scholarly journals Multidimensional Neuroanatomical Subtyping of Autism Spectrum Disorder

2017 ◽  
Vol 28 (10) ◽  
pp. 3578-3588 ◽  
Author(s):  
Seok-Jun Hong ◽  
Sofie L Valk ◽  
Adriana Di Martino ◽  
Michael P Milham ◽  
Boris C Bernhardt
Keyword(s):  
Autism Spectrum Disorder ◽  
Surface Area ◽  
Geodesic Distance ◽  
Autism Diagnostic Observation Schedule ◽  
Analytical Framework ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Learning Approaches ◽  
Bootstrap Analysis ◽  
Severity Prediction

Abstract Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders with multiple biological etiologies and highly variable symptoms. Using a novel analytical framework that integrates cortex-wide MRI markers of vertical (i.e., thickness, tissue contrast) and horizontal (i.e., surface area, geodesic distance) cortical organization, we could show that a large multi-centric cohort of individuals with ASD falls into 3 distinctive anatomical subtypes (ASD-I: cortical thickening, increased surface area, tissue blurring; ASD-II: cortical thinning, decreased distance; ASD-III: increased distance). Bootstrap analysis indicated a high consistency of these biotypes across thousands of simulations, while analysis of behavioral phenotypes and resting-state fMRI showed differential symptom load (i.e., Autism Diagnostic Observation Schedule; ADOS) and instrinsic connectivity anomalies in communication and social-cognition networks. Notably, subtyping improved supervised learning approaches predicting ADOS score in single subjects, with significantly increased performance compared to a subtype-blind approach. The existence of different subtypes may reconcile previous results so far not converging on a consistent pattern of anatomical anomalies in autism, and possibly relate the presence of diverging corticogenic and maturational anomalies. The high accuracy for symptom severity prediction indicates benefits of MRI biotyping for personalized diagnostics and may guide the development of targeted therapeutic strategies.

scholarly journals A Deep Learning Approach to Predict Autism Spectrum Disorder Using Multisite Resting-State fMRI

2021 ◽  
Vol 11 (8) ◽  
pp. 3636
Author(s):  
Faria Zarin Subah ◽  
Kaushik Deb ◽  
Pranab Kumar Dhar ◽  
Takeshi Koshiba
Keyword(s):  
Autism Spectrum Disorder ◽  
Resting State ◽  
State Of The Art ◽  
Resting State Fmri ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Bootstrap Analysis ◽  
Proposed Model ◽  
Art Methods ◽  
The Mean

Autism spectrum disorder (ASD) is a complex and degenerative neuro-developmental disorder. Most of the existing methods utilize functional magnetic resonance imaging (fMRI) to detect ASD with a very limited dataset which provides high accuracy but results in poor generalization. To overcome this limitation and to enhance the performance of the automated autism diagnosis model, in this paper, we propose an ASD detection model using functional connectivity features of resting-state fMRI data. Our proposed model utilizes two commonly used brain atlases, Craddock 200 (CC200) and Automated Anatomical Labelling (AAL), and two rarely used atlases Bootstrap Analysis of Stable Clusters (BASC) and Power. A deep neural network (DNN) classifier is used to perform the classification task. Simulation results indicate that the proposed model outperforms state-of-the-art methods in terms of accuracy. The mean accuracy of the proposed model was 88%, whereas the mean accuracy of the state-of-the-art methods ranged from 67% to 85%. The sensitivity, F1-score, and area under receiver operating characteristic curve (AUC) score of the proposed model were 90%, 87%, and 96%, respectively. Comparative analysis on various scoring strategies show the superiority of BASC atlas over other aforementioned atlases in classifying ASD and control.

scholarly journals Social Attention Deficits in Children With Autism Spectrum Disorder: Task Dependence of Objects vs. Faces Observation Bias

2021 ◽  
Vol 12 ◽  
Author(s):  
Susana Mouga ◽  
João Castelhano ◽  
Cátia Café ◽  
Daniela Sousa ◽  
Frederico Duque ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Autism Diagnostic Observation Schedule ◽  
Autism Spectrum ◽  
Social Attention ◽  
Spectrum Disorder ◽  
Attention Deficits ◽  
Social Stimuli ◽  
Task Dependence ◽  
Observation Bias ◽  
Autism Diagnostic Observation

