 5-8 years old: 29 with ASD but no intellectual disability and 46 age-matched typically developed (TD) control participants. Using magnetoencephalography (MEG) data obtained while participants listened passively to sinusoidal pure tones, bilateral auditory cortical response (P1m) was examined. (3) Results: Significantly shorter P1m latency in the left hemisphere was found for children with ASD without intellectual disabilities than for children with TD. Significant correlation between P1m latency and language conceptual ability was found in children with ASD, but not in children with TD. (4) Conclusions: These findings demonstrated atypical brain maturation in the auditory processing area in children with ASD without intellectual disability. Findings also suggest that ASD has a common neural basis for pure-tone sound processing and language development. Development of brain networks involved in language concepts in early childhood ASD might differ from that in children with TD.

Complexity of Body Movements during Sleep in Children with Autism Spectrum Disorder.

Recently, measuring the complexity of body movements during sleep has been proven as an objective biomarker of various psychiatric disorders. Although sleep problems are common in children with autism spectrum disorder (ASD) and might exacerbate ASD symptoms, their objectivity as a biomarker remains to be established. Therefore, details of body movement complexity during sleep as estimated by actigraphy were investigated in typically developing (TD) children and in children with ASD. Several complexity analyses were applied to raw and thresholded data of actigraphy from 17 TD children and 17 children with ASD. Determinism, irregularity and unpredictability, and long-range temporal correlation were examined respectively using the false nearest neighbor (FNN) algorithm, information-theoretic analyses, and detrended fluctuation analysis (DFA). Although the FNN algorithm did not reveal determinism in body movements, surrogate analyses identified the influence of nonlinear processes on the irregularity and long-range temporal correlation of body movements. Additionally, the irregularity and unpredictability of body movements measured by expanded sample entropy were significantly lower in ASD than in TD children up to two hours after sleep onset and at approximately six hours after sleep onset. This difference was found especially for the high-irregularity period. Through this study, we characterized details of the complexity of body movements during sleep and demonstrated the group difference of body movement complexity across TD children and children with ASD. Complexity analyses of body movements during sleep have provided valuable insights into sleep profiles. Body movement complexity might be useful as a biomarker for ASD.

Brain responses to human-voice processing predict child development and intelligence.

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.

Quantitative facial expression analysis revealed the efficacy and time course of oxytocin in autism.

Discrepancies in efficacy between single-dose and repeated administration of oxytocin for autism spectrum disorder have led researchers to hypothesize that time-course changes in efficacy are induced by repeated administrations of the peptide hormone. However, repeatable, objective, and quantitative measurement of autism spectrum disorder's core symptoms are lacking, making it difficult to examine potential time-course changes in efficacy. We tested this hypothesis using repeatable, objective, and quantitative measurement of the core symptoms of autism spectrum disorder. We examined videos recorded during semi-structured social interaction administered as the primary outcome in single-site exploratory (n = 18, crossover within-subjects design) and multisite confirmatory (n = 106, parallel-group design), double-blind, placebo-controlled 6-week trials of repeated intranasal administrations of oxytocin (48 IU/day) in adult males with autism spectrum disorder. The main outcomes were statistical representative values of objectively quantified facial expression intensity in a repeatable part of the Autism Diagnostic Observation Schedule: the maximum probability (i.e. mode) and the natural logarithm of mode on the probability density function of neutral facial expression and the natural logarithm of mode on the probability density function of happy expression. Our recent study revealed that increases in these indices characterize autistic facial expression, compared with neurotypical individuals. The current results revealed that oxytocin consistently and significantly decreased the increased natural logarithm of mode on the probability density function of neutral facial expression compared with placebo in exploratory (effect-size, -0.57; 95% CI, -1.27 to 0.13; P = 0.023) and confirmatory trials (-0.41; -0.62 to -0.20; P < 0.001). A significant interaction between time-course (at baseline, 2, 4, 6, and 8 weeks) and the efficacy of oxytocin on the natural logarithm of mode on the probability density function of neutral facial expression was found in confirmatory trial (P < 0.001). Post hoc analyses revealed maximum efficacy at 2 weeks (P < 0.001, Cohen's d = -0.78; 95% CI, -1.21 to -0.35) and deterioration of efficacy at 4 weeks (P = 0.042, Cohen's d = -0.46; 95% CI, -0.90 to -0.01) and 6 weeks (P = 0.10, Cohen's d = -0.35; 95% CI, -0.77 to 0.08), while efficacy was preserved at 2 weeks post-treatment (i.e. 8 weeks) (P < 0.001, Cohen's d = -1.24; 95% CI, -1.71 to -0.78). Quantitative facial expression analyses successfully verified the positive effects of repeated oxytocin on autistic individuals' facial expressions and demonstrated a time-course change in efficacy. The current findings support further development of an optimized regimen of oxytocin treatment.

