Autism spectrum disorder detection using variable frequency complex demodulation of the electroretinogram / Sultan Mohammad MANJUR ; Md Billal HOSSAIN ; Fernando MARMOLEJO-RAMOS ; Irene O. LEE ; David H. SKUSE ; Dorothy A. THOMPSON ; Paul A. CONSTABLE in Research in Autism Spectrum Disorders, 109 (November 2023)  

Public ISBD [article]  inResearch in Autism Spectrum Disorders > 109 (November 2023) . - 102258 Titre : Autism spectrum disorder detection using variable frequency complex demodulation of the electroretinogram Type de document : texte imprimé Auteurs : Sultan Mohammad MANJUR, Auteur ; Md Billal HOSSAIN, Auteur ; Fernando MARMOLEJO-RAMOS, Auteur ; Irene O. LEE, Auteur ; David H. SKUSE, Auteur ; Dorothy A. THOMPSON, Auteur ; Paul A. CONSTABLE, Auteur Article en page(s) : 102258 Langues : Anglais (eng) Mots-clés : Electroretinogram  Signal analysis  Autism spectrum disorder  Machine learning Index. décimale : PER Périodiques Résumé : The early diagnosis of neurodevelopmental conditions such as autism spectrum disorder (ASD), is an unmet need. One difficulty is the identification of a biological signal that relates to the ASD phenotype. The electroretinogram (ERG) waveform has been identified as a possible signal that could categorize neurological conditions such as ASD. The ERG waveform is derived from the electrical activity of photoreceptors and retinal neurons in response to a brief flash of light and provides an indirect 'window' into the central nervous system. Traditionally, the waveform is analyzed in the time-domain, but more recently time-frequency spectrum (TFS) analysis of ERG has been successfully carried out using discrete wavelet transformation (DWT) to characterize the morphological features of the signal. In this study, we propose the use of a high resolution TFS technique, namely variable frequency complex demodulation (VFCDM), to decompose the ERG waveform based on two signal flash strengths to build machine learning (ML) models to categorize ASD. ERG waveforms from N = 217 subjects (71 ASD, 146 control), at two different flash strengths, 446 and 113 Troland seconds (Td.s), from both right and left eyes were included. We analyzed the raw ERG waveforms using DWT and VFCDM. We computed features from the TFSs and trained ML models such as Random Forest, Gradient Boosting, Support Vector Machine to classify ASD from controls. ML models were validated using a subject independent validation strategy, and we found that the ML models with VFCDM features outperformed models using the DWT, achieving an area under the receiver operating characteristics curve of 0.90 (accuracy = 0.81, sensitivity = 0.85, specificity = 0.78). We found that the higher frequency range (80-300 Hz) included more relevant information for classifying ASD compared to the lower frequencies. We also found that the stronger flash strength of 446 Td.s in the right eye provided the best classification result which supports VFCDM analysis of the ERG waveform as a potential tool to aid in the identification of the ASD phenotype. En ligne : https://doi.org/10.1016/j.rasd.2023.102258 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=517 [article] Autism spectrum disorder detection using variable frequency complex demodulation of the electroretinogram [texte imprimé] / Sultan Mohammad MANJUR, Auteur ; Md Billal HOSSAIN, Auteur ; Fernando MARMOLEJO-RAMOS, Auteur ; Irene O. LEE, Auteur ; David H. SKUSE, Auteur ; Dorothy A. THOMPSON, Auteur ; Paul A. CONSTABLE, Auteur . - 102258. Langues : Anglais (eng) in Research in Autism Spectrum Disorders > 109 (November 2023) . - 102258 Mots-clés : Electroretinogram  Signal analysis  Autism spectrum disorder  Machine learning Index. décimale : PER Périodiques Résumé : The early diagnosis of neurodevelopmental conditions such as autism spectrum disorder (ASD), is an unmet need. One difficulty is the identification of a biological signal that relates to the ASD phenotype. The electroretinogram (ERG) waveform has been identified as a possible signal that could categorize neurological conditions such as ASD. The ERG waveform is derived from the electrical activity of photoreceptors and retinal neurons in response to a brief flash of light and provides an indirect 'window' into the central nervous system. Traditionally, the waveform is analyzed in the time-domain, but more recently time-frequency spectrum (TFS) analysis of ERG has been successfully carried out using discrete