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Résultat de la recherche
12 recherche sur le mot-clé 'Resting-state fMRI'




Atypical functional connectivity in resting-state networks of individuals with 22q11.2 deletion syndrome: associations with neurocognitive and psychiatric functioning / L. M. MATTIACCIO in Journal of Neurodevelopmental Disorders, 8-1 (December 2016)
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Titre : Atypical functional connectivity in resting-state networks of individuals with 22q11.2 deletion syndrome: associations with neurocognitive and psychiatric functioning Type de document : Texte imprimé et/ou numérique Auteurs : L. M. MATTIACCIO, Auteur ; I. L. COMAN, Auteur ; M. J. SCHREINER, Auteur ; Kevin M. ANTSHEL, Auteur ; W. P. FREMONT, Auteur ; Carrie E. BEARDEN, Auteur ; W. R. KATES, Auteur Article en page(s) : p.2 Langues : Anglais (eng) Mots-clés : 22q11.2 deletion syndrome Ica Resting-state fMRI Schizophrenia Index. décimale : PER Périodiques Résumé : BACKGROUND: 22q11.2 deletion syndrome (22q11DS) is a neurogenetic condition associated with deficits in neuropsychological functioning and psychiatric disorders. This deletion confers a high risk for the development of psychosis, as approximately 30-45 % of individuals develop psychosis in adulthood. Previous reports of resting-state functional magnetic resonance imaging (rs-fMRI) functional connectivity patterns in 22q11DS have demonstrated that atypical connectivity is associated with both the emergence and severity of psychotic symptoms. However, due to sample overlap and large age ranges of samples spanning multiple critical periods of brain maturation, more independent studies with samples within the window of time when psychotic symptoms have been shown to emerge (ages 17-26) are needed. Resting-state networks (RSNs) in 22q11DS during this stage of brain development may thus provide insight into the dynamic changes in functional integration that influence the incidence of prodromal symptoms and neurocognitive deficits characteristic of this syndrome. METHODS: Independent component analysis (ICA) was performed to identify RSNs in a combined sample of 55 individuals with 22q11DS (27 males; age range 17-26) and 29 controls (17 males; age range 17-23, consisting of 8 siblings without the deletion and 21 typically developed individuals) from two research sites. We conducted a full factorial analysis to determine group differences between 22q11DS and controls. A Poisson regression analysis was conducted in the 22q11DS group to determine relationships of rs-fMRI network connectivity with psychiatric symptoms based on factors of the 18-item Brief Psychiatric Rating Scale. Nonparametric Spearman correlations were performed to test associations between within-network functional connectivity (FC) and performance on measures of verbal memory (California Verbal Learning Test) and executive function (Behavior Rating Inventory of Executive Function Adult version) in 22q11DS. RESULTS: Between-group network connectivity analyses revealed significant differences in 9 RSNs. Decreased network FC in 22q11DS was observed in the following networks: high-level visual processing network (HLVPN), low-level visual processing network (LLVPN), visual/precuneus network, left frontal-parietal network (LFPN), right frontal-parietal network (RFPN), and self-referential network (SRN). In contrast, greater network FC in 22q11DS was observed in subclusters of the LLVPN, visual/precuneus network, limbic network (LN), default mode network (DMN), and visuospatial processing network (VSPN). Increased functional connectivity of the right cuneus (visual/precuneus network) and right superior parietal lobule (DMN) in 22q11DS was positively associated with both thought disturbance and disorganization factors of the Brief Psychiatric Rating Scale (BPRS). Decreased functional connectivity in the left posterior cingulate (LLVPN) was associated with higher thought disturbance scores in 22q11DS. No associations with our neurocognitive measures passed correction for multiple comparisons (Bonferroni-corrected p = 0.0014). CONCLUSIONS: Our findings suggest that atypical network connectivity within RSNs may be indicative of increased risk for developing psychosis and supports the utility of RSNs as biomarkers of prodromal symptoms in 22q11DS. En ligne : http://dx.doi.org/10.1186/s11689-016-9135-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=348
in Journal of Neurodevelopmental Disorders > 8-1 (December 2016) . - p.2[article] Atypical functional connectivity in resting-state networks of individuals with 22q11.2 deletion syndrome: associations with neurocognitive and psychiatric functioning [Texte imprimé et/ou numérique] / L. M. MATTIACCIO, Auteur ; I. L. COMAN, Auteur ; M. J. SCHREINER, Auteur ; Kevin M. ANTSHEL, Auteur ; W. P. FREMONT, Auteur ; Carrie E. BEARDEN, Auteur ; W. R. KATES, Auteur . - p.2.