Auditory steady-state response at 20 Hz and 40 Hz in young typically developing children and children with autism spectrum disorder.

AIM: The early detection of autistic tendencies in children is essential for providing proper care and education. The auditory steady-state response (ASSR) provides a passive, non-invasive technique for assessing neural synchrony at specific response frequencies in many mental disorders, including autism spectrum disorder (ASD), but few studies have investigated its use in young children. This study investigated the ASSR at 20 Hz and 40 Hz in typically developing (TD) children and children with ASD aged 5-7 years. METHODS: The participants were 23 children with ASD and 32 TD children aged 5-7 years. Using a custom-made magnetoencephalography device, we measured ASSR at 20 Hz and 40 Hz, compared the results between groups, and evaluated the association with intellectual function as measured by Kaufmann Assessment Battery for Children. RESULTS: Responses to 20 Hz and 40 Hz were clearly detected in both groups with no significant difference identified. Consistent with previous findings, right dominance of the 40-Hz ASSR was observed in both groups. In the TD children, the right-side 40-Hz ASSR was correlated with age. The Kaufmann Assessment Battery for Children score was correlated with the left-side 40-Hz ASSR in both groups. CONCLUSION: Right-dominant ASSR was successfully detected in young TD children and children with ASD. No difference in ASSR was observed between the children with ASD and the TD children, although the right-side 40-Hz ASSR increased with age only in the TD children. Left-side 40-Hz ASSR was associated with intelligence score in both groups.

Altered Gamma Oscillations during Motor Control in Children with Autism Spectrum Disorder.

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.

Characteristics of communication among Japanese children with autism spectrum disorder: A cluster analysis using the Children's Communication Checklist-2.

Some overlap has been suggested among the subtypes of autism spectrum disorder (ASD) in children. The Japanese version of the Children's Communication Checklist-2 (CCC-2) is a useful measure for identifying profiles in relation to communication impairments in children with ASD. The aim of this study was to investigate whether the CCC-2 could identify subtypes in relation to communication impairments in Japanese children with ASD. The study participants were 113 children with ASD but without intellectual disabilities aged 3-12 years. Parents were given the Japanese version of the CCC-2 and asked to rate their children, who were then classified into two groups based on statistical analysis. Significant differences were found between clusters in mean CCC-2 subscales. These results suggest that one subtype was associated with low language competence and strong characteristics of autism, while the other was associated with relatively high language competence and milder characteristics of autism.

Enhanced brain signal variability in children with autism spectrum disorder during early childhood.

Extensive evidence shows that a core neurobiological mechanism of autism spectrum disorder (ASD) involves aberrant neural connectivity. Recent advances in the investigation of brain signal variability have yielded important information about neural network mechanisms. That information has been applied fruitfully to the assessment of aging and mental disorders. Multiscale entropy (MSE) analysis can characterize the complexity inherent in brain signal dynamics over multiple temporal scales in the dynamics of neural networks. For this investigation, we sought to characterize the magnetoencephalography (MEG) signal variability during free watching of videos without sound using MSE in 43 children with ASD and 72 typically developing controls (TD), emphasizing early childhood to older childhood: a critical period of neural network maturation. Results revealed an age-related increase of brain signal variability in a specific timescale in TD children, whereas atypical age-related alteration was observed in the ASD group. Additionally, enhanced brain signal variability was observed in children with ASD, and was confirmed particularly for younger children. In the ASD group, symptom severity was associated region-specifically and timescale-specifically with reduced brain signal variability. These results agree well with a recently reported theory of increased brain signal variability during development and aberrant neural connectivity in ASD, especially during early childhood. Results of this study suggest that MSE analytic method might serve as a useful approach for characterizing neurophysiological mechanisms of typical-developing and its alterations in ASD through the detection of MEG signal variability at multiple timescales.

