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Atypical brain network development of infants at elevated likelihood for autism spectrum disorder during the first year of life / Fen ZHANG in Autism Research, 15-12 (December 2022)
[article]
Titre : Atypical brain network development of infants at elevated likelihood for autism spectrum disorder during the first year of life Type de document : Texte imprimé et/ou numérique Auteurs : Fen ZHANG, Auteur ; Floor MOERMAN, Auteur ; Haijing NIU, Auteur ; Petra WARREYN, Auteur ; Herbert ROEYERS, Auteur Article en page(s) : p.2223-2237 Langues : Anglais (eng) Mots-clés : Infant Humans Autism Spectrum Disorder Neurodevelopmental Disorders Brain/diagnostic imaging Phenotype autism spectrum disorder brain network functional connectivity functional near-infrared spectroscopy neurodevelopmental disorder Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by behavioral features that appear early in life. Although studies have shown that atypical brain functional and structural connectivity are associated with these behavioral traits, the occurrence and initial alterations of brain networks have not been fully investigated. The current study aimed to map early brain network efficiency and information transferring in infants at elevated likelihood (EL) compared to infants at typical likelihood (TL) for ASD in the first year of life. This study used a resting-state functional near-infrared spectroscopy (fNIRS) approach to obtain the length and strength of functional connections in the frontal and temporal areas in 45 5-month-old and 38 10-month-old infants. Modular organization and small-world properties were detected in both EL and TL infants at 5 and 10Â months. In 5-month-old EL infants, local and nodal efficiency were significantly greater than age-matched TL infants, indicating overgrown local connections. Furthermore, we used a support vector machine (SVM) model to classify infants with or without EL based on the obtained global properties of the network, achieving an accuracy of 77.6%. These results suggest that infants with EL for ASD exhibit inefficiencies in the organization of brain networks during the first year of life. En ligne : http://dx.doi.org/10.1002/aur.2827 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=488
in Autism Research > 15-12 (December 2022) . - p.2223-2237[article] Atypical brain network development of infants at elevated likelihood for autism spectrum disorder during the first year of life [Texte imprimé et/ou numérique] / Fen ZHANG, Auteur ; Floor MOERMAN, Auteur ; Haijing NIU, Auteur ; Petra WARREYN, Auteur ; Herbert ROEYERS, Auteur . - p.2223-2237.
Langues : Anglais (eng)
in Autism Research > 15-12 (December 2022) . - p.2223-2237
Mots-clés : Infant Humans Autism Spectrum Disorder Neurodevelopmental Disorders Brain/diagnostic imaging Phenotype autism spectrum disorder brain network functional connectivity functional near-infrared spectroscopy neurodevelopmental disorder Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by behavioral features that appear early in life. Although studies have shown that atypical brain functional and structural connectivity are associated with these behavioral traits, the occurrence and initial alterations of brain networks have not been fully investigated. The current study aimed to map early brain network efficiency and information transferring in infants at elevated likelihood (EL) compared to infants at typical likelihood (TL) for ASD in the first year of life. This study used a resting-state functional near-infrared spectroscopy (fNIRS) approach to obtain the length and strength of functional connections in the frontal and temporal areas in 45 5-month-old and 38 10-month-old infants. Modular organization and small-world properties were detected in both EL and TL infants at 5 and 10Â months. In 5-month-old EL infants, local and nodal efficiency were significantly greater than age-matched TL infants, indicating overgrown local connections. Furthermore, we used a support vector machine (SVM) model to classify infants with or without EL based on the obtained global properties of the network, achieving an accuracy of 77.6%. These results suggest that infants with EL for ASD exhibit inefficiencies in the organization of brain networks during the first year of life. En ligne : http://dx.doi.org/10.1002/aur.2827 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=488 Alterations in hub organization in the white matter structural network in toddlers with autism spectrum disorder: A 2-year follow-up study / L. QIAN in Autism Research, 11-9 (September 2018)
[article]