wavelet transformation (DWT) to characterize the morphological features of the signal. In this study, we propose the use of a high resolution TFS technique, namely variable frequency complex demodulation (VFCDM), to decompose the ERG waveform based on two signal flash strengths to build machine learning (ML) models to categorize ASD. ERG waveforms from N = 217 subjects (71 ASD, 146 control), at two different flash strengths, 446 and 113 Troland seconds (Td.s), from both right and left eyes were included. We analyzed the raw ERG waveforms using DWT and VFCDM. We computed features from the TFSs and trained ML models such as Random Forest, Gradient Boosting, Support Vector Machine to classify ASD from controls. ML models were validated using a subject independent validation strategy, and we found that the ML models with VFCDM features outperformed models using the DWT, achieving an area under the receiver operating characteristics curve of 0.90 (accuracy = 0.81, sensitivity = 0.85, specificity = 0.78). We found that the higher frequency range (80-300 Hz) included more relevant information for classifying ASD compared to the lower frequencies. We also found that the stronger flash strength of 446 Td.s in the right eye provided the best classification result which supports VFCDM analysis of the ERG waveform as a potential tool to aid in the identification of the ASD phenotype. En ligne : https://doi.org/10.1016/j.rasd.2023.102258 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=517

Behavioural and neurodevelopmental characteristics of SYNGAP1 / Nadja BEDNARCZUK in Journal of Neurodevelopmental Disorders, 16 (2024)  

Public ISBD [article]  inJournal of Neurodevelopmental Disorders > 16 (2024) Titre : Behavioural and neurodevelopmental characteristics of SYNGAP1 Type de document : texte imprimé Auteurs : Nadja BEDNARCZUK, Auteur ; Harriet HOUSBY, Auteur ; Irene O. LEE, Auteur ; Imagine CONSORTIUM, Auteur ; David SKUSE, Auteur ; Jeanne WOLSTENCROFT, Auteur Langues : Anglais (eng) Mots-clés : Humans  Female  ras GTPase-Activating Proteins/genetics  Male  Child  Adolescent  Child, Preschool  Intellectual Disability/genetics/etiology  Developmental Disabilities/genetics/etiology  United Kingdom  Neurodevelopmental Disorders/genetics  Cohort Studies  Phenotype  Epilepsy/genetics  Seizures/genetics  Autism  Behaviour  Intellectual Disability  Neurodevelopment  Syngap1 Index. décimale : PER Périodiques Résumé : BACKGROUND: SYNGAP1 variants are associated with varying degrees of intellectual disability (ID), developmental delay (DD), epilepsy, autism, and behavioural difficulties. These features may also be observed in other monogenic conditions. There is a need to systematically compare the characteristics of SYNGAP1 with other monogenic causes of ID and DD to identify features unique to the SYNAGP1 phenotype. We aimed to contrast the neurodevelopmental and behavioural phenotype of children with SYNGAP1-related ID (SYNGAP1-ID) to children with other monogenic conditions and a matched degree of ID. METHODS: Participants were identified from the IMAGINE-ID study, a UK-based, national cohort study of neuropsychiatric risk in children with ID of known genetic origin. Thirteen children with SYNGAP1 variants (age 4-16 years; 85% female) were matched (2:1) with 26 controls with other monogenic causes of ID for chronological and mental age, sex, socio-economic deprivation, adaptive behaviour, and physical health difficulties. Caregivers completed the Development and Wellbeing Assessment (DAWBA) and physical health questionnaires. RESULTS: Our results demonstrate that seizures affected children with SYNGAP1-ID (84.6%) more frequently than the ID-comparison group (7.6%; p = < 0.001). Fine-motor development was disproportionally impaired in SYNGAP1-ID, with 92.3% of children experiencing difficulties compared to 50% of ID-comparisons(p = 0.03). Gross motor and social development did not differ between the two groups. Children with SYNGAP1-ID were more likely to be non-verbal (61.5%) than ID-comparisons (23.1%; p = 0.01). Those children able to speak, spoke their first words at the same age as the ID-comparison group (mean = 3.25 years), yet achieved lower language competency (p = 0.04). Children with SYNGAP1-ID compared to the ID-comparison group were not more likely to meet criteria for autism (SYNGAP1-ID = 46.2%; ID-comparison = 30.7%; p = .35), attention-deficit hyperactivity disorder (15.4%;15.4%; p = 