Decreased wrist rotation imitation abilities in children with autism spectrum disorder.

Introduction: While meaningless gross motor imitation (GMI) is a common challenge for children diagnosed with autism spectrum disorder (ASD), this topic has not attracted much attention and few appropriate test paradigms have been developed. Methods: The current study proposed a wrist rotation imitation (WRI) task (a meaningless GMI assignment), and established a WRI ability evaluation system using low-cost wearable inertial sensors, which acquired the simultaneous data of acceleration and angular acceleration during the WRI task. Three metrics (i.e., total rotation time, rotation amplitude, and symmetry) were extracted from those data of acceleration and angular acceleration, and then were adopted to construct classifiers based on five machine learning (ML) algorithms, including k-nearest neighbors, linear discriminant analysis, naive Bayes, support vector machines, and random forests. To illustrate our technique, this study recruited 49 ASD children (aged 3.5-6.5 years) and 59 age-matched typically developing (TD) children. Results: Findings showed that compared with TD children, those with ASD may exhibit shorter total rotation time, lower rotation amplitude, and weaker symmetry. This implies that children with ASD might exhibit decreased WRI abilities. The classifier with the naive Bayes algorithm outperformed than other four algorithms, and achieved a maximal classification accuracy of 88% and a maximal AUC value of 0.91. Two metrics (i.e., rotation amplitude and symmetry) had high correlations with the gross and fine motor skills [evaluated by Gesell Developmental Schedules-Third Edition and Psychoeducational Profile-3 (PEP-3)]. While, the three metrics had no significant correlation with the visual-motor imitation abilities (evaluated by the subdomain of PEP-3) and the ASD symptom severity [evaluated by the Childhood Autism Rating Scale (CARS)] . Discussion: The strengths of this study are associated with the low-cost measurement system, correlation between the WRI metrics and clinical measures, decreased WRI abilities in ASD, and high classification accuracy.

Early identification of autism spectrum disorder based on machine learning with eye-tracking data.

BACKGROUND: Early identification of autism spectrum disorder (ASD) improves long-term outcomes, yet significant diagnostic delays persist. METHODS: A retrospective cohort of 449 children (ASD: 246, typically developing [TD]: 203) was used for model development. Eye-movement data were collected from the participants watching videos that featured eye-tracking paradigms for assessing social and non-social cognition. Five machine learning algorithms, namely random forest, support vector machine, logistic regression, artificial neural network, and extreme gradient boosting, were trained to classify children with ASD and TD. The best-performing algorithm was selected to build the final model which was further evaluated in a prospective cohort of 80 children. The Shapley values interpreted important eye-tracking features. RESULTS: Random forest outperformed other algorithms during model development and achieved an area under the curve of 0.849 (< 3 years: 0.832, ≥ 3 years: 0.868) on the external validation set. Of the ten most important eye-tracking features, three measured social cognition, and the rest were related to non-social cognition. A deterioration in model performance was observed using only the social or non-social cognition-related eye-tracking features. LIMITATIONS: The sample size of this study, although larger than that of existing studies of ASD based on eye-tracking data, was still relatively small compared to the number of features. CONCLUSIONS: Machine learning models based on eye-tracking data have the potential to be cost- and time-efficient digital tools for the early identification of ASD. Eye-tracking phenotypes related to social and non-social cognition play an important role in distinguishing children with ASD from TD children.

Using machine learning to explore the characteristics of eye movement patterns and relationship with cognition ability of Chinese children aged 1-6 years.

