Health-related risky behaviors and their risk factors in adolescents with high-functioning autism

BACKGROUND Health-related risky behaviors generally refer to behaviors that have a negative impact on health and quality of life.Health-related risky behaviors in adolescents with high-functioning autism(HFA)have not been well understood so far.Adolescents with HFA may have more health-related risky behaviors than neurotypical adolescents.AIM To investigate health-related risky behaviors and their risk factors with HFA.METHODS This is an observational study.Our study enrolled 110 adolescents aged 12-19-years-old meeting Diagnostic and Statistical Manual of Mental Disorders 4th edition criteria for HFA.They were recruited from Peking University Sixth Hospital.There were also 110 age,sex and nationality matched controls enrolled who came from a public school in Beijing,China.Both groups completed the Adolescents Health-related Risky Behavior Inventory.Nonparametric tests were carried out for comparison of the Adolescents Health-related Risky Behavior Inventory scores between the two groups.Expression recognition,the Inventory of Subjective Life Quality for Child and Adolescent,Chinese Wechsler Intelligence Scale for Children,Wechsler Intelligence Scale for Adult-Chinese Revised,Theory of Mind test and Autism Spectrum Screening Questionnaire were assessed in the autism group to explore factors associated with health-related risky behaviors.Multivariate regression analysis was conducted to explore the risk factors of health-related risky behaviors in the HFA group.RESULTS The results showed that the total score of the Adolescents Health-related Risky Behavior Inventory and scores of“aggression and violence,”“suicide and selfinjury,”“health compromising behavior”and“unprotected sex”subscales in the HFA group were significantly higher than those in the control group(Z range-4.197 to-2.213,P<0.05).Among the associated factors,poor emotional experience(B=-0.268,P<0.001),depression(B=-0.321,P<0.001),low score of intelligence(B=-0.032,P=0.042),low score of Theory of Mind test(B=-1.321,P=0.003)and poor adaptation to school life(B=-0.152,P=0.006)were risk factors.These risky behaviors may promote the occurrence of health-related risky behaviors in adolescents with HFA.CONCLUSION This study showed that adolescents with HFA were more likely to be involved in health-related risky behaviors.Different health-related risky behaviors have different reasons.

Cortical activity in patients with high-functioning ischemic stroke during the Purdue Pegboard Test:insights into bimanual coordinated fine motor skills with functional near-infrared spectroscopy

After stroke,even high-functioning individuals may experience compromised bimanual coordination and fine motor dexterity,leading to reduced functional independence.Bilateral arm training has been proposed as a promising intervention to address these deficits.However,the neural basis of the impairment of functional fine motor skills and their relationship to bimanual coordination performance in stroke patients remains unclear,limiting the development of more targeted interventions.To address this gap,our study employed functional near-infrared spectroscopy to investigate cortical responses in patients after stroke as they perform functional tasks that engage fine motor control and coordination.Twenty-four high-functioning patients with ischemic stroke(7 women,17 men;mean age 64.75±10.84 years)participated in this cross-sectional observational study and completed four subtasks from the Purdue Pegboard Test,which measures unimanual and bimanual finger and hand dexterity.We found significant bilateral activation of the sensorimotor cortices during all Purdue Pegboard Test subtasks,with bimanual tasks inducing higher cortical activation than the assembly subtask.Importantly,patients with better bimanual coordination exhibited lower cortical activation during the other three Purdue Pegboard Test subtasks.Notably,the observed neural response patterns varied depending on the specific subtask.In the unaffected hand task,the differences were primarily observed in the ipsilesional hemisphere.In contrast,the bilateral sensorimotor cortices and the contralesional hemisphere played a more prominent role in the bimanual task and assembly task,respectively.While significant correlations were found between cortical activation and unimanual tasks,no significant correlations were observed with bimanual tasks.This study provides insights into the neural basis of bimanual coordination and fine motor skills in high-functioning patients after stroke,highlighting task-dependent neural responses.The findings also suggest that patients who exhibit better bimanual performance demonstrate more efficient cortical activation.Therefore,incorporating bilateral arm training in post-stroke rehabilitation is important for better outcomes.The combination of functional near-infrared spectroscopy with functional motor paradigms is valuable for assessing skills and developing targeted interventions in stroke rehabilitation.