1), generalised anxiety (7.7%;15.4%; p = .49) or oppositional defiant disorder (7.7%;0%; p = .15). CONCLUSION: For the first time, we demonstrate that SYNGAP1-ID is associated with fine motor and language difficulties beyond those experienced by children with other genetic causes of DD and ID. Targeted occupational and speech and language therapies should be incorporated early into SYNGAP1-ID management. En ligne : https://dx.doi.org/10.1186/s11689-024-09563-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=575 [article] Behavioural and neurodevelopmental characteristics of SYNGAP1 [texte imprimé] / Nadja BEDNARCZUK, Auteur ; Harriet HOUSBY, Auteur ; Irene O. LEE, Auteur ; Imagine CONSORTIUM, Auteur ; David SKUSE, Auteur ; Jeanne WOLSTENCROFT, Auteur. Langues : Anglais (eng) in Journal of Neurodevelopmental Disorders > 16 (2024) Mots-clés : Humans  Female  ras GTPase-Activating Proteins/genetics  Male  Child  Adolescent  Child, Preschool  Intellectual Disability/genetics/etiology  Developmental Disabilities/genetics/etiology  United Kingdom  Neurodevelopmental Disorders/genetics  Cohort Studies  Phenotype  Epilepsy/genetics  Seizures/genetics  Autism  Behaviour  Intellectual Disability  Neurodevelopment  Syngap1 Index. décimale : PER Périodiques Résumé : BACKGROUND: SYNGAP1 variants are associated with varying degrees of intellectual disability (ID), developmental delay (DD), epilepsy, autism, and behavioural difficulties. These features may also be observed in other monogenic conditions. There is a need to systematically compare the characteristics of SYNGAP1 with other monogenic causes of ID and DD to identify features unique to the SYNAGP1 phenotype. We aimed to contrast the neurodevelopmental and behavioural phenotype of children with SYNGAP1-related ID (SYNGAP1-ID) to children with other monogenic conditions and a matched degree of ID. METHODS: Participants were identified from the IMAGINE-ID study, a UK-based, national cohort study of neuropsychiatric risk in children with ID of known genetic origin. Thirteen children with SYNGAP1 variants (age 4-16 years; 85% female) were matched (2:1) with 26 controls with other monogenic causes of ID for chronological and mental age, sex, socio-economic deprivation, adaptive behaviour, and physical health difficulties. Caregivers completed the Development and Wellbeing Assessment (DAWBA) and physical health questionnaires. RESULTS: Our results demonstrate that seizures affected children with SYNGAP1-ID (84.6%) more frequently than the ID-comparison group (7.6%; p = < 0.001). Fine-motor development was disproportionally impaired in SYNGAP1-ID, with 92.3% of children experiencing difficulties compared to 50% of ID-comparisons(p = 0.03). Gross motor and social development did not differ between the two groups. Children with SYNGAP1-ID were more likely to be non-verbal (61.5%) than ID-comparisons (23.1%; p = 0.01). Those children able to speak, spoke their first words at the same age as the ID-comparison group (mean = 3.25 years), yet achieved lower language competency (p = 0.04). Children with SYNGAP1-ID compared to the ID-comparison group were not more likely to meet criteria for autism (SYNGAP1-ID = 46.2%; ID-comparison = 30.7%; p = .35), attention-deficit hyperactivity disorder (15.4%;15.4%; p = 1), generalised anxiety (7.7%;15.4%; p = .49) or oppositional defiant disorder (7.7%;0%; p = .15). CONCLUSION: For the first time, we demonstrate that SYNGAP1-ID is associated with fine motor and language difficulties beyond those experienced by children with other genetic causes of DD and ID. Targeted occupational and speech and language therapies should be incorporated early into SYNGAP1-ID management. En ligne : https://dx.doi.org/10.1186/s11689-024-09563-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=575