Researchers have begun to investigate the relationship between eye movement characteristics of gaze patterns and cognitive abilities, and have attempted to use eye-tracking technology as a new method to evaluate cognitive abilities. Traditional eye movement analysis methods typically separate spatial and temporal information of eye movements, mostly analyze averaged data, and consider individual differences as noise. In addition, current eye movement studies on gaze patterns mostly involve adults, while research on infants and toddlers is limited with small sample sizes and narrow age ranges. It is still unknown whether the conclusions drawn from adult-based research can be applied to children. Consequently, eye movement research on gaze patterns in children is necessary. To address the concerns stated above, this study used the Hidden Markov machine learning method to model gaze patterns of 330 children aged 1-6 years while observing faces freely, and analyzed characteristics of eye movement gaze patterns. Additionally, we analyzed the correlation between gaze patterns of 31 toddlers aged 1-3 years and 37 preschoolers aged 4-6 years, and the different dimensions of cognitive abilities. The findings indicated that children exhibited holistic and analytic gaze patterns while observing different faces freely. More children adopted a holistic gaze pattern, and there were age-specific gaze pattern characteristics and regularities. Gaze patterns of toddlers may be correlated with their adaptive abilities and gaze patterns of preschoolers may be correlated with their visual space abilities. Specifically, toddlers aged 1-3 years showed a moderate negative correlation between the H-A scale and the adaptive dimension, while preschoolers aged 4-6 years showed a low negative correlation between the H-A scale and the visual space dimension. This study may provide new insights into the characteristics of children's eye-movement gaze patterns during face observation, and potentially offer objective evidence for future research aimed at promoting the use of eye-tracking technology in the assessment of toddlers' adaptive abilities and preschoolers' visual space abilities in the field of face perception.

Improving Accuracy of ADHD Diagnosis with the Combination of Brain Imaging and Behavioral Measures.

Neuropsychological measures may improve Attention-deficit/hyperactivity disorder (ADHD) diagnostic accuracy and enhance treatment response detection. Highquality evaluation indicators are necessary for accurate diagnosis of ADHD. Due to the high complexity of the pathogenesis of ADHD, it may not be possible to accurately diagnose ADHD only by relying on behavioral assessment or brain imaging examination. Therefore, the authors propose a comprehensive index that combines brain imaging behavioral and measures. The results showed that the classification performance of the composite index was better than that of the single behavior or brain image index.Clinical Relevance- The results of this study help to remind practicing clinicians to consider the results of multiple clinical examinations when clinically diagnosing ADHD patients.

Randomized, controlled trial of a mixed early start Denver model for toddlers and preschoolers with autism.

The early start Denver model (ESDM) has been extensively studied as a promising early intervention approach for young children with autism spectrum disorder (ASD). Various methodological drawbacks from earlier ESDM investigations must be rectified to expand the application scopes. For this purpose, the present study recruited a very large sample of 249 autistic children (aged 24-47 months), and used a randomized controlled design to compare outcomes from a mixed ESDM (M-ESDM) intervention with a mixed discrete trial teaching (M-DTT) intervention which remains one of the most commonly-used programming for early intervention. Over the course of a 12-week period, both groups (i.e., M-ESDM and M-DTT groups) received 25 h of intensive intervention per week using individual, group, and parent coaching techniques. Findings showed that: (i) the M-ESDM significantly outperformed the M-DTT in enhancing children's developmental abilities in gross motor and personal-social skills for toddlers and preschoolers, as well as in language for preschoolers with mild/moderate ASD and toddlers; and (ii) the M-ESDM dramatically reduced the severity of autistic symptoms in toddlers with severe ASD only, when compared to the M-DTT. However, the M-ESDM did not outperform the M-DTT in terms of improving children's developmental abilities in adaptability and fine motor for toddlers and preschoolers, as well as in language for preschoolers with severe ASD. In addition, when compared to the M-DTT, the M-ESDM did not show an advantage in reducing the severity of autistic symptoms in toddlers with mild/moderate ASD and preschoolers. Clinical Trial Registration: Chinese Clinical Trial Registry. Registration number ChiCTR200039492.

Nonlinear features of gaze behavior during joint attention in children with autism spectrum disorder.