Facial Image-Based Autism Detection:A Comparative Study of Deep Neural Network Classifiers

Autism Spectrum Disorder(ASD)is a neurodevelopmental condition characterized by significant challenges in social interaction,communication,and repetitive behaviors.Timely and precise ASD detection is crucial,particularly in regions with limited diagnostic resources like Pakistan.This study aims to conduct an extensive comparative analysis of various machine learning classifiers for ASD detection using facial images to identify an accurate and cost-effective solution tailored to the local context.The research involves experimentation with VGG16 and MobileNet models,exploring different batch sizes,optimizers,and learning rate schedulers.In addition,the“Orange”machine learning tool is employed to evaluate classifier performance and automated image processing capabilities are utilized within the tool.The findings unequivocally establish VGG16 as the most effective classifier with a 5-fold cross-validation approach.Specifically,VGG16,with a batch size of 2 and the Adam optimizer,trained for 100 epochs,achieves a remarkable validation accuracy of 99% and a testing accuracy of 87%.Furthermore,the model achieves an F1 score of 88%,precision of 85%,and recall of 90% on test images.To validate the practical applicability of the VGG16 model with 5-fold cross-validation,the study conducts further testing on a dataset sourced fromautism centers in Pakistan,resulting in an accuracy rate of 85%.This reaffirms the model’s suitability for real-world ASD detection.This research offers valuable insights into classifier performance,emphasizing the potential of machine learning to deliver precise and accessible ASD diagnoses via facial image analysis.

Evaluation of Clinician Training in Autism Screening, Care Management, and Patient Education

Objective: The demand for pediatric developmental evaluations has far exceeded the workforce available to perform them, which creates long significant wait times for services. A year-long clinician training using the Extension for Community Healthcare Outcomes (ECHO®) model with monthly meetings was conducted and evaluated for its impact on primary care clinicians’ self-reported self-efficacy, ability to administer autism screening and counsel families, professional fulfillment, and burnout. Methods: Participants represented six community health centers and a hospital-based practice. Data collection was informed by participant feedback and the Normalization Process Theory via online surveys and focus groups/interviews. Twelve virtual monthly trainings were delivered between November 2020 and October 2021. Results: 30 clinicians participated in data collection. Matched analyses (n = 9) indicated statistically significant increase in self-rated ability to counsel families about autism (Pre-test Mean = 3.00, Post-test Mean = 3.89, p = 0.0313), manage autistic patients’ care (Pre-test Mean = 2.56, Post-test Mean = 4.11, p = 0.0078), empathy toward patients (Pre-test Mean = 2.11, Post-test Mean = 1.22, p = 0.0156) and colleagues (Pre-test Mean = 2.33, Post-test Mean = 1.22, respectively, p = 0.0391). Unmatched analysis revealed increases in participants confident about educating patients about autism (70.59%, post-test n = 12 vs. 3.33%, pre-test n = 1, p = 0.0019). Focus groups found increased confidence in using the term “autism”. Conclusion: Participants reported increases in ability and confidence to care for autistic patients, as well as empathy toward patients and colleagues. Future research should explore long-term outcomes in participants’ knowledge retention, confidence in practice, and improvements to autism evaluations and care.

Nutritional epigenetics education improves diet and attitude of parents of children with autism or attention deficit/hyperactivity disorder