Langues : Anglais (eng)
in Journal of Neurodevelopmental Disorders > 8-1 (December 2016) . - p.2
Mots-clés : 22q11.2 deletion syndrome Ica Resting-state fMRI Schizophrenia Index. décimale : PER Périodiques Résumé : BACKGROUND: 22q11.2 deletion syndrome (22q11DS) is a neurogenetic condition associated with deficits in neuropsychological functioning and psychiatric disorders. This deletion confers a high risk for the development of psychosis, as approximately 30-45 % of individuals develop psychosis in adulthood. Previous reports of resting-state functional magnetic resonance imaging (rs-fMRI) functional connectivity patterns in 22q11DS have demonstrated that atypical connectivity is associated with both the emergence and severity of psychotic symptoms. However, due to sample overlap and large age ranges of samples spanning multiple critical periods of brain maturation, more independent studies with samples within the window of time when psychotic symptoms have been shown to emerge (ages 17-26) are needed. Resting-state networks (RSNs) in 22q11DS during this stage of brain development may thus provide insight into the dynamic changes in functional integration that influence the incidence of prodromal symptoms and neurocognitive deficits characteristic of this syndrome. METHODS: Independent component analysis (ICA) was performed to identify RSNs in a combined sample of 55 individuals with 22q11DS (27 males; age range 17-26) and 29 controls (17 males; age range 17-23, consisting of 8 siblings without the deletion and 21 typically developed individuals) from two research sites. We conducted a full factorial analysis to determine group differences between 22q11DS and controls. A Poisson regression analysis was conducted in the 22q11DS group to determine relationships of rs-fMRI network connectivity with psychiatric symptoms based on factors of the 18-item Brief Psychiatric Rating Scale. Nonparametric Spearman correlations were performed to test associations between within-network functional connectivity (FC) and performance on measures of verbal memory (California Verbal Learning Test) and executive function (Behavior Rating Inventory of Executive Function Adult version) in 22q11DS. RESULTS: Between-group network connectivity analyses revealed significant differences in 9 RSNs. Decreased network FC in 22q11DS was observed in the following networks: high-level visual processing network (HLVPN), low-level visual processing network (LLVPN), visual/precuneus network, left frontal-parietal network (LFPN), right frontal-parietal network (RFPN), and self-referential network (SRN). In contrast, greater network FC in 22q11DS was observed in subclusters of the LLVPN, visual/precuneus network, limbic network (LN), default mode network (DMN), and visuospatial processing network (VSPN). Increased functional connectivity of the right cuneus (visual/precuneus network) and right superior parietal lobule (DMN) in 22q11DS was positively associated with both thought disturbance and disorganization factors of the Brief Psychiatric Rating Scale (BPRS). Decreased functional connectivity in the left posterior cingulate (LLVPN) was associated with higher thought disturbance scores in 22q11DS. No associations with our neurocognitive measures passed correction for multiple comparisons (Bonferroni-corrected p = 0.0014). CONCLUSIONS: Our findings suggest that atypical network connectivity within RSNs may be indicative of increased risk for developing psychosis and supports the utility of RSNs as biomarkers of prodromal symptoms in 22q11DS. En ligne : http://dx.doi.org/10.1186/s11689-016-9135-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=348 Aberrant local striatal functional connectivity in attention-deficit/hyperactivity disorder / Daniel VON RHEIN in Journal of Child Psychology and Psychiatry, 57-6 (June 2016)