Since children with autism spectrum disorder (ASD) might exhibit a variety of aberrant response to joint attention (RJA) behaviors, there is growing interest in identifying robust, reliable and valid eye-tracking metrics for determining differences in RJA behaviors between typically developing (TD) children and those with ASD. Previous eye-tracking studies have not been deeply investigated nonlinear features of gaze time-series during RJA. As a main motivation, this study aimed to extract three nonlinear features (i.e., complexity, long-range correlation, and local instability) of gaze time-series during RJA in children with ASD, which can be measured by fractal dimension (FD), Hurst exponent (H), and largest Lyapunov exponent (LLE), respectively. To illustrate our idea, this study adopted a publicly accessible database, including eye-tracking data collected during RJA from 19 children with ASD (7.74 ± 2.73) and 30 TD children (8.02 ± 2.89), and conducted a battery of nonparametric analysis of covariance (ANCOVA), where gender was used as covariable. Findings showed that gaze time-series during RJA in autistic children may generally have greater FD but lower H than that in TD controls. This implies that children with ASD possess more complex and unpredictable gaze behaviors during RJA than TD children. Furthermore, nonlinear metrics outperformed traditional eye-tracking metrics in obtaining higher identification performance with an accuracy of 82% and an AUC value of 0.81, distinguishing the differences between successful and failed RJA trails, and predicting the severity of ASD symptoms. Findings might bring some new insights into the understanding of the impairments in RJA behaviors for children with ASD.

Complex network of eye movements during rapid automatized naming.

Introduction: Although the method of visualizing eye-tracking data as a time-series might enhance performance in the understanding of gaze behavior, it has not yet been thoroughly examined in the context of rapid automated naming (RAN). Methods: This study attempted, for the first time, to measure gaze behavior during RAN from the perspective of network-domain, which constructed a complex network [referred to as gaze-time-series-based complex network (GCN)] from gaze time-series. Hence, without designating regions of interest, the features of gaze behavior during RAN were extracted by computing topological parameters of GCN. A sample of 98 children (52 males, aged 11.50 ± 0.28 years) was studied. Nine topological parameters (i.e., average degree, network diameter, characteristic path length, clustering coefficient, global efficiency, assortativity coefficient, modularity, community number, and small-worldness) were computed. Results: Findings showed that GCN in each RAN task was assortative and possessed "small-world" and community architecture. Additionally, observations regarding the influence of RAN task types included that: (i) five topological parameters (i.e., average degree, clustering coefficient, assortativity coefficient, modularity, and community number) could reflect the difference between tasks N-num (i.e., naming of numbers) and N-cha (i.e., naming of Chinese characters); (ii) there was only one topological parameter (i.e., network diameter) which could reflect the difference between tasks N-obj (i.e., naming of objects) and N-col (i.e., naming of colors); and (iii) when compared to GCN in alphanumeric RAN, GCN in non-alphanumeric RAN may have higher average degree, global efficiency, and small-worldness, but lower network diameter, characteristic path length, clustering coefficient, and modularity. Findings also illustrated that most of these topological parameters were largely independent of traditional eye-movement metrics. Discussion: This article revealed the architecture and topological parameters of GCN as well as the influence of task types on them, and thus brought some new insights into the understanding of RAN from the perspective of complex network.

Features of eye movements during rapid automatized naming in Chinese children aged 7-11 years.

