Atypical Inter-Network Deactivation Associated With the Posterior Default-Mode Network in Autism Spectrum Disorder / Aija KOTILA in Autism Research, 14-2 (February 2021)  

Public ISBD [article]  inAutism Research > 14-2 (February 2021) . - p.248-264 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 [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

Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder / Ville RAATIKAINEN in Autism Research, 13-2 (February 2020)  

Public ISBD [article]  inAutism Research > 13-2 (February 2020) . - p.244-258 Titre : Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Ville RAATIKAINEN, Auteur ; Vesa KORHONEN, Auteur ; Viola BORCHARDT, Auteur ; Niko HUOTARI, Auteur ; Heta HELAKARI, Auteur ; Janne KANANEN, Auteur ; Lauri RAITAMAA, Auteur ; Leena JOSKITT, Auteur ; Soile LOUKUSA, Auteur ; Tuula HURTIG, Auteur ; Hanna EBELING, Auteur ; Lucina Q. UDDIN, Auteur ; Vesa KIVINIEMI, Auteur ; Finnish Epilepsy ASSOCIATION, Auteur ; Instrumentariumin TIEDESAATIO, Auteur ; Jane ja Aatos Erkon SAATIO, Auteur Article en page(s) : p.244-258 Langues : Anglais (eng) Mots-clés : Asd  Mreg  dynamic lag analysis  human brain  lag pattern  resting state fMRI Index. décimale : PER Périodiques Résumé : This study investigated whole-brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting-state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P-value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default-mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large-scale functional brain networks may contribute to the ASD phenotype. Autism Res 2020, 13: 244-258. (c) 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. LAY SUMMARY: Autism spectrum disorder (ASD) is characterized by atypical neurodevelopment. Using an ultra-fast neuroimaging procedure, we investigated communication across brain regions in adults with ASD compared with neurotypical (NT) individuals. We found that ASD individuals had altered information flow patterns across brain regions. Atypical patterns were concentrated in salience, executive, visual, and default-mode network areas of the brain that have previously been implicated in the pathophysiology of the disorder. En ligne : http://dx.doi.org/10.1002/aur.2218 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=420 [article] Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder [Texte imprimé et/ou numérique] / Ville RAATIKAINEN, Auteur ; Vesa KORHONEN, Auteur ; Viola BORCHARDT, Auteur ; Niko HUOTARI, Auteur ; Heta HELAKARI, Auteur ; Janne KANANEN, Auteur ; Lauri RAITAMAA, Auteur ; Leena JOSKITT, Auteur ; Soile LOUKUSA, Auteur ; Tuula HURTIG, Auteur ; Hanna EBELING, Auteur ; Lucina Q. UDDIN, Auteur ; Vesa KIVINIEMI, Auteur ; Finnish Epilepsy ASSOCIATION, Auteur ; Instrumentariumin TIEDESAATIO, Auteur ; Jane ja Aatos Erkon SAATIO, Auteur . - p.244-258. Langues : Anglais (eng) in Autism Research > 13-2 (February 2020) . - p.244-258 Mots-clés : Asd  Mreg  dynamic lag analysis  human brain  lag pattern  resting state fMRI Index. décimale : PER Périodiques Résumé : This study investigated whole-brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting-state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P-value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default-mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large-scale functional brain networks may contribute to the ASD phenotype. Autism Res 2020, 13: 244-258. (c) 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. LAY SUMMARY: Autism spectrum disorder (ASD) is characterized by atypical neurodevelopment. Using an ultra-fast neuroimaging procedure, we investigated communication across brain regions in adults with ASD compared with neurotypical (NT) individuals. We found that ASD individuals had altered information flow patterns across brain regions. Atypical patterns were concentrated in salience, executive, visual, and default-mode network areas of the brain that have previously been implicated in the pathophysiology of the disorder. En ligne : http://dx.doi.org/10.1002/aur.2218 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=420