BACKGROUND Unhealthy maternal diet leads to heavy metal exposures from the consumption of ultra-processed foods that may impact gene behavior across generations,creating conditions for the neurodevelopmental disorders known as autism and attention deficit/hyperactivity disorder(ADHD).Children with these disorders have difficulty metabolizing and excreting heavy metals from their bloodstream,and the severity of their symptoms correlates with the heavy metal levels measured in their blood.Psychiatrists may play a key role in helping parents reduce their ultra-processed food and dietary heavy metal intake by providing access to effective nutritional epigenetics education.AIM To test the efficacy of nutritional epigenetics instruction in reducing parental ultra-processed food intake.METHODS The study utilized a semi-randomized test and control group pretest-posttest pilot study design with participants recruited from parents having a learning-disabled child with autism or ADHD.Twenty-two parents who met the inclusion criteria were randomly selected to serve in the test(n=11)or control(n=11)group.The test group participated in the six-week online nutritional epigenetics tutorial,while the control group did not.The efficacy of the nutritional epigenetics instruction was determined by measuring changes in parent diet and attitude using data derived from an online diet survey administered to the participants during the pre and post intervention periods.Diet intake scores were derived for both ultra-processed and whole/organic foods.Paired sample t-tests were conducted to determine any differences in mean diet scores within each group.RESULTS There was a significant difference in the diet scores of the test group between the pre-and post-intervention periods.The parents in the test group significantly reduced their intake of ultra-processed foods with a preintervention diet score of 70(mean=5.385,SD=2.534)and a post-intervention diet score of 113(mean=8.692,SD=1.750)and the paired t-test analysis showing a significance of P<0.001.The test group also significantly increased their consumption of whole and/or organic foods with a pre-intervention diet score of 100(mean=5.882,SD=2.472)and post-intervention diet score of 121(mean=7.118,SD=2.390)and the paired t-test analysis showing a significance of P<0.05.CONCLUSION Here we show nutritional epigenetics education can be used to reduce ultra-processed food intake and improve attitude among parents having learning-disabled children with autism or ADHD.

Des-Arg(9)bradykinin as a causal metabolite for autism spectrum disorder

BACKGROUND Early diagnosis and therapeutic interventions can greatly enhance the developmental trajectory of children with autism spectrum disorder(ASD).However,the etiology of ASD is not completely understood.The presence of confounding factors from environment and genetics has increased the difficulty of the identification of diagnostic biomarkers for ASD.AIM To estimate and interpret the causal relationship between ASD and metabolite profile,taking into consideration both genetic and environmental influences.METHODS A two-sample Mendelian randomization(MR)analysis was conducted using summarized data from large-scale genome-wide association studies(GWAS)including a metabolite GWAS dataset covering 453 metabolites from 7824 European and an ASD GWAS dataset comprising 18381 ASD cases and 27969 healthy controls.Metabolites in plasma were set as exposures with ASD as the main outcome.The causal relationships were estimated using the inverse variant weight(IVW)algorithm.We also performed leave-one-out sensitivity tests to validate the robustness of the results.Based on the drafted metabolites,enrichment analysis was conducted to interpret the association via constructing a protein-protein interaction network with multi-scale evidence from databases including Infinome,SwissTargetPrediction,STRING,and Metascape.RESULTS Des-Arg(9)-bradykinin was identified as a causal metabolite that increases the risk of ASD(β=0.262,SE=0.064,P_(IVW)=4.64×10^(-5)).The association was robust,with no significant heterogeneity among instrument variables(P_(MR Egger)=0.663,P_(IVW)=0.906)and no evidence of pleiotropy(P=0.949).Neuroinflammation and the response to stimulus were suggested as potential biological processes mediating the association between Des-Arg(9)bradykinin and ASD.CONCLUSION Through the application of MR,this study provides practical insights into the potential causal association between plasma metabolites and ASD.These findings offer perspectives for the discovery of diagnostic or predictive biomarkers to support clinical practice in treating ASD.

Melatonin improves synapse development by PI3K/Akt signaling in a mouse model of autism spectrum disorder

Autism spectrum disorders are a group of neurodevelopmental disorders involving more than 1100 genes,including Ctnnd2 as a candidate gene.Ctnnd2knockout mice,serving as an animal model of autis m,have been demonstrated to exhibit decreased density of dendritic spines.The role of melatonin,as a neuro hormone capable of effectively alleviating social interaction deficits and regulating the development of dendritic spines,in Ctnnd2 deletion-induced nerve injury remains unclea r.In the present study,we discove red that the deletion of exon 2 of the Ctnnd2 gene was linked to social interaction deficits,spine loss,impaired inhibitory neurons,and suppressed phosphatidylinositol-3-kinase(PI3K)/protein kinase B(Akt) signal pathway in the prefrontal cortex.Our findings demonstrated that the long-term oral administration of melatonin for 28 days effectively alleviated the aforementioned abnormalities in Ctnnd2 gene-knockout mice.Furthermore,the administration of melatonin in the prefro ntal cortex was found to improve synaptic function and activate the PI3K/Akt signal pathway in this region.The pharmacological blockade of the PI3K/Akt signal pathway with a PI3K/Akt inhibitor,wo rtmannin,and melatonin receptor antagonists,luzindole and 4-phenyl-2-propionamidotetralin,prevented the melatonin-induced enhancement of GABAergic synaptic function.These findings suggest that melatonin treatment can ameliorate GABAe rgic synaptic function by activating the PI3K/Akt signal pathway,which may contribute to the improvement of dendritic spine abnormalities in autism spectrum disorders.