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Titre : Aberrant local striatal functional connectivity in attention-deficit/hyperactivity disorder Type de document : Texte imprimé et/ou numérique Auteurs : Daniel VON RHEIN, Auteur ; Marianne OLDEHINKEL, Auteur ; Christian F. BECKMANN, Auteur ; Jaap OOSTERLAAN, Auteur ; Dirk J. HESLENFELD, Auteur ; Catharina A. HARTMAN, Auteur ; Pieter J. HOEKSTRA, Auteur ; Barbara FRANKE, Auteur ; Roshan COOLS, Auteur ; Jan K. BUITELAAR, Auteur ; Maarten MENNES, Auteur Article en page(s) : p.697-705 Langues : Anglais (eng) Mots-clés : Resting-state fMRI functional connectivity attention-deficit/hyperactivity disorder cortico-striatal networks striatum putamen Index. décimale : PER Périodiques Résumé : Background Task-based and resting-state functional Magnetic Resonance Imaging (fMRI) studies report attention-deficit/hyperactivity disorder (ADHD)-related alterations in brain regions implicated in cortico-striatal networks. We assessed whether ADHD is associated with changes in the brain's global cortico-striatal functional architecture, or whether ADHD-related alterations are limited to local, intrastriatal functional connections. Methods We included a cohort of adolescents with ADHD (N = 181) and healthy controls (N = 140) and assessed functional connectivity of nucleus accumbens, caudate nucleus, anterior putamen, and posterior putamen. To assess global cortico-striatal functional architecture we computed whole-brain functional connectivity by including all regions of interest in one multivariate analysis. We assessed local striatal functional connectivity using partial correlations between the time series of the striatal regions. Results Diagnostic status did not influence global cortico-striatal functional architecture. However, compared to controls, participants with ADHD exhibited significantly increased local functional connectivity between anterior and posterior putamen (p = .0003; ADHD: z = .30, controls: z = .24). Results were not affected by medication use or comorbid oppositional defiant disorder and conduct disorder. Conclusions Our results do not support hypotheses that ADHD is associated with alterations in cortico-striatal networks, but suggest changes in local striatal functional connectivity. We interpret our findings as aberrant development of local functional connectivity of the putamen, potentially leading to decreased functional segregation between anterior and posterior putamen in ADHD. En ligne : http://dx.doi.org/10.1111/jcpp.12529 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=289
in Journal of Child Psychology and Psychiatry > 57-6 (June 2016) . - p.697-705[article] Aberrant local striatal functional connectivity in attention-deficit/hyperactivity disorder [Texte imprimé et/ou numérique] / Daniel VON RHEIN, Auteur ; Marianne OLDEHINKEL, Auteur ; Christian F. BECKMANN, Auteur ; Jaap OOSTERLAAN, Auteur ; Dirk J. HESLENFELD, Auteur ; Catharina A. HARTMAN, Auteur ; Pieter J. HOEKSTRA, Auteur ; Barbara FRANKE, Auteur ; Roshan COOLS, Auteur ; Jan K. BUITELAAR, Auteur ; Maarten MENNES, Auteur . - p.697-705.
Langues : Anglais (eng)
in Journal of Child Psychology and Psychiatry > 57-6 (June 2016) . - p.697-705
Mots-clés : Resting-state fMRI functional connectivity attention-deficit/hyperactivity disorder cortico-striatal networks striatum putamen Index. décimale : PER Périodiques Résumé : Background Task-based and resting-state functional Magnetic Resonance Imaging (fMRI) studies report attention-deficit/hyperactivity disorder (ADHD)-related alterations in brain regions implicated in cortico-striatal networks. We assessed whether ADHD is associated with changes in the brain's global cortico-striatal functional architecture, or whether ADHD-related alterations are limited to local, intrastriatal functional connections. Methods We included a cohort of adolescents with ADHD (N = 181) and healthy controls (N = 140) and assessed functional connectivity of nucleus accumbens, caudate nucleus, anterior putamen, and posterior putamen. To assess global cortico-striatal functional architecture we computed whole-brain functional connectivity by including all regions of interest in one multivariate analysis. We assessed local striatal functional connectivity using partial correlations between the time