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88 recherche sur le mot-clé 'Eeg'




EEG data collection in children with ASD: The role of state in data quality and spectral power / Charlotte DISTEFANO in Research in Autism Spectrum Disorders, 57 (January 2019)
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[article]
Titre : EEG data collection in children with ASD: The role of state in data quality and spectral power Type de document : Texte imprimé et/ou numérique Auteurs : Charlotte DISTEFANO, Auteur ; Abigail DICKINSON, Auteur ; Elizabeth BAKER, Auteur ; Shafali SPURLING JESTE, Auteur Article en page(s) : p.132-144 Langues : Anglais (eng) Mots-clés : Autism spectrum disorder Intellectual disability EEG Spectral power Index. décimale : PER Périodiques Résumé : Background Electroencephalography can elucidate neurobiological mechanisms underlying heterogeneity in ASD. Studying the full range of children with ASD introduces methodological challenges stemming from participants’ difficulties tolerating the data collection process, leading to diminished EEG data retention and increased variability in participant ‘state’ during the recording. Quantifying state will improve data collection methods and aide in interpreting results. Objectives Observationally quantify participant state during the EEG recording; examine its relationship to child characteristics, data retention and spectral power. Methods Participants included 5–11 year-old children with ASD (N?=?39) and age-matched TD children (N?=?16). Participants were acclimated to the EEG environment using behavioral strategies. EEG was recorded while participants watched a video of bubbles. Participant ‘state’ was rated using a Likert scale (Perceived State Rating: PSR). Results Participants with ASD had more elevated PSR than TD participants. Less EEG data were retained in participants with higher PSR scores, but this was not related to age or IQ. TD participants had higher alpha power compared with the ASD group. Within the ASD group, participants with high PSR had decreased frontal alpha power. Conclusions Given supportive strategies, EEG data was collected from children with ASD across cognitive levels. Participant state influenced both EEG data retention and alpha spectral power. Alpha suppression is linked to attention and vigilance, suggesting that these participants were less ‘at rest’. This highlights the importance of considering state when conducting EEG studies with challenging participants, both to increase data retention rates and to quantify the influence of state on EEG variables. En ligne : https://doi.org/10.1016/j.rasd.2018.10.001 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=371
in Research in Autism Spectrum Disorders > 57 (January 2019) . - p.132-144[article] EEG data collection in children with ASD: The role of state in data quality and spectral power [Texte imprimé et/ou numérique] / Charlotte DISTEFANO, Auteur ; Abigail DICKINSON, Auteur ; Elizabeth BAKER, Auteur ; Shafali SPURLING JESTE, Auteur . - p.132-144.
Langues : Anglais (eng)
in Research in Autism Spectrum Disorders > 57 (January 2019) . - p.132-144
Mots-clés : Autism spectrum disorder Intellectual disability EEG Spectral power Index. décimale : PER Périodiques Résumé : Background Electroencephalography can elucidate neurobiological mechanisms underlying heterogeneity in ASD. Studying the full range of children with ASD introduces methodological challenges stemming from participants’ difficulties tolerating the data collection process, leading to diminished EEG data retention and increased variability in participant ‘state’ during the recording. Quantifying state will improve data collection methods and aide in interpreting results. Objectives Observationally quantify participant state during the EEG recording; examine its relationship to child characteristics, data retention and spectral power. Methods Participants included 5–11 year-old children with ASD (N?=?39) and age-matched TD children (N?=?16). Participants were acclimated to the EEG environment using behavioral strategies. EEG was recorded while participants watched a video of bubbles. Participant ‘state’ was rated using a Likert scale (Perceived State Rating: PSR). Results Participants with ASD had more elevated PSR than TD participants. Less EEG data were retained in participants with higher PSR scores, but this was not related to age or IQ. TD participants had higher alpha power compared with the ASD group. Within the ASD group, participants with high PSR had decreased frontal alpha power. Conclusions Given supportive strategies, EEG data was collected from children with ASD across cognitive levels. Participant state influenced both EEG data retention and alpha spectral power. Alpha suppression is linked to attention and vigilance, suggesting that these participants were less ‘at rest’. This highlights the importance of considering state when conducting EEG studies with challenging participants, both to increase data retention rates and to quantify the influence of state on EEG variables. En ligne : https://doi.org/10.1016/j.rasd.2018.10.001 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=371 EEG hyper-connectivity in high-risk infants is associated with later autism / Elena V. OREKHOVA in Journal of Neurodevelopmental Disorders, 6-1 (December 2014)