Magnetoencephalography in the study of children with autism spectrum disorder.

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that provides a measure of cortical neural activity on a millisecond timescale with high spatial resolution. MEG has been clinically applied to various neurological diseases, including epilepsy and cognitive dysfunction. In the past decade, MEG has also emerged as an important investigatory tool in neurodevelopmental studies. It is therefore an opportune time to review how MEG is able to contribute to the study of atypical brain development. We limit this review to autism spectrum disorder (ASD). The relevant published work for children was accessed using PubMed on 5 January 2015. Case reports, case series, and papers on epilepsy were excluded. Owing to their accurate separation of brain activity in the right and left hemispheres and the higher accuracy of source localization, MEG studies have added new information related to auditory-evoked brain responses to findings from previous electroencephalography studies of children with ASD. In addition, evidence of atypical brain connectivity in children with ASD has accumulated over the past decade. MEG is well suited for the study of neural activity with high time resolution even in young children. Although further studies are still necessary, the detailed findings provided by neuroimaging methods may aid clinical diagnosis and even contribute to the refinement of diagnostic categories for neurodevelopmental disorders in the future.

Broader autism phenotype in mothers predicts social responsiveness in young children with autism spectrum disorders.

AIMS: The aim of this study was to identify phenotypes in mothers and fathers that are specifically associated with disturbances in reciprocal social interactions and communication in their young children with autism spectrum disorder (ASD) in a Japanese sample. METHODS: Autistic traits in parents were evaluated using the Autism-spectrum Quotient (AQ), the Empathy Quotient (EQ) and the Systemizing Quotient (SQ) in 88 parents (44 mothers and corresponding fathers) of children with ASD and in 60 parents (30 mothers and corresponding fathers) of typically developing (TD) children. For the measurement of autistic traits in children, we employed the Social Responsiveness Scale (SRS). RESULTS: In two of the five AQ subscales (social skills and communication), the parents of ASD children scored significantly higher than did the parents of TD children, regardless of whether the parent was a mother or a father. In addition, in mothers of ASD children, there were significant positive correlations between two of the five AQ subscales (attention-switching and communication) and the SRS T-score in their children. CONCLUSIONS: This is the first study to demonstrate that the social skills and communication subscales in the AQ are more sensitive as autism traits in a Japanese sample and to demonstrate that some autistic traits in mothers are specifically associated with disturbances in the social ability of their young children with ASD, as measured by the SRS score. Further study is necessary to determine whether these results were caused by genetic or environmental factors.

Unusual developmental pattern of brain lateralization in young boys with autism spectrum disorder: Power analysis with child-sized magnetoencephalography.

AIMS: Autism spectrum disorder (ASD) is often described as comprising an unusual brain growth pattern and aberrant brain lateralization. Although it is important to study the pathophysiology of the developing ASD cortex, examples of physiological brain lateralization in young children with ASD have yet to be well examined. METHODS: Thirty-eight boys with ASD (aged 3-7 years) and 38 typically developing (TD) boys (aged 3-8 years) concentrated on video programs and their brain activities were measured non-invasively. We employed a customized child-sized magnetoencephalography system in which the sensors were located as close to the brain as possible for optimal recording in young children. To produce a credible laterality index of the brain oscillations, we defined two clusters of sensors corresponding to the right and left hemispheres. We focused on the laterality index ([left - right]/[left+right]) of the relative power band in seven frequency bands. RESULTS: The TD group displayed significantly rightward lateralized brain oscillations in the theta-1 frequency bands compared to the ASD group. CONCLUSIONS: This is the first study to demonstrate unusual brain lateralization of brain oscillations measured by magnetoencephalography in young children with ASD.

A longitudinal study of auditory evoked field and language development in young children.