Detecting Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder Using Multimodal Time-Frequency Analysis with Machine Learning Using the Electroretinogram from Two Flash Strengths / Sultan Mohammad MANJUR in Journal of Autism and Developmental Disorders, 55-4 (April 2024)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 55-4 (April 2024) . - p.1365-1378 Titre : Detecting Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder Using Multimodal Time-Frequency Analysis with Machine Learning Using the Electroretinogram from Two Flash Strengths Type de document : texte imprimé Auteurs : Sultan Mohammad MANJUR, Auteur ; Luis Roberto Mercado DIAZ, Auteur ; Irene O. LEE, Auteur ; David H. SKUSE, Auteur ; Dorothy A. THOMPSON, Auteur ; Fernando MARMOLEJO-RAMOS, Auteur ; Paul A. CONSTABLE, Auteur ; Hugo F. POSADA-QUINTERO, Auteur Article en page(s) : p.1365-1378 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are conditions that similarly alter cognitive functioning ability and challenge the social interaction, attention, and communication skills of affected individuals. Yet these are distinct neurological conditions that can exhibit diverse characteristics which require different management strategies. It is desirable to develop tools to assist with early distinction so that appropriate early interventions and support may be tailored to an individual?s specific requirements. The current diagnostic procedures for ASD and ADHD require a multidisciplinary approach and can be lengthy. This study investigated the potential of electroretinogram (ERG), an eye test measuring retinal responses to light, for rapid screening of ASD and ADHD. Methods: Previous studies identified differences in ERG amplitude between ASD and ADHD, but this study explored time-frequency analysis (TFS) to capture dynamic changes in the signal. ERG data from 286 subjects (146 control, 94 ASD, 46 ADHD) was analyzed using two TFS techniques. Results: Key features were selected, and machine learning models were trained to classify individuals based on their ERG response. The best model achieved 70% overall accuracy in distinguishing control, ASD, and ADHD groups. Conclusion: The ERG to the stronger flash strength provided better separation and the high frequency dynamics (80-300 Hz) were more informative features than lower frequency components. To further improve classification a greater number of different flash strengths may be required along with a discrimination comparison to participants who meet both ASD and ADHD classifications and carry both diagnoses. En ligne : https://doi.org/10.1007/s10803-024-06290-w Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=550 [article] Detecting Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder Using Multimodal Time-Frequency Analysis with Machine Learning Using the Electroretinogram from Two Flash Strengths [texte imprimé] / Sultan Mohammad MANJUR, Auteur ; Luis Roberto Mercado DIAZ, Auteur ; Irene O. LEE, Auteur ; David H. SKUSE, Auteur ; Dorothy A. THOMPSON, Auteur ; Fernando MARMOLEJO-RAMOS, Auteur ; Paul A. CONSTABLE, Auteur ; Hugo F. POSADA-QUINTERO, Auteur . - p.1365-1378. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 55-4 (April 2024) . - p.1365-1378 Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are conditions that similarly alter cognitive functioning ability and challenge the social interaction, attention, and communication skills of affected individuals. Yet these are distinct neurological conditions that can exhibit diverse characteristics which require different management strategies. It is desirable to develop tools to assist with early distinction so that appropriate early interventions and support may be tailored to an individual?s specific requirements. The current diagnostic procedures for ASD and ADHD require a multidisciplinary approach and can be lengthy. This study investigated the potential of electroretinogram (ERG), an eye test measuring retinal responses to light, for rapid screening of ASD and ADHD. Methods: Previous studies identified differences in ERG amplitude between ASD and ADHD, but this study explored time-frequency analysis (TFS) to capture dynamic changes in the signal. ERG data from 286 subjects (146 control, 94 ASD, 46 ADHD) was analyzed using two TFS techniques. Results: Key features were selected, and machine learning models were trained to classify individuals based on their ERG response. The best model achieved 70% overall accuracy in distinguishing control, ASD, and ADHD groups. Conclusion: The ERG to the stronger flash strength provided better separation and the high frequency dynamics (80-300 Hz) were more informative features than lower frequency components. To further improve classification a greater number of different flash strengths may be required along with a discrimination comparison to participants who meet both ASD and ADHD classifications and carry both diagnoses. En ligne : https://doi.org/10.1007/s10803-024-06290-w Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=550