Social attention deficits represent a central impairment of patients suffering from autism spectrum disorder (ASD), but the nature of such deficits remains controversial. We compared visual attention regarding social (faces) vs. non-social stimuli (objects), in an ecological diagnostic context, in 46 children and adolescents divided in two groups: ASD (N = 23) and typical neurodevelopment (TD) (N = 23), matched for chronological age and intellectual performance. Eye-tracking measures of visual scanning, while exploring and describing scenes from three different tasks from the Autism Diagnostic Observation Schedule (ADOS), were analyzed: “Description of a Picture,” “Cartoons,” and “Telling a Story from a Book.” Our analyses revealed a three-way interaction between Group, Task, and Social vs. Object Stimuli. We found a striking main effect of group and a task dependence of attentional allocation: while the TD attended first and longer to faces, ASD participants became similar to TD when they were asked to look at pictures while telling a story. Our results suggest that social attention allocation is task dependent, raising the question whether spontaneous attention deficits can be rescued by guiding goal-directed actions.

scholarly journals An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder

2018 ◽  
Vol 50 (5) ◽  
pp. 727-736 ◽  
Author(s):  
Donna M. Werling ◽  
Harrison Brand ◽  
Joon-Yong An ◽  
Matthew R. Stone ◽  
Lingxue Zhu ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Genome Sequence ◽  
Association Studies ◽  
Analytical Framework ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Whole Genome Sequence ◽  
Whole Genome

Autism severity, co-occurring psychopathology, and intellectual functioning predict supportive school services for youth with autism spectrum disorder

Autism ◽  
2019 ◽  
Vol 23 (7) ◽  
pp. 1805-1816 ◽  
Author(s):  
Tamara E Rosen ◽  
Christine J Spaulding ◽  
Jacquelyn A Gates ◽  
Matthew D Lerner
Keyword(s):  
Autism Spectrum Disorder ◽  
Internalizing Symptoms ◽  
Psychiatric Symptoms ◽  
Skills Training ◽  
Autism Diagnostic Observation Schedule ◽  
Intellectual Functioning ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Multiple Sources ◽  
School Services

Supportive school services are a primary service modality for youth with autism spectrum disorder. Autism spectrum disorder, as well as co-occurring psychiatric symptoms and low intellectual abilities, interfere with academic achievement and therefore influence decisions about school services. Therefore, we examined the association of parent, teacher, and clinician ratings of autism spectrum disorder and co-occurring psychiatric symptom severity and intellectual functioning with school services. In total, 283 youth with autism spectrum disorder were assessed with clinical evaluation via the Autism Diagnostic Observation Schedule and parent and teacher versions of the CASI-4R ( Child and Adolescent Symptom Inventory). Full Scale Intelligence Quotient scores were obtained from case records. Clinical and teacher evaluations of autism spectrum disorder severity predicted services and were more strongly associated with school services than parent ratings. Teacher ratings were only associated with common school services (e.g. speech/language therapy, occupational therapy, and/or social skills training) frequency at medium and high levels of clinician-rated autism spectrum disorder severity. Higher IQ and parent-rated externalizing symptoms predicted lower likelihood of receiving school services, whereas internalizing symptoms were not predictive of school services. Autism spectrum disorder symptoms may overshadow externalizing and internalizing symptoms when considering school service supports. Results highlight the importance of evaluating autism spectrum disorder severity via multiple sources, especially in cases of unclear symptom presentation, when examining correlates of school services for youth with autism spectrum disorder.

When an Early Diagnosis of Autism Spectrum Disorder Resolves, What Remains?

2019 ◽  
Vol 34 (7) ◽  
pp. 382-386 ◽  
Author(s):  
Lisa Shulman ◽  
Erin D’Agostino ◽  
Samantha Lee ◽  
Maria Valicenti-McDermott ◽  
Rosa Seijo ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Rating Scale ◽  
Autism Diagnostic Observation Schedule ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Learning Problems ◽  
Educational Support ◽  
Autism Diagnostic Observation ◽  
Cognitive Data

A chart review was performed of 38 children diagnosed with autism spectrum disorder (ASD) by 3 years of age at an inner-city developmental program who subsequently experienced resolution of ASD symptomatology and no longer met diagnostic criteria for ASD at follow-up an average of 4 years later. Demographic, developmental/cognitive data, Childhood Autism Rating Scale, and Autism Diagnostic Observation Schedule data as available were reviewed from the initial diagnostic evaluation and at the time of follow-up. Services received by the children between the time of diagnosis and follow-up, educational setting at the time of follow-up, and emotional/behavioral and learning diagnoses made by the multidisciplinary team at follow-up were reviewed. The findings indicate that residual emotional/behavioral and learning problems were present at follow-up in the vast majority of children in this group and that the majority continued to require educational support.

scholarly journals Autism spectrum disorder screening in preschools

Autism ◽  
2020 ◽  
pp. 136236132096752
Author(s):  
Angel Hoe-chi Au ◽  
Kathy Kar-man Shum ◽  
Yongtian Cheng ◽  
Hannah Man-yan Tse ◽  
Rose Mui-fong Wong ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Clinical Training ◽  
Peer Interaction ◽  
Screening Tool ◽  
Classroom Observation ◽  
Stress Test ◽  
Autism Diagnostic Observation Schedule ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Observation Scale