The relationship between language development in early childhood and the maturation of brain functions related to the human voice remains unclear. Because the development of the auditory system likely correlates with language development in young children, we investigated the relationship between the auditory evoked field (AEF) and language development using non-invasive child-customized magnetoencephalography (MEG) in a longitudinal design. Twenty typically developing children were recruited (aged 36-75 months old at the first measurement). These children were re-investigated 11-25 months after the first measurement. The AEF component P1m was examined to investigate the developmental changes in each participant's neural brain response to vocal stimuli. In addition, we examined the relationships between brain responses and language performance. P1m peak amplitude in response to vocal stimuli significantly increased in both hemispheres in the second measurement compared to the first measurement. However, no differences were observed in P1m latency. Notably, our results reveal that children with greater increases in P1m amplitude in the left hemisphere performed better on linguistic tests. Thus, our results indicate that P1m evoked by vocal stimuli is a neurophysiological marker for language development in young children. Additionally, MEG is a technique that can be used to investigate the maturation of the auditory cortex based on auditory evoked fields in young children. This study is the first to demonstrate a significant relationship between the development of the auditory processing system and the development of language abilities in young children.

Relationship between brain network pattern and cognitive performance of children revealed by MEG signals during free viewing of video.

Application of graph theory to analysis of functional networks in the brain is an important research trend. Extensive research on the resting state has shown a "small-world" organization of the brain network as a whole. However, the small-worldness of children's brain networks in a working state has not yet been well characterized. In this paper, we used a custom-made, child-sized magnetoencephalography (MEG) device to collect data from children while they were watching cartoon videos. Network structures were analyzed and compared with scores on the Kaufman Assessment Battery for Children (K-ABC). The results of network analysis showed that (1) the small-world scalar showed a negative correlation with the simultaneous processing raw score, a measure of visual processing (Gv) ability, and (2) the children with higher simultaneous processing raw scores possessed network structures that can be more efficient for local information processing than children with lower scores. These results were compatible with previous studies on the adult working state. Additional results obtained from further analysis of the frontal and occipital lobes indicated that high cognitive performance could represent better local efficiency in task-related sub-networks. Under free viewing of cartoon videos, brain networks were no longer confined to their strongest small-world states; connections became clustered in local areas such as the frontal and occipital lobes, which might be a more useful configuration for handling visual processing tasks.

Neural responses to syllable-induced P1m and social impairment in children with autism spectrum disorder and typically developing Peers.

In previous magnetoencephalography (MEG) studies, children with autism spectrum disorder (ASD) have been shown to respond differently to speech stimuli than typically developing (TD) children. Quantitative evaluation of this difference in responsiveness may support early diagnosis and intervention for ASD. The objective of this research is to investigate the relationship between syllable-induced P1m and social impairment in children with ASD and TD children. We analyzed 49 children with ASD aged 40-92 months and age-matched 26 TD children. We evaluated their social impairment by means of the Social Responsiveness Scale (SRS) and their intelligence ability using the Kaufman Assessment Battery for Children (K-ABC). Multiple regression analysis with SRS score as the dependent variable and syllable-induced P1m latency or intensity and intelligence ability as explanatory variables revealed that SRS score was associated with syllable-induced P1m latency in the left hemisphere only in the TD group and not in the ASD group. A second finding was that increased leftward-lateralization of intensity was correlated with higher SRS scores only in the ASD group. These results provide valuable insights but also highlight the intricate nature of neural mechanisms and their relationship with autistic traits.

Autism Detection in Children using Common Spatial Patterns of MEG Signals.

Autism exhibits a wide range of developmental disabilities and is associated with aberrant anatomical and functional neural patterns. To detect autism in young children (4-7 years) in an automatic and non-invasive fashion, we have recorded magnetoencephalogram (MEG) signals from 30 autistic and 30 age-matched typically developing (TD) children. We have used a machine learning classification framework with common spatial pattern (CSP)-based logarithmic band power (LBP) features. When comparing the LBP feature to the conventional logarithmic variance (LV) spatial pattern, CSP + LBP (92.77%) has performed better than CSP + LV (90.66%) in the 1-100 Hz frequency range for distinguishing autistic children from TD children. In frequency band-wise analysis using our proposed method, the high gamma frequency band (50-100 Hz) has shown the highest classification accuracy (97.14%). Our findings reveal that the occipital lobe exhibits the most distinct spatial pattern in autistic children over the whole frequency range. This study shows that spatial brain activation patterns can be utilized as potential biomarkers of autism in young children. The improved performance signifies the clinical relevance of the work for autism detection using MEG signals.