Evaluating social (pragmatic) communication disorder / William MANDY in Journal of Child Psychology and Psychiatry, 58-10 (October 2017)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 58-10 (October 2017) . - p.1166-1175 Titre : Evaluating social (pragmatic) communication disorder Type de document : texte imprimé Auteurs : William MANDY, Auteur ; Adele WANG, Auteur ; Irene O. LEE, Auteur ; David SKUSE, Auteur Article en page(s) : p.1166-1175 Langues : Anglais (eng) Mots-clés : Social (pragmatic) communication disorder  autism spectrum disorder  diagnostic and statistical manual  fifth edition (DSM-5)  pervasive developmental disorder – not otherwise specified  nosology Index. décimale : PER Périodiques Résumé : Background Social (pragmatic) communication disorder (SPCD) is a new diagnosis introduced by DSM-5, characterised by problems with verbal and nonverbal social communication. It is currently unclear whether SPCD is a valid diagnostic category, because little is known about the characteristics of those who meet its criteria. We sought to identify and describe cases of SPCD, to contribute to debates about its validity. We investigated whether the symptoms of SPCD cluster together to form a coherent syndrome that is distinct from autism spectrum disorder (ASD) in terms of its core and associated features. Methods Participants were young people (N = 1,081, age range = 4–18 years) who had attended a specialist social communication disorders clinic for children with fluent language and normal-range intelligence. Standardised parent-report data were collected using the Developmental, Dimensional and Diagnostic Interview (3Di), Child Communication Checklist (CCC) and Strengths and Difficulties Questionnaire (SDQ). An algorithm was designed using 3Di and CCC items to implement DSM-5 SPCD criteria. Results Eighty-eight young people met our criteria for SPCD, with 801 meeting DSM-5 ASD criteria and the remaining 192 having neither SPCD nor ASD (‘clinical comparison group’). The core symptoms of SPCD co-occurred to a moderate degree (average interitem correlation = .22). SPCD cases had autistic social difficulties that were intermediate between ASD and the clinical comparison group. SPCD was associated with high rates of nonautistic psychopathology, with 63.5% scoring in the abnormal range of the SDQ's Total Problems scale. Conclusions We did not find evidence that SPCD is qualitatively distinct from ASD. Rather, it appears to lie on the borderlands of the autism spectrum, describing those with autistic traits that fall just below the threshold for an ASD diagnosis. SPCD may have clinical utility for identifying people with autistic traits that are insufficiently severe for ASD diagnosis, but who nevertheless require support. En ligne : http://dx.doi.org/10.1111/jcpp.12785 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=321 [article] Evaluating social (pragmatic) communication disorder [texte imprimé] / William MANDY, Auteur ; Adele WANG, Auteur ; Irene O. LEE, Auteur ; David SKUSE, Auteur . - p.1166-1175. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 58-10 (October 2017) . - p.1166-1175 Mots-clés : Social (pragmatic) communication disorder  autism spectrum disorder  diagnostic and statistical manual  fifth edition (DSM-5)  pervasive developmental disorder – not otherwise specified  nosology Index. décimale : PER Périodiques Résumé : Background Social (pragmatic) communication disorder (SPCD) is a new diagnosis introduced by DSM-5, characterised by problems with verbal and nonverbal social communication. It is currently unclear whether SPCD is a valid diagnostic category, because little is known about the characteristics of those who meet its criteria. We sought to identify and describe cases of SPCD, to contribute to debates about its validity. We investigated whether the symptoms of SPCD cluster together to form a coherent syndrome that is distinct from autism spectrum disorder (ASD) in terms of its core and associated features. Methods Participants were young people (N = 1,081, age range = 4–18 years) who had attended a specialist social communication disorders clinic for children with fluent language and normal-range intelligence. Standardised parent-report data were collected using the Developmental, Dimensional and Diagnostic Interview (3Di), Child Communication Checklist (CCC) and Strengths and Difficulties Questionnaire (SDQ). An algorithm was designed using 3Di and CCC items to implement DSM-5 SPCD criteria. Results Eighty-eight young people