Faith and Belief in Autism in Cote d’Ivoire: About Judith, God’s Strange Gift

Faced with autism, motherhood and parenthood are turned upside down in many ways. Coping with stress and mental health problems, continuing to assume a rewarding parental role and finding suitable care are the trials and tribulations that mark out the journey of African parents. Faith and belief have been described as providing meaning and coping mechanisms in the frightening ordeal of disability. An encounter with a young girl and her parents provided an opportunity to analyse the mother’s experience and the impact of beliefs and discourses on her commitment to care. Based on this clinical story, we discuss the place of other-actors (parents and carers) and the Other-God in relation to the psychopathological dynamics of the mother.

Moral judgment and cooperation in children with high-functioning autism

With the support by the National Natural Science Foundation of China and the Chinese Academy of Sciences,Dr.Li Jing and Prof.Zhu Liqi at the Institute of Psychology,Chinese Academy of Sciences,reported the relationship between moral judgment and cooperation in children with high-functioning autism,which was published in Scientific Reports(2014,4:4314.doi:10.1038/srep04314).

Metabolomic changes in children with autism

BACKGROUND Autism spectrum disorder(ASD)is a neurodevelopmental condition characterized by deficits in social communication and repetitive behaviors.Metabolomic profiling has emerged as a valuable tool for understanding the underlying metabolic dysregulations associated with ASD.AIM To comprehensively explore metabolomic changes in children with ASD,integrating findings from various research articles,reviews,systematic reviews,meta-analyses,case reports,editorials,and a book chapter.METHODS A systematic search was conducted in electronic databases,including PubMed,PubMed Central,Cochrane Library,Embase,Web of Science,CINAHL,Scopus,LISA,and NLM catalog up until January 2024.Inclusion criteria encompassed research articles(83),review articles(145),meta-analyses(6),systematic reviews(6),case reports(2),editorials(2),and a book chapter(1)related to metabolomic changes in children with ASD.Exclusion criteria were applied to ensure the relevance and quality of included studies.RESULTS The systematic review identified specific metabolites and metabolic pathways showing consistent differences in children with ASD compared to typically developing individuals.These metabolic biomarkers may serve as objective measures to support clinical assessments,improve diagnostic accuracy,and inform personalized treatment approaches.Metabolomic profiling also offers insights into the metabolic alterations associated with comorbid conditions commonly observed in individuals with ASD.CONCLUSION Integration of metabolomic changes in children with ASD holds promise for enhancing diagnostic accuracy,guiding personalized treatment approaches,monitoring treatment response,and improving outcomes.Further research is needed to validate findings,establish standardized protocols,and overcome technical challenges in metabolomic analysis.By advancing our understanding of metabolic dysregulations in ASD,clinicians can improve the lives of affected individuals and their families.