Titre : Alterations in hub organization in the white matter structural network in toddlers with autism spectrum disorder: A 2-year follow-up study Type de document : Texte imprimé et/ou numérique Auteurs : L. QIAN, Auteur ; Y. WANG, Auteur ; K. CHU, Auteur ; Y. LI, Auteur ; C. XIAO, Auteur ; T. XIAO, Auteur ; X. XIAO, Auteur ; T. QIU, Auteur ; Y. XIAO, Auteur ; H. FANG, Auteur ; X. KE, Auteur Article en page(s) : p.1218-1228 Langues : Anglais (eng) Mots-clés : autism spectrum disorder brain network developmental trajectory hubs neuromechanism Index. décimale : PER Périodiques Résumé : Little is currently known about the longitudinal developmental patterns of hubs in the whole-brain white matter (WM) structural networks among toddlers with autism spectrum disorder (ASD). This study utilized diffusion tensor imaging (DTI) and deterministic tractography to map the WM structural networks in 37 ASD toddlers and 27 age-, gender- and developmental quotient-matched controls with developmental delay (DD) toddlers aged 2-3 years old at baseline (Time 1) and at 2-year follow-up (Time 2). Furthermore, graph-theoretical methods were applied to investigate alterations in the network hubs in these patients at the two time points. The results showed that after 2 years, 17 hubs were identified in the ASD subjects compared to the controls, including 13 hubs that had not changed from baseline and 4 hubs that were newly identified. In addition, alterations in the properties of the hubs of the right middle frontal gyrus, right insula, left median cingulate gyri, and bilateral precuneus were significantly correlated with alterations in the behavioral data for ASD patients. These results indicated that at the stage of 2-5 years of age, ASD children showed distributions of network hubs that were relatively stable, with minor differences. Abnormal developmental patterns in the five areas mentioned above in ASD may contribute to abnormalities in the social and nonsocial characteristics of this disorder. Autism Res 2018, 11: 1218-1228. (c) 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: This work studied the longitudinal developmental patterns of hubs in the whole-brain white matter (WM) structural network among toddlers with autism spectrum disorder (ASD). The findings of this study could have implications for understanding how the abnormalities in hub organization in ASD account for behavioral deficits in patients and may provide potential biomarkers for disease diagnosis and the subsequent monitoring of progression and treatment effects for patients with ASD. En ligne : http://dx.doi.org/10.1002/aur.1983 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=369
in Autism Research > 11-9 (September 2018) . - p.1218-1228[article] Alterations in hub organization in the white matter structural network in toddlers with autism spectrum disorder: A 2-year follow-up study [Texte imprimé et/ou numérique] / L. QIAN, Auteur ; Y. WANG, Auteur ; K. CHU, Auteur ; Y. LI, Auteur ; C. XIAO, Auteur ; T. XIAO, Auteur ; X. XIAO, Auteur ; T. QIU, Auteur ; Y. XIAO, Auteur ; H. FANG, Auteur ; X. KE, Auteur . - p.1218-1228.
Langues : Anglais (eng)
in Autism Research > 11-9 (September 2018) . - p.1218-1228
Mots-clés : autism spectrum disorder brain network developmental trajectory hubs neuromechanism Index. décimale : PER Périodiques Résumé : Little is currently known about the longitudinal developmental patterns of hubs in the whole-brain white matter (WM) structural networks among toddlers with autism spectrum disorder (ASD). This study utilized diffusion tensor imaging (DTI) and deterministic tractography to map the WM structural networks in 37 ASD toddlers and 27 age-, gender- and developmental quotient-matched controls with developmental delay (DD) toddlers aged 2-3 years old at baseline (Time 1) and at 2-year follow-up (Time 2). Furthermore, graph-theoretical methods were applied to investigate alterations in the network hubs in these patients at the two time points. The results showed that after 2 years, 17 hubs were identified in the ASD subjects compared to the controls, including 13 hubs that had not changed from baseline and 4 hubs that were newly identified. In addition, alterations in the properties of the hubs of the right middle frontal gyrus, right insula, left median cingulate gyri, and bilateral precuneus were significantly correlated with alterations in the behavioral data for ASD patients. These results indicated that at the stage of 2-5 years of age, ASD children showed distributions of network hubs that were relatively stable, with minor differences. Abnormal developmental patterns in the five areas mentioned above in ASD may contribute to abnormalities in the social and nonsocial characteristics of this disorder. Autism Res 2018, 11: 1218-1228. (c) 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: This work studied the longitudinal developmental patterns of hubs in the whole-brain white matter (WM) structural network among toddlers with autism spectrum disorder (ASD). The findings of this study could have implications for understanding how the abnormalities in hub organization in ASD account for behavioral deficits in patients and may provide potential biomarkers for disease diagnosis and the subsequent monitoring of progression and treatment effects for patients with ASD. En ligne : http://dx.doi.org/10.1002/aur.1983 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=369 Applying a network framework to the neurobiology of reading and dyslexia / S. K. BAILEY in Journal of Neurodevelopmental Disorders, 10-1 (December 2018)
[article]