series of the striatal regions. Results Diagnostic status did not influence global cortico-striatal functional architecture. However, compared to controls, participants with ADHD exhibited significantly increased local functional connectivity between anterior and posterior putamen (p = .0003; ADHD: z = .30, controls: z = .24). Results were not affected by medication use or comorbid oppositional defiant disorder and conduct disorder. Conclusions Our results do not support hypotheses that ADHD is associated with alterations in cortico-striatal networks, but suggest changes in local striatal functional connectivity. We interpret our findings as aberrant development of local functional connectivity of the putamen, potentially leading to decreased functional segregation between anterior and posterior putamen in ADHD. En ligne : http://dx.doi.org/10.1111/jcpp.12529 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=289 Atypical Functional Covariance Connectivity Between Gray and White Matter in Children With Autism Spectrum Disorder / Heng CHEN in Autism Research, 14-3 (March 2021)
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Titre : Atypical Functional Covariance Connectivity Between Gray and White Matter in Children With Autism Spectrum Disorder Type de document : Texte imprimé et/ou numérique Auteurs : Heng CHEN, Auteur ; Jinjin LONG, Auteur ; Shanshan YANG, Auteur ; Bifang HE, Auteur Article en page(s) : p.464-472 Langues : Anglais (eng) Mots-clés : autism spectrum disorder functional covariance connectivity resting-state fMRI white matter function Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with atypical gray matter (GM) and white matter (WM) functional developmental course. However, the functional co-developmental pattern between GM and WM in ASD is unclear. Here, we utilized a functional covariance connectivity method to explore the concordance pattern between GM and WM function in individuals with ASD. A multi-center resting-state fMRI dataset composed of 105 male children with ASD and 102 well-matched healthy controls (HCs) from six sites of the ABIDE dataset was utilized. GM and WM ALFF maps were calculated for each subject. Voxel by voxel functional covariance connectivity of the ALFF values across subjects was calculated between GM and WM for children with ASD and HCs. A Z-test combining FDR multi-comparison correction was then employed to determine whether the functional covariance is significantly different between the two groups. A "bundling" strategy was utilized to ensure that the GM/WM clusters showing atypical functional covariance were larger than 5 voxels. Finally, canonical correlation analysis was conducted to explore whether the atypical GM/WM functional covariance is related to ASD symptoms. Results showed atypical functional covariance connections between specific GM and WM regions, whereas the ALFF values of these regions indicated no significant difference between the two groups. Canonical correlation analysis revealed a significant relationship between the atypical functional covariance and stereotyped behaviors of ASD. The results indicated an altered functional co-developmental pattern between WM and GM in ASD. LAY SUMMARY: White matter (WM) and gray matter (GM) are two major human brain organs supporting brain function. WM and GM functions show a specific co-developmental pattern in typical developed individuals. This study showed that this GM/WM co-developmental pattern was altered in children with ASD, while this altered GM/WM co-developmental pattern was related to stereotyped behaviors. These findings may help understand the GM/WM functional development of ASD. En ligne : http://dx.doi.org/10.1002/aur.2435 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=443
in Autism Research > 14-3 (March 2021) . - p.464-472[article] Atypical Functional Covariance Connectivity Between Gray and White Matter in Children With Autism Spectrum Disorder [Texte imprimé et/ou numérique] / Heng CHEN, Auteur ; Jinjin LONG, Auteur ; Shanshan YANG, Auteur ; Bifang HE, Auteur . - p.464-472.