Rapid Automatized Naming (RAN) tests have been well-documented to predict reading abilities as well as a variety of neurobiological disorders (e.g., developmental dyslexia). Traditional measures of RAN tests only take into account the naming time and accuracy and cannot reflect temporal-spatial features during RAN tests. Although the eye tracking approach appears to be a promising tool for characterizing the essential temporal-spatial characteristics of RAN tests, no research has been conducted to investigate whether and how gender, age, and task-type alter those characteristics. Additionally, no study has examined eye movements during a Chinese adaptation of RAN in order to expand the applicability of RAN to developmental dyslexia in Chinese. To address the concerns stated above, this article recruited 408 children (206 males, aged 7-11 years) and adopted eight measures to quantify features of eye movements during a Chinese adaptation of RAN. Findings showed that: (1) eight eye-movement measures had the main effects of task-type and age, but only five of them had the main effect of gender (in particular, females outperformed males); (2) RAN abilities observed by eight eye-movement measures initially developed quickly before the age of 9, and then entered a relatively sluggish development phase; (3) non-alphanumeric RAN tasks generally required higher mental load (implying more fixation counts, saccade counts, and regression counts, smaller average saccade amplitude, fixation duration fluctuation and saccade amplitude fluctuation, and longer average fixation duration and total time of naming) than alphanumeric ones; (4) there were significant correlations between total time of naming (a widely-used behavioral parameter) and other eye-movement measures; and (5) there were significant correlation between eight eye-movement measures and three attention-related skills observed from a number cancellation task. The current study might offer some perspectives on the understanding of normative data of eye movements during RAN in Chinese school-aged children, as well as the applications (e.g., developmental dyslexia) associated with RAN.

Development, Reliability, and Validity of the Preschool Learning Skills Scale: A Tool for Early Identification of Preschoolers at Risk of Learning Disorder in Mainland China.

Background: Early identification of children at risk of learning disorders (LD) may mitigate the adverse effects of delayed intervention by guiding children to receive preventive services at an earlier age. However, there is no assessment tool for the early identification of children at risk of LD in Mainland China. Therefore, this study aimed to create a Chinese version of the Preschool Learning Skills Scale and investigate its validity and reliability. Methods: Firstly, a pilot scale was designed based on literature review and expert review. Secondly, a pre-survey of the pilot scale was conducted. In phase 3, a formal survey was carried out to test the reliability and validity of the scale by involving 2,677 preschool children from 7 kindergartens. Data were collected using a checklist for demographic characteristics, the preschool learning skills scale, the Behavior Rating Inventory of Executive Function-Preschool Version (BRIEF-P), and Conners' Rating Scales. Results: The final scale included 38 items under seven factors. The reliability and validity tests confirmed that the Cronbach's alpha, split-half reliability, and test-retest reliability coefficients of the scale were 0.946, 0.888, and 0.941, respectively. The Spearman correlations of factor-total score ranged from 0.685 to 0.876. The results of criterion-related validity showed a direct and significant association between the preschool learning skills scale with the BRIEF-P (r = 0.641, P < 0.001) and the cognitive problems factor of Conners' Rating Scales (r = 0.564, P < 0.001). The model had a good fit (χ 2 /df = 3.489, RMSEA = 0.047, RMR = 0.024, CFI = 0.912, TLI = 0.900, and IFI = 0.912). Multigroup confirmatory factor analysis supported the structural and measurement invariance on the preschool learning skills scale across gender and grade. Conclusions: The developed preschool learning skills scale has good reliability and validity, indicating that the scale can be used to identify preschool children at risk of LD and can be recommended for use in clinical research and practice.

Entropy of eye movement during rapid automatized naming.

Numerous studies have focused on the understanding of rapid automatized naming (RAN), which can be applied to predict reading abilities and developmental dyslexia in children. Eye tracking technique, characterizing the essential ocular activities, might have the feasibility to reveal the visual and cognitive features of RAN. However, traditional measures of eye movements ignore many dynamical details about the visual and cognitive processing of RAN, and are usually associated with the duration of time spent on some particular areas of interest, fixation counts, revisited fixation counts, saccadic velocities, or saccadic amplitudes. To cope with this drawback, we suggested an entropy-based method to measure eye movements for the first time, which first mapped eye movements during RAN in a time-series and then analyzed the time-series by a proper definition of entropy from the perspective of information theory. Our findings showed that the entropy was more sensitive to reflect small perturbation (e.g., rapid movements between focuses in the presence of skipping or omitting some stimulus during RAN) of eye movements, and thus gained better performance than traditional measures. We also verified that the entropy of eye movements significantly deceased with the age and the task complexity of RAN, and significantly correlated with traditional eye-movement measures [e.g., total time of naming (TTN)] and the RAN-related skills [e.g., selective attention (SA), cognitive speed, and visual-motor integration]. Our findings may bring some new insights into the understanding of both RAN and eye tracking technique itself.