Autism的本质理解及翻译问题研究

心理学概念autism有两个汉语译名:孤独症与自闭症。两个译名同时并用,造成了不同程度的混乱和误解。从词源学翻译及理论史双重视角看,autism的本质及合适译名不是孤独症,而是自闭症。孤独症是错误的意译,不符合autism的原始含义,易将其本质误解为极度孤独或依恋障碍。自闭症译名更能反映autism的本义,更符合《精神障碍诊断与统计手册》诊断体系对autism的临床描述,即以自我封闭为根本特征的社交障碍。因此,学界应当放弃孤独症译名,只用自闭症来翻译和理解autism,以避免不正确的病因学解释及一词两译带来的其他问题。

Play therapy in children with autism:Its role,implications,and limitations

Play is a pleasurable physical or mental activity that enhances the child’s skills involving negotiation abilities,problem-solving,manual dexterity,sharing,decision-making,and working in a group.Play affects all the brain's areas,structures,and functions.Children with autism have adaptive behavior,adaptive response,and social interaction limitations.This review explores the different applications of play therapy in helping children with autism disorder.Play is usually significantly impaired in children with autism.Play therapy is mainly intended to help children to honor their unique mental abilities and developmental levels.The main aim of play therapy is to prevent or solve psychosocial difficulties and achieve optimal child-healthy growth and development.Play therapy helps children with autism to engage in play activities of their interest and choice to express themselves in the most comfortable ways.It changes their way of self-expression from unwanted behaviors to more non-injurious expressive behavior using toys or activities of their choice as their words.Play therapy also helps those children to experience feeling out various interaction styles.Every child with autism is unique and responds differently.Therefore,different types of intervention,like play therapy,could fit the differences in children with autism.Proper evaluation of the child is mandatory to evaluate which type fits the child more than the others.This narrative review revised the different types of play therapy that could fit children with autism in an evidence-based way.Despite weak evidence,play therapy still has potential benefits for patients and their families.

Conditional Generative Adversarial Network Approach for Autism Prediction

Autism Spectrum Disorder(ASD)requires a precise diagnosis in order to be managed and rehabilitated.Non-invasive neuroimaging methods are disease markers that can be used to help diagnose ASD.The majority of available techniques in the literature use functional magnetic resonance imaging(fMRI)to detect ASD with a small dataset,resulting in high accuracy but low generality.Traditional supervised machine learning classification algorithms such as support vector machines function well with unstructured and semi structured data such as text,images,and videos,but their performance and robustness are restricted by the size of the accompanying training data.Deep learning on the other hand creates an artificial neural network that can learn and make intelligent judgments on its own by layering algorithms.It takes use of plentiful low-cost computing and many approaches are focused with very big datasets that are concerned with creating far larger and more sophisticated neural networks.Generative modelling,also known as Generative Adversarial Networks(GANs),is an unsupervised deep learning task that entails automatically discovering and learning regularities or patterns in input data in order for the model to generate or output new examples that could have been drawn from the original dataset.GANs are an exciting and rapidly changingfield that delivers on the promise of generative models in terms of their ability to generate realistic examples across a range of problem domains,most notably in image-to-image translation tasks and hasn't been explored much for Autism spectrum disorder prediction in the past.In this paper,we present a novel conditional generative adversarial network,or cGAN for short,which is a form of GAN that uses a generator model to conditionally generate images.In terms of prediction and accuracy,they outperform the standard GAN.The pro-posed model is 74%more accurate than the traditional methods and takes only around 10 min for training even with a huge dataset.

Pharmacotherapy in autism spectrum disorders,including promising older drugs warranting trials

Available pharmacotherapies for autism spectrum disorders(ASD)are reviewed based on clinical and research experience,highlighting some older drugs with emerging evidence.Several medications show efficacy in ASD,though controlled studies in ASD are largely lacking.Only risperidone and aripiprazole have Federal Drug Administration approval in the United States.Methylphenidate(MPH)studies showed lower efficacy and tolerability for attention deficit hyperactivity disorder(ADHD)than in the typically developing(TD)population;atomoxetine demonstrated lower efficacy but comparable tolerability to TD outcomes.Guanfacine improved hyperactivity in ASD comparably to TD.Dextroamphetamine promises greater efficacy than MPH in ASD.ADHD medications reduce impulsive aggression in youth,and may also be key for this in adults.Controlled trials of the selective serotonin reuptake inhibitors citalopram and fluoxetine demonstrated poor tolerability and lack of efficacy for repetitive behaviors.Trials of antiseizure medications in ASD remain inconclusive,however clinical trials may be warranted in severely disabled individuals showing bizarre behaviors.No identified drugs treat ASD core symptoms;oxytocin lacked efficacy.Amitriptyline and loxapine however,show promise.Loxapine at 5-10 mg daily resembled an atypical antipsychotic in positron emission tomography studies,but may be weight-sparing.Amitriptyline at approximately 1 mg/kg/day used cautiously,shows efficacy for sleep,anxiety,impulsivity and ADHD,repetitive behaviors,and enuresis.Both drugs have promising neurotrophic properties.