met our criteria for SPCD, with 801 meeting DSM-5 ASD criteria and the remaining 192 having neither SPCD nor ASD (‘clinical comparison group’). The core symptoms of SPCD co-occurred to a moderate degree (average interitem correlation = .22). SPCD cases had autistic social difficulties that were intermediate between ASD and the clinical comparison group. SPCD was associated with high rates of nonautistic psychopathology, with 63.5% scoring in the abnormal range of the SDQ's Total Problems scale. Conclusions We did not find evidence that SPCD is qualitatively distinct from ASD. Rather, it appears to lie on the borderlands of the autism spectrum, describing those with autistic traits that fall just below the threshold for an ASD diagnosis. SPCD may have clinical utility for identifying people with autistic traits that are insufficiently severe for ASD diagnosis, but who nevertheless require support. En ligne : http://dx.doi.org/10.1111/jcpp.12785 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=321

Light-Adapted Electroretinogram Differences in Autism Spectrum Disorder / Paul A. CONSTABLE in Journal of Autism and Developmental Disorders, 50-8 (August 2020)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 50-8 (August 2020) . - p.2874-2885 Titre : Light-Adapted Electroretinogram Differences in Autism Spectrum Disorder Type de document : texte imprimé Auteurs : Paul A. CONSTABLE, Auteur ; Edward R. RITVO, Auteur ; Ariella R. RITVO, Auteur ; Irene O. LEE, Auteur ; Morgan L. MCNAIR, Auteur ; Dylan STAHL, Auteur ; Jane SOWDEN, Auteur ; Stephen QUINN, Auteur ; David H. SKUSE, Auteur ; Dorothy A. THOMPSON, Auteur ; James C. MCPARTLAND, Auteur Article en page(s) : p.2874-2885 Langues : Anglais (eng) Mots-clés : Autism spectrum disorder  Electroretinogram  b-wave Index. décimale : PER Périodiques Résumé : Light-adapted (LA) electroretinograms (ERGs) from 90 individuals with autism spectrum disorder (ASD), mean age (13.0 ± 4.2), were compared to 87 control subjects, mean age (13.8 ± 4.8). LA-ERGs were produced by a random series of nine different Troland based, full-field flash strengths and the ISCEV standard flash at 2/s on a 30 cd m(-2) white background. A random effects mixed model analysis showed the ASD group had smaller b- and a-wave amplitudes at high flash strengths (p < .001) and slower b-wave peak times (p < .001). Photopic hill models showed the peaks of the component Gaussian (p = .035) and logistic functions (p = .014) differed significantly between groups. Retinal neurophysiology assessed by LA-ERG provides insight into neural development in ASD. En ligne : http://dx.doi.org/10.1007/s10803-020-04396-5 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=428 [article] Light-Adapted Electroretinogram Differences in Autism Spectrum Disorder [texte imprimé] / Paul A. CONSTABLE, Auteur ; Edward R. RITVO, Auteur ; Ariella R. RITVO, Auteur ; Irene O. LEE, Auteur ; Morgan L. MCNAIR, Auteur ; Dylan STAHL, Auteur ; Jane SOWDEN, Auteur ; Stephen QUINN, Auteur ; David H. SKUSE, Auteur ; Dorothy A. THOMPSON, Auteur ; James C. MCPARTLAND, Auteur . - p.2874-2885. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 50-8 (August 2020) . - p.2874-2885 Mots-clés : Autism spectrum disorder  Electroretinogram  b-wave Index. décimale : PER Périodiques Résumé : Light-adapted (LA) electroretinograms (ERGs) from 90 individuals with autism spectrum disorder (ASD), mean age (13.0 ± 4.2), were compared to 87 control subjects, mean age (13.8 ± 4.8). LA-ERGs were produced by a random series of nine different Troland based, full-field flash strengths and the ISCEV standard flash at 2/s on a 30 cd m(-2) white background. A random effects mixed model analysis showed the ASD group had smaller b- and a-wave amplitudes at high flash strengths (p < .001) and slower b-wave peak times (p < .001). Photopic hill models showed the peaks of the component Gaussian (p = .035) and logistic functions (p = .014) differed significantly between groups. Retinal neurophysiology assessed by LA-ERG provides insight into neural development in ASD. En ligne : http://dx.doi.org/10.1007/s10803-020-04396-5 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=428

The electroretinogram b-wave amplitude: a differential physiological measure for Attention Deficit Hyperactivity Disorder and Autism Spectrum Disorder / Irene O. LEE in Journal of Neurodevelopmental Disorders, 14 (2022)  

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