Establishing Normative Data for the Number Cancelation Test Among Children in Kindergartens and Primary Schools in China.

This study aimed to suggest an attention assessment tool using a Digital Pen for measuring the temporal-spatial parameters during the Number Cancelation Test (NCT), and then to establish the normative data for the NCT among children in kindergartens and primary schools in China by recruiting a total of 989 children (496 males). Four measures, i.e., selective attention (SA), speed of cognitive processing (SpC), averaged time of circlings (ATC), and averaged circumference of circled curves (ACCC), were proposed to evaluate the NCT performance. They basically have a development trend with fast speed in the beginning before Grade 1 or 2 of primary schools, and then enter an extremely slow development period (with ceiling or floor effect). SA and SpC have gender and grade main effects, while ATC and ACCC have the grade main effect, only. In particular, females have higher SA scores than males in middle class of kindergarten, and Grade 2-Grade 5 of primary school, but no gender differences in other grades; females have higher SpC scores than males in middle class of kindergarten, and Grade 3-4 of primary school, but no gender differences in other grades. More importantly, in clinical practice, if SA or SpC measure of a child is below than the 5th centile (i.e., p5 level) of his/her grade-specific normative data, then this child may be predicted to have a high-risk of learning disabilities. Findings suggest that the proposed method can be used for early screening of learning disabilities by setting appropriate cut-off values.

The Effect of Socioeconomic Disparities on Prefrontal Activation in Initiating Joint Attention: A Functional Near-Infrared Spectroscopy Evidence From Two Socioeconomic Status Groups.

Low socioeconomic status (SES) may generally have a long-lasting negative effect on cognitive development, and show deficits in the development of executive functions. However, it is unclear whether there is an SES-dependent disparity in the functional brain development of the prefrontal cortex. By collecting task-related functional near-infrared spectroscopy (fNIRS) data and behavioral data (e.g., intelligence, language, home reading environment (HRE), family income, and parental education level), the current study aimed to detect whether the SES of preschool children (N = 86) is associated with prefrontal activation during the joint attention task. Results verified that low-SES children show lower right prefrontal activation during joint attention than Relatively High-SES children. In addition, our findings confirmed the mediating effect of HRE on the association between SES and brain activation during joint attention, as well as that between SES and language ability. These results suggest that SES contributes to functional development of the prefrontal regions, and the improvement of HRE could be a potential strategy to intervene SES-related disparities on child development.

Altered Temporal Structure of Neural Phase Synchrony in Patients With Autism Spectrum Disorder.

Functional connectivity, quantified by phase synchrony, between brain regions is known to be aberrant in patients with autism spectrum disorder (ASD). Here, we evaluated the long-range temporal correlations of time-varying phase synchrony (TV-PS) of electrocortical oscillations in patients with ASD as well as typically developing people using detrended fluctuation analysis (DFA) after validating the scale-invariance of the TV-PS time series. By comparing the DFA exponents between the two groups, we found that those of the TV-PS time series of high-gamma oscillations were significantly attenuated in patients with ASD. Furthermore, the regions involved in aberrant TV-PS time series were mainly within the social ability and cognition-related cortical networks. These results support the notion that abnormal social functions observed in patients with ASD may be caused by the highly volatile phase synchrony states of electrocortical oscillations.

Negative affective processing is associated with cognitive control in early childhood: An fNIRS study.

