Baseline EEG in the first year of life: Preliminary insights into the development of autism spectrum disorder and language impairments
Early identification of neurodevelopmental disorders is important to ensure a prompt and effective intervention, thus improving the later outcome. Autism spectrum disorder (ASD) and language learning impairment (LLI) are among the most common neurodevelopmental disorders, and they share overlapping...
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| Published in | iScience Vol. 26; no. 7; p. 106987 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Elsevier Inc
21.07.2023
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2589-0042 2589-0042 |
| DOI | 10.1016/j.isci.2023.106987 |
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| Abstract | Early identification of neurodevelopmental disorders is important to ensure a prompt and effective intervention, thus improving the later outcome. Autism spectrum disorder (ASD) and language learning impairment (LLI) are among the most common neurodevelopmental disorders, and they share overlapping symptoms. This study aims to characterize baseline electroencephalography (EEG) spectral power in 6- and 12-month-old infants at higher likelihood of developing ASD and LLI, compared to typically developing infants, and to preliminarily verify if spectral power components associated with the risk status are also linked with the later ASD or LLI diagnosis. We found risk status for ASD to be associated with reduced power in the low-frequency bands and risk status for LLI with increased power in the high-frequency bands. Interestingly, later diagnosis shared similar associations, thus supporting the potential role of EEG spectral power as a biomarker useful for understanding pathophysiology and classifying diagnostic outcomes.
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•EEG spectral power measures represent a candidate biomarker for both ASD and LLI•Low power values in the low-frequency bands are associated with ASD outcome•High power values in the high-frequency bands are associated with LLI outcome
Behavioral neuroscience; Clinical neuroscience; Techniques in neuroscience |
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| AbstractList | Early identification of neurodevelopmental disorders is important to ensure a prompt and effective intervention, thus improving the later outcome. Autism spectrum disorder (ASD) and language learning impairment (LLI) are among the most common neurodevelopmental disorders, and they share overlapping symptoms. This study aims to characterize baseline electroencephalography (EEG) spectral power in 6- and 12-month-old infants at higher likelihood of developing ASD and LLI, compared to typically developing infants, and to preliminarily verify if spectral power components associated with the risk status are also linked with the later ASD or LLI diagnosis. We found risk status for ASD to be associated with reduced power in the low-frequency bands and risk status for LLI with increased power in the high-frequency bands. Interestingly, later diagnosis shared similar associations, thus supporting the potential role of EEG spectral power as a biomarker useful for understanding pathophysiology and classifying diagnostic outcomes. Early identification of neurodevelopmental disorders is important to ensure a prompt and effective intervention, thus improving the later outcome. Autism spectrum disorder (ASD) and language learning impairment (LLI) are among the most common neurodevelopmental disorders, and they share overlapping symptoms. This study aims to characterize baseline electroencephalography (EEG) spectral power in 6- and 12-month-old infants at higher likelihood of developing ASD and LLI, compared to typically developing infants, and to preliminarily verify if spectral power components associated with the risk status are also linked with the later ASD or LLI diagnosis. We found risk status for ASD to be associated with reduced power in the low-frequency bands and risk status for LLI with increased power in the high-frequency bands. Interestingly, later diagnosis shared similar associations, thus supporting the potential role of EEG spectral power as a biomarker useful for understanding pathophysiology and classifying diagnostic outcomes.Early identification of neurodevelopmental disorders is important to ensure a prompt and effective intervention, thus improving the later outcome. Autism spectrum disorder (ASD) and language learning impairment (LLI) are among the most common neurodevelopmental disorders, and they share overlapping symptoms. This study aims to characterize baseline electroencephalography (EEG) spectral power in 6- and 12-month-old infants at higher likelihood of developing ASD and LLI, compared to typically developing infants, and to preliminarily verify if spectral power components associated with the risk status are also linked with the later ASD or LLI diagnosis. We found risk status for ASD to be associated with reduced power in the low-frequency bands and risk status for LLI with increased power in the high-frequency bands. Interestingly, later diagnosis shared similar associations, thus supporting the potential role of EEG spectral power as a biomarker useful for understanding pathophysiology and classifying diagnostic outcomes. Early identification of neurodevelopmental disorders is important to ensure a prompt and effective intervention, thus improving the later outcome. Autism spectrum disorder (ASD) and language learning impairment (LLI) are among the most common neurodevelopmental disorders, and they share overlapping symptoms. This study aims to characterize baseline electroencephalography (EEG) spectral power in 6- and 12-month-old infants at higher likelihood of developing ASD and LLI, compared to typically developing infants, and to preliminarily verify if spectral power components associated with the risk status are also linked with the later ASD or LLI diagnosis. We found risk status for ASD to be associated with reduced power in the low-frequency bands and risk status for LLI with increased power in the high-frequency bands. Interestingly, later diagnosis shared similar associations, thus supporting the potential role of EEG spectral power as a biomarker useful for understanding pathophysiology and classifying diagnostic outcomes. • EEG spectral power measures represent a candidate biomarker for both ASD and LLI • Low power values in the low-frequency bands are associated with ASD outcome • High power values in the high-frequency bands are associated with LLI outcome Behavioral neuroscience; Clinical neuroscience; Techniques in neuroscience Early identification of neurodevelopmental disorders is important to ensure a prompt and effective intervention, thus improving the later outcome. Autism spectrum disorder (ASD) and language learning impairment (LLI) are among the most common neurodevelopmental disorders, and they share overlapping symptoms. This study aims to characterize baseline electroencephalography (EEG) spectral power in 6- and 12-month-old infants at higher likelihood of developing ASD and LLI, compared to typically developing infants, and to preliminarily verify if spectral power components associated with the risk status are also linked with the later ASD or LLI diagnosis. We found risk status for ASD to be associated with reduced power in the low-frequency bands and risk status for LLI with increased power in the high-frequency bands. Interestingly, later diagnosis shared similar associations, thus supporting the potential role of EEG spectral power as a biomarker useful for understanding pathophysiology and classifying diagnostic outcomes. [Display omitted] •EEG spectral power measures represent a candidate biomarker for both ASD and LLI•Low power values in the low-frequency bands are associated with ASD outcome•High power values in the high-frequency bands are associated with LLI outcome Behavioral neuroscience; Clinical neuroscience; Techniques in neuroscience |
| ArticleNumber | 106987 |
| Author | Piazza, Caterina Dondena, Chiara Riboldi, Elena Maria Riva, Valentina Cantiani, Chiara |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37534149$$D View this record in MEDLINE/PubMed |
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| Keywords | Techniques in neuroscience Behavioral neuroscience Clinical neuroscience |
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