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Titre : EEG hyper-connectivity in high-risk infants is associated with later autism Type de document : Texte imprimé et/ou numérique Auteurs : Elena V. OREKHOVA, Auteur ; M. ELSABBAGH, Auteur ; E. J. JONES, Auteur ; G. DAWSON, Auteur ; Tony CHARMAN, Auteur ; M. H. JOHNSON, Auteur Article en page(s) : p.40 Langues : Anglais (eng) Mots-clés : Alpha Autism spectrum disorders Connectivity Eeg Infants Siblings Index. décimale : PER Périodiques Résumé : BACKGROUND: It has been previously reported that structural and functional brain connectivity in individuals with autism spectrum disorders (ASD) is atypical and may vary with age. However, to date, no measures of functional connectivity measured within the first 2 years have specifically associated with a later ASD diagnosis. METHODS: In the present study, we analyzed functional brain connectivity in 14-month-old infants at high and low familial risk for ASD using electroencephalography (EEG). EEG was recorded while infants attended to videos. Connectivity was assessed using debiased weighted phase lag index (dbWPLI). At 36 months, the high-risk infants were assessed for symptoms of ASD. RESULTS: As a group, high-risk infants who were later diagnosed with ASD demonstrated elevated phase-lagged alpha-range connectivity as compared to both low-risk infants and high-risk infants who did not go on to ASD. Hyper-connectivity was most prominent over frontal and central areas. The degree of hyper-connectivity at 14 months strongly correlated with the severity of restricted and repetitive behaviors in participants with ASD at 3 years. These effects were not attributable to differences in behavior during the EEG session or to differences in spectral power. CONCLUSIONS: The results suggest that early hyper-connectivity in the alpha frequency range is an important feature of the ASD neurophysiological phenotype. En ligne : http://dx.doi.org/10.1186/1866-1955-6-40 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=347
in Journal of Neurodevelopmental Disorders > 6-1 (December 2014) . - p.40[article] EEG hyper-connectivity in high-risk infants is associated with later autism [Texte imprimé et/ou numérique] / Elena V. OREKHOVA, Auteur ; M. ELSABBAGH, Auteur ; E. J. JONES, Auteur ; G. DAWSON, Auteur ; Tony CHARMAN, Auteur ; M. H. JOHNSON, Auteur . - p.40.
Langues : Anglais (eng)
in Journal of Neurodevelopmental Disorders > 6-1 (December 2014) . - p.40
Mots-clés : Alpha Autism spectrum disorders Connectivity Eeg Infants Siblings Index. décimale : PER Périodiques Résumé : BACKGROUND: It has been previously reported that structural and functional brain connectivity in individuals with autism spectrum disorders (ASD) is atypical and may vary with age. However, to date, no measures of functional connectivity measured within the first 2 years have specifically associated with a later ASD diagnosis. METHODS: In the present study, we analyzed functional brain connectivity in 14-month-old infants at high and low familial risk for ASD using electroencephalography (EEG). EEG was recorded while infants attended to videos. Connectivity was assessed using debiased weighted phase lag index (dbWPLI). At 36 months, the high-risk infants were assessed for symptoms of ASD. RESULTS: As a group, high-risk infants who were later diagnosed with ASD demonstrated elevated phase-lagged alpha-range connectivity as compared to both low-risk infants and high-risk infants who did not go on to ASD. Hyper-connectivity was most prominent over frontal and central areas. The degree of hyper-connectivity at 14 months strongly correlated with the severity of restricted and repetitive behaviors in participants with ASD at 3 years. These effects were not attributable to differences in behavior during the EEG session or to differences in spectral power. CONCLUSIONS: The results suggest that early hyper-connectivity in the alpha frequency range is an important feature of the ASD neurophysiological phenotype. En ligne : http://dx.doi.org/10.1186/1866-1955-6-40 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=347 EEG spectral characteristics and asymmetry in pre-school children with autism in awake and sleep stages / Sowmyashree Mayur KAKU ; Anoop JOSEPH ; Manjula William JAMES ; Gosala R. K. SARMA ; Ashok MYSORE ; Shyam Sundar RAJAGOPALAN in Research in Autism, 121-122 (March-April 2025)