Attention-Deficit/Hyperactivity Disorder in Adults with High-Functioning Pervasive Developmental Disorders in Japan

Aims: This study was designed to verify the proportion of Japanese adults with pervasive developmental disorder (PDD) who met the diagnostic criteria (other than E) for attention-deficit/hyperactivity disorder (ADHD) in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). Furthermore, we examined to what extent adults with PDD think that they exhibit ADHD symptoms. Methods: We developed an original Japanese self-report questionnaire to determine the presence or absence of 18 symptoms from the diagnostic criteria for ADHD in the DSM-IV-TR. We administered the questionnaire to 64 adults with high-functioning PDD (45 men and 19 women) and 21 adults with ADHD (10 men and 11 women), aged 18 to 59 years, with a full-scale intelligence quotient ≥75. Target patients were evaluated for ADHD by their psychiatrists. Results: Twenty-nine (45.3%) adults with PDD also had ADHD. The percentage of these adults who had over six perceived inattention symptoms from the DSM-IV-TR was 96.6%. The percentage of these adults who had over six perceived hyperactivity-impulsivity symptoms was 65.5%. Thirty-five (55.6%) adults with PDD responded that they were aware of having ADHD symptoms at the level of the relevant diagnostic criteria. Conclusions: The present study is the first to examine the frequency of objective and perceived ADHD symptoms in adults with PDD in Japan. Our results show that both objective and perceived ADHD symptoms frequently appear in a large number of adults with PDD. This suggests that it is necessary to attend to concomitant ADHD symptoms in the medical care of adults with PDD.

Higher rates of autism and attention deficit/hyperactivity disorder in American children:Are food quality issues impacting epigenetic inheritance?

In the United States,schools offer special education services to children who are diagnosed with a learning or neurodevelopmental disorder and have difficulty meeting their learning goals.Pediatricians may play a key role in helping children access special education services.The number of children ages 6-21 in the United States receiving special education services increased 10.4%from 2006 to 2021.Children receiving special education services under the autism category increased 242%during the same period.The demand for special education services for children under the developmental delay and other health impaired categories increased by 184%and 83%respectively.Although student enrollment in American schools has remained stable since 2006,the percentage distribution of children receiving special education services nearly tripled for the autism category and quadrupled for the developmental delay category by 2021.Allowable heavy metal residues remain persistent in the American food supply due to food ingredient manufacturing processes.Numerous clinical trial data indicate heavy metal exposures and poor diet are the primary epigenetic factors responsible for the autism and attention deficit hyperactivity disorder epidemics.Dietary heavy metal exposures,especially inorganic mercury and lead may impact gene behavior across generations.In 2021,the United States Congress found heavy metal residues problematic in the American food supply but took no legislative action.Mandatory health warning labels on select foods may be the only way to reduce dietary heavy metal exposures and improve child learning across generations.

Risk of Autism Spectrum Disorder According to the Dose and Trimester of Exposure to Antiseizure Medications: A Systematic Review and Meta-Analysis

Background: The association between prenatal exposure to antiseizure medications (ASM) and autism spectrum disorder has been documented. This study sought to examine and synthesize evidence from studies that have evaluated these associations, with particular focus on the trimester of pregnancy and dosage of exposure. Methodology: PubMed, Embase, and PsycINFO databases were searched following strict inclusion/exclusion criteria. 10 studies were recruited involving children born to mothers with epilepsy who took ASM during pregnancy as cases, and those with epilepsy who did not take any ASM in pregnancy. Results: The relative risk of developing ASD among children exposed to valproic acid (RR, 3.90 [95% CI: 2.36 - 6.44], p < 0.006), was twice higher than that of carbamazepine (RR, 1.65 [95% CI: 0.62 - 4.37], p < 0.0001), or lamotrigine (RR, 1.60 [95% CI: 0.77 - 3.32], p = 0.006). The trimester of exposure and dosage of ASM administered were not significant. Conclusion: In summary, prenatal exposure to ASM increased the risk of developing ASD in children. The relative risk was twice as high in those exposed to valproic acid compared to those exposed to carbamazepine or lamotrigine. Trimester of pregnancy and dosage of ASM used by the mothers were not significant.