Titre : Applying a network framework to the neurobiology of reading and dyslexia Type de document : Texte imprimé et/ou numérique Auteurs : S. K. BAILEY, Auteur ; K. S. ABOUD, Auteur ; T. Q. NGUYEN, Auteur ; L. E. CUTTING, Auteur Année de publication : 2018 Article en page(s) : 37 p. Langues : Anglais (eng) Mots-clés : Brain network Dyslexia Functional MRI Graph theory Individual differences Language Reading Index. décimale : PER Périodiques Résumé : BACKGROUND: There is a substantial literature on the neurobiology of reading and dyslexia. Differences are often described in terms of individual regions or individual cognitive processes. However, there is a growing appreciation that the brain areas subserving reading are nested within larger functional systems, and new network analysis methods may provide greater insight into how reading difficulty arises. Yet, relatively few studies have adopted a principled network-based approach (e.g., connectomics) to studying reading. In this study, we combine data from previous reading literature, connectomics studies, and original data to investigate the relationship between network architecture and reading. METHODS: First, we detailed the distribution of reading-related areas across many resting-state networks using meta-analytic data from NeuroSynth. Then, we tested whether individual differences in modularity, the brain's tendency to segregate into resting-state networks, are related to reading skill. Finally, we determined whether brain areas that function atypically in dyslexia, as identified by previous meta-analyses, tend to be concentrated in hub regions. RESULTS: We found that most resting-state networks contributed to the reading network, including those subserving domain-general cognitive skills such as attention and executive function. There was also a positive relationship between the global modularity of an individual's brain network and reading skill, with the visual, default mode and cingulo-opercular networks showing the highest correlations. Brain areas implicated in dyslexia were also significantly more likely to have a higher participation coefficient (connect to multiple resting-state networks) than other areas. CONCLUSIONS: These results contribute to the growing literature on the relationship between reading and brain network architecture. They suggest that an efficient network organization, i.e., one in which brain areas form cohesive resting-state networks, is important for skilled reading, and that dyslexia can be characterized by abnormal functioning of hub regions that map information between multiple systems. Overall, use of a connectomics framework opens up new possibilities for investigating reading difficulty, especially its commonalities across other neurodevelopmental disorders. En ligne : http://dx.doi.org/10.1186/s11689-018-9251-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=386
in Journal of Neurodevelopmental Disorders > 10-1 (December 2018) . - 37 p.[article] Applying a network framework to the neurobiology of reading and dyslexia [Texte imprimé et/ou numérique] / S. K. BAILEY, Auteur ; K. S. ABOUD, Auteur ; T. Q. NGUYEN, Auteur ; L. E. CUTTING, Auteur . - 2018 . - 37 p.
Langues : Anglais (eng)
in Journal of Neurodevelopmental Disorders > 10-1 (December 2018) . - 37 p.
Mots-clés : Brain network Dyslexia Functional MRI Graph theory Individual differences Language Reading Index. décimale : PER Périodiques Résumé : BACKGROUND: There is a substantial literature on the neurobiology of reading and dyslexia. Differences are often described in terms of individual regions or individual cognitive processes. However, there is a growing appreciation that the brain areas subserving reading are nested within larger functional systems, and new network analysis methods may provide greater insight into how reading difficulty arises. Yet, relatively few studies have adopted a principled network-based approach (e.g., connectomics) to studying reading. In this study, we combine data from previous reading literature, connectomics studies, and original data to investigate the relationship between network architecture and reading. METHODS: First, we detailed the distribution of reading-related areas across many resting-state networks using meta-analytic data from NeuroSynth. Then, we tested whether individual differences in modularity, the brain's tendency to segregate into resting-state networks, are related to reading skill. Finally, we determined whether brain areas that function atypically in dyslexia, as identified by previous meta-analyses, tend to be concentrated in hub regions. RESULTS: We found that most resting-state networks contributed to the reading network, including those subserving domain-general cognitive skills such as attention and executive function. There was also a positive relationship between the global modularity of an individual's brain network and reading skill, with the visual, default mode and cingulo-opercular networks showing the highest correlations. Brain areas implicated in dyslexia were also significantly more likely to have a higher participation coefficient (connect to multiple resting-state networks) than other areas. CONCLUSIONS: These results contribute to the growing literature on the relationship between reading and brain network architecture. They suggest that an efficient network organization, i.e., one in which brain areas form cohesive resting-state networks, is important for skilled reading, and that dyslexia can be characterized by abnormal functioning of hub regions that map information between multiple systems. Overall, use of a connectomics framework opens up new possibilities for investigating reading difficulty, especially its commonalities across other neurodevelopmental disorders. En ligne : http://dx.doi.org/10.1186/s11689-018-9251-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=386 Atypical Inter-Network Deactivation Associated With the Posterior Default-Mode Network in Autism Spectrum Disorder / Aija KOTILA in Autism Research, 14-2 (February 2021)