Can non-clinicians spot preschoolers likely to have autism spectrum disorder by observing their everyday peer interaction? We set out to develop a screening tool that capitalizes on peer interaction as a naturalistic “stress test” to identify children more likely than their peers to have autism spectrum disorder. A total of 304 3- to 4-year-olds were observed at school with an 84-item preliminary checklist; data-driven item reduction yielded a 13-item Classroom Observation Scale. The Classroom Observation Scale scores correlated significantly with Autism Diagnostic Observation Schedule–2 scores. To validate the scale, another 322 2- to 4-year-olds were screened using the Classroom Observation Scale. The screen-positive children and randomly selected typically developing peers were assessed for autism spectrum disorder 1.5 years later. The Classroom Observation Scale as used by teachers and researchers near preschool onset predicted autism spectrum disorder diagnoses 1.5 years later (odds ratios = 14.6 and 6.7, respectively). This user-friendly 13-item Classroom Observation Scale enables teachers and healthcare workers with little or no clinical training to identify, with reliable and valid results, preschoolers more likely than their peers to have autism spectrum disorder. Lay abstract With professional training and regular opportunities to observe children interacting with their peers, preschool teachers are in a good position to notice children’s autism spectrum disorder symptomatology. Yet even when a preschool teacher suspects that a child may have autism spectrum disorder, fear of false alarm may hold the teacher back from alerting the parents, let alone suggesting them to consider clinical assessment for the child. A valid and convenient screening tool can help preschool teachers make more informed and hence more confident judgment. We set out to develop a screening tool that capitalizes on peer interaction as a naturalistic “stress test” to identify children more likely than their peers to have autism spectrum disorder. A total of 304 3- to 4-year-olds were observed at school with an 84-item preliminary checklist; data-driven item reduction yielded a 13-item Classroom Observation Scale. The Classroom Observation Scale scores correlated significantly with Autism Diagnostic Observation Schedule–2 scores. To validate the scale, another 322 2- to 4-year-olds were screened using the Classroom Observation Scale. The screen-positive children and randomly selected typically developing peers were assessed for autism spectrum disorder 1.5 years later. The Classroom Observation Scale as used by teachers and researchers near preschool onset predicted autism spectrum disorder diagnoses 1.5 years later. This user-friendly 13-item Classroom Observation Scale enables teachers and healthcare workers with little or no clinical training to identify, with reliable and valid results, preschoolers more likely than their peers to have autism spectrum disorder.

scholarly journals “Are We Done Yet?” Question-Asking in Boys With Fragile X Syndrome and Idiopathic Autism Spectrum Disorder

2020 ◽  
Vol 63 (6) ◽  
pp. 1822-1834
Author(s):  
Laura Friedman ◽  
Emily Lorang ◽  
Elizabeth Hilvert ◽  
Audra Sterling
Keyword(s):  
Autism Spectrum Disorder ◽  
Fragile X Syndrome ◽  
Fragile X ◽  
Autism Diagnostic Observation Schedule ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Frequency Function ◽  
Question Asking ◽  
Social Settings ◽  
New Information

Purpose Question-asking serves as a tool to learn new information and is important in both academic and social settings. Boys with idiopathic autism spectrum disorder (ASD) and boys with fragile X syndrome and comorbid ASD (FXS + ASD) have similar social communication deficits, which may have downstream effects on their question-asking ability. This study examined question-asking in school-age boys with idiopathic ASD and FXS + ASD, including the role of ASD severity, expressive grammatical complexity (measured by mean length of utterance [MLU]), and IQ. Method Twenty-five boys with FXS + ASD and 21 boys with idiopathic ASD (ages 9–16 years) were included in this study. Autism Diagnostic Observation Schedule assessments were transcribed and coded for the frequency, function, and appropriateness of spontaneous questions asked. We examined group differences in these aspects of question-asking and relationships between question-asking and ASD severity, MLU, and IQ within each group. Results Boys with FXS + ASD asked more questions than boys with idiopathic ASD, although boys with idiopathic ASD asked a higher proportion of appropriate questions. Boys with idiopathic ASD also asked the examiner more personal questions than the boys with FXS + ASD. ASD severity and MLU were related to the proportion of clarification questions in FXS + ASD, and ASD severity was also related to the proportion of personal questions in this group. For the boys with idiopathic ASD, ASD severity was related to the total number of questions asked. Conclusions Our findings highlight similarities and differences between boys with FXS + ASD and idiopathic ASD in their spontaneous question production and indicate that ASD severity and grammatical language are differentially important for question-asking. This study has implications for targeted treatment in question-asking skills for boys with FXS + ASD and ASD.

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