The association between emotion and cognition has recently gathered interest in the field of cognitive neuroscience. However, the neural mechanism of negative emotion processing and its association with cognitive control in early childhood remains unclear. In the present study, we compared the processing of three emotions (i.e., negative, neutral, and positive emotions) and investigated the association between negative emotion processing and cognitive control in children aged 4-6 years (N = 43). Results indicated that children revealed greater brain activation when processing negative emotions than processing neutral and positive emotions. We also found a significant negative association between brain activation during negative emotion processing and reaction times of cognitive control, which represented children with better cognitive control evoked higher brain activation when processing negative emotions. The current study proposes a neural mechanism underlying emotion processing and provides important insights into the risk and future behavioral outcomes of potential psychological disorders.

Decreased Right Prefrontal Synchronization Strength and Asymmetry During Joint Attention in the Left-Behind Children: A Functional Near-Infrared Spectroscopy Study.

Although there are millions of left-behind children in China, the researches on brain structure and functions in left-behind children are not sufficient at the brain imaging level. This study aimed to explore whether there is decreased prefrontal synchronization during joint attention in left-behind children. Sixty children (65.12 ± 6.54 months, 29 males) with 34 left-behind children were recruited. The functional near-infrared spectroscopy (fNIRS) imaging data from the prefrontal cortex during joint attention, as well as behavioral measures (associated with family income, intelligence, language, and social-emotional abilities), were collected. Results verified that brain imaging data and behavioral measures are correlative and support that left-behind children have deficits in social-emotional abilities. More importantly, left-behind children showed decreased synchronization strength and asymmetry in the right middle frontal gyrus during joint attention. The findings suggest that decreased right prefrontal synchronization strength and asymmetry during joint attention might be vulnerability factors in the development of left-behind children.

Is left-behind a real reason for children's social cognition deficit? An fNIRS study on the effect of social interaction on left-behind preschooler's prefrontal activation.

The left-behind phenomenon, caused by parent out-migration, has become a common social issue and might lead to long-term and potential risks for children in rural areas of China. It is important to investigate the effect of social interaction on prefrontal activation of left-behind children in China because of possible effects of parent out-migration on children's social cognition. We recruited 81 rural Chinese preschoolers aged 52-76 months (mean = 64.98 ± 6.321 months) preschoolers with three different statuses of parental out-migration (including non-, partially, and completely left-behind children). Using functional Near-Infrared Spectroscopy (fNIRS), we compared behavior and brain activation and in three groups (non-, partially-, completely-left-behind children) under two different social interaction conditions (child-teacher and child-stranger situation). Results revealed that initiating joint attention (IJA) may evoke higher brain activation than responding to joint attention (RJA) in the prefrontal cortex (PFC), especially in the case of initiating joint attention with the stranger. In addition, the activation of joint attention was positively correlated with children's language score, cognitive flexibility, and facial expression recognition. More importantly, partially-left-behind children evoked higher brain activation in the IJA condition and presented a higher language level than completely/non-left-behind children. The current study provides insight into the neural basis of left-behind children's development and revealed for the first time that family economic level and left-behind status may contribute to the lower social cognition.

Effect of Picture-Book Reading With Additive Audio on Bilingual Preschoolers' Prefrontal Activation: A Naturalistic Functional Near-Infrared Spectroscopy Study.

Acquiring a second language (L2) has the power to shape cognition and even the function and structure of the brain. Picture-book reading with additive audio (PRA) is a popular and convenient means of providing L2 exposure for non-balanced bilingual children; however, its contribution to bilingual children's brain activity is unclear. This study conducted a rigorous bilingual word comprehension experiment and a naturalistic PRA task to explore the effect of L2 processing on brain activation among English as a foreign language (EFL) preschoolers, using functional near-infrared spectroscopy (fNIRS). We found that the two contexts of comprehending English words and bilingual switching (BS), which impose more cognitive control demands, activated the prefrontal cortex (PFC) more than did the condition of comprehending Chinese words. Furthermore, the effect of PFC activity in the condition of picture-book reading with additive English audio (English PRA) was also found to be greater than in the condition of picture-book reading with additive Chinese audio (Chinese PRA); moreover, the effect was modulated by story difficulty. Finally, a positive correlation was shown between EFL children's English competence and PFC activation through English PRA. This study indicates that the experiences of hearing L2 auditory stories in a picture-book reading activity yielded significant changes to early bilinguals' PFC functional for cognitive control and language processing.