Pre-autism:What a paediatrician should know about early diagnosis of autism

Autism,also known as an autism spectrum disorder,is a complex neurodevelopmental disorder usually diagnosed in the first three years of a child's life.A range of symptoms characterizes it and can be diagnosed at any age,including adolescence and adulthood.However,early diagnosis is crucial for effective management,prognosis,and care.Unfortunately,there are no established fetal,prenatal,or newborn screening programs for autism,making early detection difficult.This review aims to shed light on the early detection of autism prenatally,natally,and early in life,during a stage we call as“pre-autism”when typical symptoms are not yet apparent.Some fetal,neonatal,and infant biomarkers may predict an increased risk of autism in the coming baby.By developing a biomarker array,we can create an objective diagnostic tool to diagnose and rank the severity of autism for each patient.These biomarkers could be genetic,immunological,hormonal,metabolic,amino acids,acute phase reactants,neonatal brainstem function biophysical activity,behavioral profile,body measurements,or radiological markers.However,every biomarker has its accuracy and limitations.Several factors can make early detection of autism a real challenge.To improve early detection,we need to overcome various challenges,such as raising community awareness of early signs of autism,improving access to diagnostic tools,reducing the stigma attached to the diagnosis of autism,and addressing various culturally sensitive concepts related to the disorder.

Estimating Brain Functional Networks Based on Spatiotemporal Higher-Order Correlations for Autism Identification

Brain functional network (BFN) has become an important tool for the analysis and diagnosis of brain diseases, and how to build a high-quality BFN based on resting-state functional magnetic resonance imaging (rs-fMRI) has become a growing concern in the neuroscience community. Although some methods have been proposed to construct a high-quality BFN, they only encode the spatial characteristics of the ROIs, ignoring the temporal characteristics. As a result, it becomes challenging to accurately capture the true state of the brain. To address this problem, we propose a novel method to construct a higher-order BFN, considering both temporal and spatial domain characteristics. In particular, we get the characteristics of the temporal domain by differentiating the rs-fMRI signal itself, and then we integrate the information of the spatial domain and temporal domain to build a high-order BFN. To evaluate the proposed method, we conduct our experiments on ABIDE database to identify subjects with Autism Spectrum Disorder (ASD) from normal controls. Experimental results show that our method can achieve higher performance than baseline methods.

Consistent and Specific Multi-View Functional Brain Networks Fusion for Autism Spectrum Disorder Diagnosis

Functional brain networks (FBN) based on resting-state functional magnetic resonance imaging (rs-fMRI) have become an important tool for exploring underlying organization patterns in the brain, which can provide an objective basis for brain disorders such as autistic spectrum disorder (ASD). Due to its importance, researchers have proposed a number of FBN estimation methods. However, most existing methods only model a type of functional connection relationship between brain regions-of-interest (ROIs), such as partial correlation or full correlation, which is difficult to fully capture the subtle connections among ROIs since these connections are extremely complex. Motivated by the multi-view learning, in this study we propose a novel Consistent and Specific Multi-view FBNs Fusion (CSMF) approach. Concretely, we first construct multi-view FBNs (i.e., multiple types of FBNs modelling various relationships among ROIs), and then these FBNs are decomposed into a consistent representation matrix and their own specific matrices which capture their common and unique information, respectively. Lastly, to obtain a better brain representation, it is fusing the consistent and specific representation matrices in the latent representation spaces of FBNs, but not directly fusing the original FBNs. This potentially makes it more easily to find the comprehensively brain connections. The experimental results of ASD identification on the ABIDE datasets validate the effectiveness of our proposed method compared to several state-of-the-art methods. Our proposed CSMF method achieved 72.8% and 76.67% classification performance on the ABIDE dataset.