[article]
Titre : Atypical Inter-Network Deactivation Associated With the Posterior Default-Mode Network in Autism Spectrum Disorder Type de document : Texte imprimé et/ou numérique Auteurs : Aija KOTILA, Auteur ; Matti JÄRVELÄ, Auteur ; Vesa KORHONEN, Auteur ; Soile LOUKUSA, Auteur ; Tuula HURTIG, Auteur ; Hanna EBELING, Auteur ; Vesa KIVINIEMI, Auteur ; Ville RAATIKAINEN, Auteur Article en page(s) : p.248-264 Langues : Anglais (eng) Mots-clés : Asd Mreg brain network default-mode network dynamic lag analysis resting-state fMRI Index. décimale : PER Périodiques Résumé : Previous studies have suggested that atypical deactivation of functional brain networks contributes to the complex cognitive and behavioral profile associated with autism spectrum disorder (ASD). However, these studies have not considered the temporal dynamics of deactivation mechanisms between the networks. In this study, we examined (a) mutual deactivation and (b) mutual activation-deactivation (i.e., anticorrelated) time-lag patterns between resting-state networks (RSNs) in young adults with ASD (n = 20) and controls (n = 20) by applying the recently defined dynamic lag analysis (DLA) method, which measures time-lag variations peak-by-peak between the networks. In order to achieve temporally accurate lag patterns, the brain imaging data was acquired with a fast functional magnetic resonance imaging (fMRI) sequence (TR = 100?ms). Group-level independent component analysis was used to identify 16 RSNs for the DLA. We found altered mutual deactivation timings in ASD in (a) three of the deactivated and (b) two of the transiently anticorrelated (activated-deactivated) RSN pairs, which survived the strict threshold for significance of surrogate data. Of the significant RSN pairs, 80% included the posterior default-mode network (DMN). We propose that temporally altered deactivation mechanisms, including timings and directionality, between the posterior DMN and RSNs mediating processing of socially relevant information may contribute to the ASD phenotype. LAY SUMMARY: To understand autistic traits on a neural level, we examined temporal fluctuations in information flow between brain regions in young adults with autism spectrum disorder (ASD) and controls. We used a fast neuroimaging procedure to investigate deactivation mechanisms between brain regions. We found that timings and directionality of communication between certain brain regions were temporally altered in ASD, suggesting atypical deactivation mechanisms associated with the posterior default-mode network. En ligne : http://dx.doi.org/10.1002/aur.2433 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=441
in Autism Research > 14-2 (February 2021) . - p.248-264[article] Atypical Inter-Network Deactivation Associated With the Posterior Default-Mode Network in Autism Spectrum Disorder [Texte imprimé et/ou numérique] / Aija KOTILA, Auteur ; Matti JÄRVELÄ, Auteur ; Vesa KORHONEN, Auteur ; Soile LOUKUSA, Auteur ; Tuula HURTIG, Auteur ; Hanna EBELING, Auteur ; Vesa KIVINIEMI, Auteur ; Ville RAATIKAINEN, Auteur . - p.248-264.
Langues : Anglais (eng)
in Autism Research > 14-2 (February 2021) . - p.248-264
Mots-clés : Asd Mreg brain network default-mode network dynamic lag analysis resting-state fMRI Index. décimale : PER Périodiques Résumé : Previous studies have suggested that atypical deactivation of functional brain networks contributes to the complex cognitive and behavioral profile associated with autism spectrum disorder (ASD). However, these studies have not considered the temporal dynamics of deactivation mechanisms between the networks. In this study, we examined (a) mutual deactivation and (b) mutual activation-deactivation (i.e., anticorrelated) time-lag patterns between resting-state networks (RSNs) in young adults with ASD (n = 20) and controls (n = 20) by applying the recently defined dynamic lag analysis (DLA) method, which measures time-lag variations peak-by-peak between the networks. In order to achieve temporally accurate lag patterns, the brain imaging data was acquired with a fast functional magnetic resonance imaging (fMRI) sequence (TR = 100?ms). Group-level independent component analysis was used to identify 16 RSNs for the DLA. We found altered mutual deactivation timings in ASD in (a) three of the deactivated and (b) two of the transiently anticorrelated (activated-deactivated) RSN pairs, which survived the strict threshold for significance of surrogate data. Of the significant RSN pairs, 80% included the posterior default-mode network (DMN). We propose that temporally altered deactivation mechanisms, including timings and directionality, between the posterior DMN and RSNs mediating processing of socially relevant information may contribute to the ASD phenotype. LAY SUMMARY: To understand autistic traits on a neural level, we examined temporal fluctuations in information flow between brain regions in young adults with autism spectrum disorder (ASD) and controls. We used a fast neuroimaging procedure to investigate deactivation mechanisms between brain regions. We found that timings and directionality of communication between certain brain regions were temporally altered in ASD, suggesting atypical deactivation mechanisms associated with the posterior default-mode network. En ligne : http://dx.doi.org/10.1002/aur.2433 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=441