Valence Scaling of Dynamic Facial Expressions is Altered in High-Functioning Subjects with Autism Spectrum Disorders: an fMRI Study / Jukka S. RAHKO in Journal of Autism and Developmental Disorders, 42-6 (June 2012)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 42-6 (June 2012) . - p.1011-1024 Titre : Valence Scaling of Dynamic Facial Expressions is Altered in High-Functioning Subjects with Autism Spectrum Disorders: an fMRI Study Type de document : Texte imprimé et/ou numérique Auteurs : Jukka S. RAHKO, Auteur ; Jyri-Johan PAAKKI, Auteur ; Tuomo H. STARCK, Auteur ; Juha NIKKINEN, Auteur ; David L. PAULS, Auteur ; Jari V. KATSYRI, Auteur ; Eira JANSSON-VERKASALO, Auteur ; Alice S. CARTER, Auteur ; Tuula HURTIG, Auteur ; Marja-Leena MATTILA, Auteur ; Katja JUSSILA, Auteur ; Jukka J. REMES, Auteur ; Sanna KUUSIKKO-GAUFFIN, Auteur ; Mikko E. SAMS, Auteur ; Sven BÖLTE, Auteur ; Hanna EBELING, Auteur ; Irma MOILANEN, Auteur ; Osmo TERVONEN, Auteur ; Vesa KIVINIEMI, Auteur Année de publication : 2012 Article en page(s) : p.1011-1024 Langues : Anglais (eng) Mots-clés : Autism spectrum disorders  Emotional facial expressions  Face processing  Functional MRI  Mirror neuron system  Valence Index. décimale : PER Périodiques Résumé : FMRI was performed with the dynamic facial expressions fear and happiness. This was done to detect differences in valence processing between 25 subjects with autism spectrum disorders (ASDs) and 27 typically developing controls. Valence scaling was abnormal in ASDs. Positive valence induces lower deactivation and abnormally strong activity in ASD in multiple regions. Negative valence increased deactivation in visual areas in subjects with ASDs. The most marked differences between valences focus on fronto-insular and temporal regions. This supports the idea that subjects with ASDs may have difficulty in passive processing of the salience and mirroring of expressions. When the valence scaling of brain activity fails, in contrast to controls, these areas activate and/or deactivate inappropriately during facial stimuli presented dynamically. En ligne : http://dx.doi.org/10.1007/s10803-011-1332-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=156 [article] Valence Scaling of Dynamic Facial Expressions is Altered in High-Functioning Subjects with Autism Spectrum Disorders: an fMRI Study [Texte imprimé et/ou numérique] / Jukka S. RAHKO, Auteur ; Jyri-Johan PAAKKI, Auteur ; Tuomo H. STARCK, Auteur ; Juha NIKKINEN, Auteur ; David L. PAULS, Auteur ; Jari V. KATSYRI, Auteur ; Eira JANSSON-VERKASALO, Auteur ; Alice S. CARTER, Auteur ; Tuula HURTIG, Auteur ; Marja-Leena MATTILA, Auteur ; Katja JUSSILA, Auteur ; Jukka J. REMES, Auteur ; Sanna KUUSIKKO-GAUFFIN, Auteur ; Mikko E. SAMS, Auteur ; Sven BÖLTE, Auteur ; Hanna EBELING, Auteur ; Irma MOILANEN, Auteur ; Osmo TERVONEN, Auteur ; Vesa KIVINIEMI, Auteur . - 2012 . - p.1011-1024. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 42-6 (June 2012) . - p.1011-1024 Mots-clés : Autism spectrum disorders  Emotional facial expressions  Face processing  Functional MRI  Mirror neuron system  Valence Index. décimale : PER Périodiques Résumé : FMRI was performed with the dynamic facial expressions fear and happiness. This was done to detect differences in valence processing between 25 subjects with autism spectrum disorders (ASDs) and 27 typically developing controls. Valence scaling was abnormal in ASDs. Positive valence induces lower deactivation and abnormally strong activity in ASD in multiple regions. Negative valence increased deactivation in visual areas in subjects with ASDs. The most marked differences between valences focus on fronto-insular and temporal regions. This supports the idea that subjects with ASDs may have difficulty in passive processing of the salience and mirroring of expressions. When the valence scaling of brain activity fails, in contrast to controls, these areas activate and/or deactivate inappropriately during facial stimuli presented dynamically. En ligne : http://dx.doi.org/10.1007/s10803-011-1332-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=156

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