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Titre : EEG spectral characteristics and asymmetry in pre-school children with autism in awake and sleep stages Type de document : Texte imprimé et/ou numérique Auteurs : Sowmyashree Mayur KAKU, Auteur ; Anoop JOSEPH, Auteur ; Manjula William JAMES, Auteur ; Gosala R. K. SARMA, Auteur ; Ashok MYSORE, Auteur ; Shyam Sundar RAJAGOPALAN, Auteur Article en page(s) : 202538 Langues : Anglais (eng) Mots-clés : Autism Preschool Electroencephalogram EEG NREM Sleep stage Asymmetry Power spectral density Band power Index. décimale : PER Périodiques Résumé : Background Autism spectrum disorder (ASD) is a complex-heterogeneous neurodevelopmental disorder manifesting as abnormalities in social communication and repetitive behaviors, generally observed from early childhood. These syndromic behaviors have neurophysiological basis which stems from altered activations of cortical structures in the pathways of functional neural networks and regulatory mechanisms. Frequency bands of Electroencephalography (EEG) have functional and topographical significance expressed through computed parameters like band power and asymmetry index. Previous studies have mapped these parameters to ASD symptoms, limited to select cortical locations, bands and restricted study conditions in either passive awake or selected sleep stage. Methods Spontaneous EEG recorded from two clinically diagnosed groups of preschoolers, ASD and non-ASD in awake and 3 stages of Non-Rapid Eye Movement (NREM) sleep (N1-N3) was decomposed into 8 frequency bands spanning 0.5-24 Hz. Band powers were computed for 60 channels and hemispheric asymmetry index (AI) for 12 regions covering the entire scalp. Results We found awake alpha with N1 slow and fast theta powers significantly lower for ASD. N1 fast beta power was higher in ASD. Sleep AI exhibited significant dominance with both groups displaying congruent orientation in N1 and contralateral in N2 and N3. ASD showed lower AI in N1 and N3 with higher AI in N2. Conclusion Cyclical states of awake and sleep often tend to project their mental processes from one onto another making a use case for our pervasive approach. This pilot study highlights the need to include EEG spectral parameters into the heterogeneous relationship of awake/sleep states mentation, neuropsychology and ASD symptoms. En ligne : https://doi.org/10.1016/j.reia.2025.202538 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=555
in Research in Autism > 121-122 (March-April 2025) . - 202538[article] EEG spectral characteristics and asymmetry in pre-school children with autism in awake and sleep stages [Texte imprimé et/ou numérique] / Sowmyashree Mayur KAKU, Auteur ; Anoop JOSEPH, Auteur ; Manjula William JAMES, Auteur ; Gosala R. K. SARMA, Auteur ; Ashok MYSORE, Auteur ; Shyam Sundar RAJAGOPALAN, Auteur . - 202538.
Langues : Anglais (eng)
in Research in Autism > 121-122 (March-April 2025) . - 202538
Mots-clés : Autism Preschool Electroencephalogram EEG NREM Sleep stage Asymmetry Power spectral density Band power Index. décimale : PER Périodiques Résumé : Background Autism spectrum disorder (ASD) is a complex-heterogeneous neurodevelopmental disorder manifesting as abnormalities in social communication and repetitive behaviors, generally observed from early childhood. These syndromic behaviors have neurophysiological basis which stems from altered activations of cortical structures in the pathways of functional neural networks and regulatory mechanisms. Frequency bands of Electroencephalography (EEG) have functional and topographical significance expressed through computed parameters like band power and asymmetry index. Previous studies have mapped these parameters to ASD symptoms, limited to select cortical locations, bands and restricted study conditions in either passive awake or selected sleep stage. Methods Spontaneous EEG recorded from two clinically diagnosed groups of preschoolers, ASD and non-ASD in awake and 3 stages of Non-Rapid Eye Movement (NREM) sleep (N1-N3) was decomposed into 8 frequency bands spanning 0.5-24 Hz. Band powers were computed for 60 channels and hemispheric asymmetry index (AI) for 12 regions covering the entire scalp. Results We found awake alpha with N1 slow and fast theta powers significantly lower for ASD. N1 fast beta power was higher in ASD. Sleep AI exhibited significant dominance with both groups displaying congruent orientation in N1 and contralateral in N2 and N3. ASD showed lower AI in N1 and N3 with higher AI in N2. Conclusion Cyclical states of awake and sleep often tend to project their mental processes from one onto another making a use case for our pervasive approach. This pilot study highlights the need to include EEG spectral parameters into the heterogeneous relationship of awake/sleep states mentation, neuropsychology and ASD symptoms. En ligne : https://doi.org/10.1016/j.reia.2025.202538 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=555 EEG Spectral Features in Sleep of Autism Spectrum Disorders in Children with Tuberous Sclerosis Complex / Ian COOK in Journal of Autism and Developmental Disorders, 50-3 (March 2020)