Attenuated long-range temporal correlations of electrocortical oscillations in patients with autism spectrum disorder.

The aim of this study was to investigate the long-range temporal correlations (LRTCs) of instantaneous amplitude of electrocortical oscillations in patients with autism spectrum disorder (ASD). Using the resting-state electroencephalography (EEG) of 15 patients with ASD (aged between 5˜18 years, mean age = 11.6 years, SD = 4.4 years) and 18 typical developing (TD) people (aged between 5˜18 years, mean age = 8.9 years, SD = 2.4 years), we estimated the LRTCs of neuronal oscillations amplitude of 84 predefined cortical regions of interest using detrended fluctuation analysis (DFA) after confirming the presence of scale invariance. We found that the DFA exponents of instantaneous amplitude of beta and low-gamma oscillations were significantly attenuated in patients with ASD compared to TD participants. Moreover, the regions with attenuated DFA exponent were mainly located in social functions related cortical networks, including the default mode network (DMN), the mirror neuron system (MNS) and the salience network (SN). These findings suggest that ASD is associated with highly volatile neuronal states of electrocortical oscillations, which may be related to social and cognitive dysfunction in patients with ASD.

Differences in brain signal complexity between experts and novices when solving conceptual science problem: a functional near-infrared spectroscopy study.

Assessing the result of conceptual change (i.e., whether an individual has come to correctly understand a science concept) is important in science education, however traditional assessment methods lack objectivity. In this study, permutation entropy (PE) based complexity, a kind of entropy used to quantify the complexity describing the uncertainty of time series, was explored by the functional near-infrared spectroscopy to seek an objective neurobiological indicator for this assessment. Two groups of participants, engineering students (classified as "experts") and humanities students (classified as "novices"), were tested on their conceptions to discriminate the speed of cars according to the animation, while the hemodynamic response was recorded over their inferior frontal gyrus (IFG). The activation analysis, PE based complexity analysis, and k-means clustering analysis were conducted. The results indicated that experts performed the task better than novices in behavioral performances, and PE values in the IFG were smaller for experts, especially in the right IFG. Furthermore, the k-means clustering analysis showed that the PE could be a feature to classify the students into two groups. It is concluded that the PE is a promising neurobiological indicator for assessment of this kind.

Aberrant Intrinsic Brain Activity in Patients with Autism Spectrum Disorder: Insights from EEG Microstates.

Autism spectrum disorder (ASD) involves aberrant organization and functioning of large-scale brain networks. The aim of this study was to examine whether the resting-state EEG microstate analysis could provide novel insights into the abnormal temporal and spatial properties of intrinsic brain activities in patients with ASD. To achieve this goal, EEG microstate analysis was conducted on the resting-state EEG datasets of 15 patients with ASD and 18 healthy controls from the Healthy Brain Network. The parameters (i.e., duration, occurrence rate, time coverage and topographical configuration) of four classical microstate classes (i.e., class A, B, C and D) were statistically tested between two groups. The results showed that: (1) the occurrence rate and time coverage of microstate class B in ASD group were significantly larger than those in control group; (2) the duration of microstate class A, the duration and time coverage of microstate class C were significantly smaller than those in control group; (3) the map configuration and occurrence rate differed significantly between two groups for microstate class D. These results suggested that EEG microstate analysis could be used to detect the deviant functions of large-scale cortical activities in ASD, and may provide indices that could be used in clinical researches of ASD.