A New Paradigm for Autism Spectrum Disorder Discrimination in Children Utilizing EEG Data Collected During Cartoon Viewing With a Focus on Atypical Semantic Processing.
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| Názov: | A New Paradigm for Autism Spectrum Disorder Discrimination in Children Utilizing EEG Data Collected During Cartoon Viewing With a Focus on Atypical Semantic Processing. |
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| Autori: | Deng L; Department of Developmental and Behavioral Pediatric and Child Primary Care & Ministry of Education-Shanghai Key Laboratory for Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China., Lu MJ; Shanghai Municipal Public Security Bureau, Shanghai, China., Yang LT; University of Michigan, Ann Arbor, Michigan, USA., Zhang Y; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China., Tan HY; Department of Developmental and Behavioral Pediatric and Child Primary Care & Ministry of Education-Shanghai Key Laboratory for Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China., Cao M; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China., Li F; Department of Developmental and Behavioral Pediatric and Child Primary Care & Ministry of Education-Shanghai Key Laboratory for Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. |
| Zdroj: | Autism research : official journal of the International Society for Autism Research [Autism Res] 2025 Oct; Vol. 18 (10), pp. 1978-1990. Date of Electronic Publication: 2025 Aug 23. |
| Spôsob vydávania: | Journal Article |
| Jazyk: | English |
| Informácie o časopise: | Publisher: John Wiley & Sons, Inc Country of Publication: United States NLM ID: 101461858 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1939-3806 (Electronic) Linking ISSN: 19393806 NLM ISO Abbreviation: Autism Res Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Hoboken, NJ : John Wiley & Sons, Inc. |
| Výrazy zo slovníka MeSH: | Autism Spectrum Disorder*/physiopathology , Autism Spectrum Disorder*/diagnosis , Semantics* , Electroencephalography*/methods , Cartoons as Topic*, Humans ; Child ; Male ; Female ; Child, Preschool ; Machine Learning |
| Abstrakt: | Autism spectrum disorder (ASD) is characterized by impaired social interaction and communication skills, with semantic processing difficulties being a hallmark feature that significantly impacts social communication. While traditional neuroimaging studies have provided insights into language processing in ASD, ecological validity remains a challenge, particularly when assessing young children. This study introduces a novel approach to evaluate atypical semantic processing in children with ASD (aged 4-10 years) through electroencephalography (EEG) data collection during cartoon viewing, offering a more natural assessment environment. We developed an innovative methodology combining pretrained language models with regression techniques in a machine learning framework. The analysis incorporated the Six-dimensional Semantic Database system and EEG topographical mapping to investigate semantic processing preferences and neural mechanisms across various word dimensions. Our semantic processing model demonstrated robust performance with high sensitivity (91.3%) and moderate specificity (61.0%); findings successfully replicated in validation analysis. These results reveal distinct patterns in how children with ASD process semantic information, particularly in their integration and response to emotional semantic dimensions. These findings help us understand the language processing patterns in ASD and provide potential applications for auxiliary diagnosis in more natural settings, meeting important needs in clinical practice. (© 2025 International Society for Autism Research and Wiley Periodicals LLC.) |
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| Grant Information: | 82430104 National Natural Science Foundation of China; 82125032 National Natural Science Foundation of China; 81901826 National Natural Science Foundation of China; 81930095 National Natural Science Foundation of China; STI2030-Major Projects 2021ZD0200800 the China Brain Initiative Grant; 19410713500 Science and Technology Commission of Shanghai Municipality; 23Y21900500 Science and Technology Commission of Shanghai Municipality; 19ZR1405600 Science and Technology Commission of Shanghai Municipality; 20ZR1404900 Science and Technology Commission of Shanghai Municipality; 2018SHZDZX01 Science and Technology Commission of Shanghai Municipality; GWVI-11.1-34 Shanghai Municipal Commission of Health and Family Planning; 2020CXJQ01 Shanghai Municipal Commission of Health and Family Planning; 2018YJRC03 Shanghai Municipal Commission of Health and Family Planning; SHSMU-ZDCX20211100 Innovative Research Team of High-level Local University in Shanghai; 2018B030335001 Guangdong Key Project; ZJLab and Shanghai Center for Brain Science and Brain-inspired Technology |
| Contributed Indexing: | Keywords: autism spectrum disorder; cartoons as topic; early diagnosis; electroencephalography; semantics |
| Entry Date(s): | Date Created: 20250823 Date Completed: 20251022 Latest Revision: 20251022 |
| Update Code: | 20251022 |
| DOI: | 10.1002/aur.70105 |
| PMID: | 40847596 |
| Databáza: | MEDLINE |
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Nájsť tento článok vo Web of Science | Abstrakt: | Autism spectrum disorder (ASD) is characterized by impaired social interaction and communication skills, with semantic processing difficulties being a hallmark feature that significantly impacts social communication. While traditional neuroimaging studies have provided insights into language processing in ASD, ecological validity remains a challenge, particularly when assessing young children. This study introduces a novel approach to evaluate atypical semantic processing in children with ASD (aged 4-10 years) through electroencephalography (EEG) data collection during cartoon viewing, offering a more natural assessment environment. We developed an innovative methodology combining pretrained language models with regression techniques in a machine learning framework. The analysis incorporated the Six-dimensional Semantic Database system and EEG topographical mapping to investigate semantic processing preferences and neural mechanisms across various word dimensions. Our semantic processing model demonstrated robust performance with high sensitivity (91.3%) and moderate specificity (61.0%); findings successfully replicated in validation analysis. These results reveal distinct patterns in how children with ASD process semantic information, particularly in their integration and response to emotional semantic dimensions. These findings help us understand the language processing patterns in ASD and provide potential applications for auxiliary diagnosis in more natural settings, meeting important needs in clinical practice.<br /> (© 2025 International Society for Autism Research and Wiley Periodicals LLC.) |
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| ISSN: | 1939-3806 |
| DOI: | 10.1002/aur.70105 |