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Titre : EEG Spectral Features in Sleep of Autism Spectrum Disorders in Children with Tuberous Sclerosis Complex Type de document : Texte imprimé et/ou numérique Auteurs : Ian COOK, Auteur ; Andrew C. WILSON, Auteur ; Jurriaan M. PETERS, Auteur ; Monisha N. GOYAL, Auteur ; E. Martina BEBIN, Auteur ; Hope NORTHRUP, Auteur ; Darcy KRUEGER, Auteur ; Andrew F. LEUCHTER, Auteur ; Mustafa SAHIN, Auteur Article en page(s) : p.916-923 Langues : Anglais (eng) Mots-clés : Autism Biomarkers Eeg Tsc Index. décimale : PER Périodiques Résumé : Tuberous sclerosis complex (TSC) is a multisystem disorder with increased prevalence of autism spectrum disorders (ASDs). This project aimed to characterize the autism phenotype of TSC and identify biomarkers of risk for ASD. Because abnormalities of EEG during sleep are tied to neurodevelopment in children, we compared electroencephalographic (EEG) measures during Stage II sleep in TSC children who either did (ASD+) or did not (ASD-) exhibit symptoms of ASD over 36-month follow up. Relative alpha band power was significantly elevated in the ASD+ group at 24 months of age with smaller differences at younger ages, suggesting this may arise from differences in brain development. These findings suggest that EEG features could enhance the detection of risk for ASD. En ligne : http://dx.doi.org/10.1007/s10803-019-04326-0 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=419
in Journal of Autism and Developmental Disorders > 50-3 (March 2020) . - p.916-923[article] EEG Spectral Features in Sleep of Autism Spectrum Disorders in Children with Tuberous Sclerosis Complex [Texte imprimé et/ou numérique] / Ian COOK, Auteur ; Andrew C. WILSON, Auteur ; Jurriaan M. PETERS, Auteur ; Monisha N. GOYAL, Auteur ; E. Martina BEBIN, Auteur ; Hope NORTHRUP, Auteur ; Darcy KRUEGER, Auteur ; Andrew F. LEUCHTER, Auteur ; Mustafa SAHIN, Auteur . - p.916-923.
Langues : Anglais (eng)
in Journal of Autism and Developmental Disorders > 50-3 (March 2020) . - p.916-923
Mots-clés : Autism Biomarkers Eeg Tsc Index. décimale : PER Périodiques Résumé : Tuberous sclerosis complex (TSC) is a multisystem disorder with increased prevalence of autism spectrum disorders (ASDs). This project aimed to characterize the autism phenotype of TSC and identify biomarkers of risk for ASD. Because abnormalities of EEG during sleep are tied to neurodevelopment in children, we compared electroencephalographic (EEG) measures during Stage II sleep in TSC children who either did (ASD+) or did not (ASD-) exhibit symptoms of ASD over 36-month follow up. Relative alpha band power was significantly elevated in the ASD+ group at 24 months of age with smaller differences at younger ages, suggesting this may arise from differences in brain development. These findings suggest that EEG features could enhance the detection of risk for ASD. En ligne : http://dx.doi.org/10.1007/s10803-019-04326-0 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=419 Correlations between EEG abnormalities and clinical phenotypes in a population of children with autism spectrum disorder / Mario BRINCIOTTI ; Federica GIOVANNONE ; Francesco PISANI ; Marco TOFANI ; Carla SOGOS in Research in Autism, 123 (May 2025)
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Titre : Correlations between EEG abnormalities and clinical phenotypes in a population of children with autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Mario BRINCIOTTI, Auteur ; Federica GIOVANNONE, Auteur ; Francesco PISANI, Auteur ; Marco TOFANI, Auteur ; Carla SOGOS, Auteur Article en page(s) : 202536 Langues : Anglais (eng) Mots-clés : Autism EEG Sex differences EEG abnormalities Mirror neurons system Index. décimale : PER Périodiques Résumé : Purpose EEG abnormalities (EA) have recently been proposed as a way to understand the pathophysiology of the Autism Spectrum Disorder (ASD). The present study aims to determine whether there are peculiar correlations between EA in autistic patients and clinical phenotypes. Method We collected information about patient's past medical and developmental history and investigated clinical phenotypes using the observation and standardized instruments in a cohort of 111 outpatients with ASD or at risk for ASD. Then we proceeded to investigate the association between EA and phenotypic characteristics. Results In our cohort we found a significant frequency (90%) of moderate/severe autism spectrum symptoms (corroborated by results from standardized tests, such as ADOS-2). Epileptiform EA detected in our sample were mainly focal, with a predominantly left fronto-central temporal region localization. Generalized or widespread epileptiform EA during sleep EEG was significantly correlated with non-verbal profile, greater impairment in terms of social interaction, and higher ADI-R scores in the communication and language scale. Conclusion In the current study, the presence of widespread epileptiform EA correlates with a more severe clinical presentation, in particular with a non-verbal profile and impairment in social interaction. The prevalent detection of focal EEA in the left fronto-central temporal region could demonstrate the hypothesis of dysfunction of the mirror neuron system and Wernicke?s area. However, it is necessary to understand if EA may be considered an epiphenomenon of the underlying neural dysfunction or whether there is a causal relationship with the autism phenotypes. En ligne : https://doi.org/10.1016/j.reia.2025.202536 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=555
in Research in Autism > 123 (May 2025) . - 202536[article] Correlations between EEG abnormalities and clinical phenotypes in a population of children with autism spectrum disorder [Texte imprimé et/ou numérique] / Mario BRINCIOTTI, Auteur ; Federica GIOVANNONE, Auteur ; Francesco PISANI, Auteur ; Marco TOFANI, Auteur ; Carla SOGOS, Auteur . - 202536.
Langues : Anglais (eng)
in Research in Autism > 123 (May 2025) . - 202536
Mots-clés : Autism EEG Sex differences EEG abnormalities Mirror neurons system Index. décimale : PER Périodiques Résumé : Purpose EEG abnormalities (EA) have recently been proposed as a way to understand the pathophysiology of the Autism Spectrum Disorder (ASD). The present study aims to determine whether there are peculiar correlations between EA in autistic patients and clinical phenotypes. Method We collected information about patient's past medical and developmental history and investigated clinical phenotypes using the observation and standardized instruments in a cohort of 111 outpatients with ASD or at risk for ASD. Then we proceeded to investigate the association between EA and phenotypic characteristics. Results In our cohort we found a significant frequency (90%) of moderate/severe autism spectrum symptoms (corroborated by results from standardized tests, such as ADOS-2). Epileptiform EA detected in our sample were mainly focal, with a predominantly left fronto-central temporal region localization. Generalized or widespread epileptiform EA during sleep EEG was significantly correlated with non-verbal profile, greater impairment in terms of social interaction, and higher ADI-R scores in the communication and language scale. Conclusion In the current study, the presence of widespread epileptiform EA correlates with a more severe clinical presentation, in particular with a non-verbal profile and impairment in social interaction. The prevalent detection of focal EEA in the left fronto-central temporal region could demonstrate the hypothesis of dysfunction of the mirror neuron system and Wernicke?s area. However, it is necessary to understand if EA may be considered an epiphenomenon of the underlying neural dysfunction or whether there is a causal relationship with the autism phenotypes. En ligne : https://doi.org/10.1016/j.reia.2025.202536 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=555 Abnormal coherence and sleep composition in children with Angelman syndrome: a retrospective EEG study / H. DEN BAKKER in Molecular Autism, 9 (2018)
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PermalinkAtypical Pattern of Frontal EEG Asymmetry for Direct Gaze in Young Children with Autism Spectrum Disorder / J. LAUTTIA in Journal of Autism and Developmental Disorders, 49-9 (September 2019)
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PermalinkAuditory repetition suppression alterations in relation to cognitive functioning in fragile X syndrome: a combined EEG and machine learning approach / I. S. KNOTH in Journal of Neurodevelopmental Disorders, 10-1 (December 2018)
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PermalinkDelta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis / M. S. SIDOROV in Journal of Neurodevelopmental Disorders, 9-1 (December 2017)
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PermalinkEpilepsy and EEG Findings in Children with Autism Spectrum Disorders / Nashwa M. SAMRA in Autism - Open Access, 7-3 ([01/06/2017])
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