Langues : Anglais (eng)
in Autism Research > 14-3 (March 2021) . - p.464-472
Mots-clés : autism spectrum disorder functional covariance connectivity resting-state fMRI white matter function Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with atypical gray matter (GM) and white matter (WM) functional developmental course. However, the functional co-developmental pattern between GM and WM in ASD is unclear. Here, we utilized a functional covariance connectivity method to explore the concordance pattern between GM and WM function in individuals with ASD. A multi-center resting-state fMRI dataset composed of 105 male children with ASD and 102 well-matched healthy controls (HCs) from six sites of the ABIDE dataset was utilized. GM and WM ALFF maps were calculated for each subject. Voxel by voxel functional covariance connectivity of the ALFF values across subjects was calculated between GM and WM for children with ASD and HCs. A Z-test combining FDR multi-comparison correction was then employed to determine whether the functional covariance is significantly different between the two groups. A "bundling" strategy was utilized to ensure that the GM/WM clusters showing atypical functional covariance were larger than 5 voxels. Finally, canonical correlation analysis was conducted to explore whether the atypical GM/WM functional covariance is related to ASD symptoms. Results showed atypical functional covariance connections between specific GM and WM regions, whereas the ALFF values of these regions indicated no significant difference between the two groups. Canonical correlation analysis revealed a significant relationship between the atypical functional covariance and stereotyped behaviors of ASD. The results indicated an altered functional co-developmental pattern between WM and GM in ASD. LAY SUMMARY: White matter (WM) and gray matter (GM) are two major human brain organs supporting brain function. WM and GM functions show a specific co-developmental pattern in typical developed individuals. This study showed that this GM/WM co-developmental pattern was altered in children with ASD, while this altered GM/WM co-developmental pattern was related to stereotyped behaviors. These findings may help understand the GM/WM functional development of ASD. En ligne : http://dx.doi.org/10.1002/aur.2435 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=443 Atypical Inter-Network Deactivation Associated With the Posterior Default-Mode Network in Autism Spectrum Disorder / Aija KOTILA in Autism Research, 14-2 (February 2021)
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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 Correlates and predictors of the severity of suicidal ideation in adolescence: an examination of brain connectomics and psychosocial characteristics / Jaclyn S. KIRSHENBAUM in Journal of Child Psychology and Psychiatry, 63-6 (June 2022)
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Titre : Correlates and predictors of the severity of suicidal ideation in adolescence: an examination of brain connectomics and psychosocial characteristics Type de document : Texte imprimé et/ou numérique Auteurs : Jaclyn S. KIRSHENBAUM, Auteur ; Rajpreet CHAHAL, Auteur ; Tiffany C. HO, Auteur ; Lucy S. KING, Auteur ; Anthony J. GIFUNI, Auteur ; Dana MASTROVITO, Auteur ; Saché M. COURY, Auteur ; Rachel L. WEISENBURGER, Auteur ; Ian H. GOTLIB, Auteur Article en page(s) : p.701-714 Langues : Anglais (eng) Mots-clés : Suicidal ideation adolescence graph theory internalizing and externalizing symptoms resting-state fMRI Index. décimale : PER Périodiques Résumé : BACKGROUND: Suicidal ideation (SI) typically emerges during adolescence but is challenging to predict. Given the potentially lethal consequences of SI, it is important to identify neurobiological and psychosocial variables explaining the severity of SI in adolescents. METHODS: In 106 participants (59 female) recruited from the community, we assessed psychosocial characteristics and obtained resting-state fMRI data in early adolescence (baseline: aged 9-13?years). Across 250 brain regions, we assessed local graph theory-based properties of interconnectedness: local efficiency, eigenvector centrality, nodal degree, within-module z-score, and participation coefficient. Four years later (follow-up: ages 13-19?years), participants self-reported their SI severity. We used least absolute shrinkage and selection operator (LASSO) regressions to identify a linear combination of psychosocial and brain-based variables that best explain the severity of SI symptoms at follow-up. Nested-cross-validation yielded model performance statistics for all LASSO models. RESULTS: A combination of psychosocial and brain-based variables explained subsequent severity of SI (R(2?) =?.55); the strongest was internalizing and externalizing symptom severity at follow-up. Follow-up LASSO regressions of psychosocial-only and brain-based-only variables indicated that psychosocial-only variables explained 55% of the variance in SI severity; in contrast, brain-based-only variables performed worse than the null model. CONCLUSIONS: A linear combination of baseline and follow-up psychosocial variables best explained the severity of SI. Follow-up analyses indicated that graph theory resting-state metrics did not increase the prediction of the severity of SI in adolescents. Attending to internalizing and externalizing symptoms is important in early adolescence; resting-state connectivity properties other than local graph theory metrics might yield a stronger prediction of the severity of SI. En ligne : http://dx.doi.org/10.1111/jcpp.13512 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=475
in Journal of Child Psychology and Psychiatry > 63-6 (June 2022) . - p.701-714[article] Correlates and predictors of the severity of suicidal ideation in adolescence: an examination of brain connectomics and psychosocial characteristics [Texte imprimé et/ou numérique] / Jaclyn S. KIRSHENBAUM, Auteur ; Rajpreet CHAHAL, Auteur ; Tiffany C. HO, Auteur ; Lucy S. KING, Auteur ; Anthony J. GIFUNI, Auteur ; Dana MASTROVITO, Auteur ; Saché M. COURY, Auteur ; Rachel L. WEISENBURGER, Auteur ; Ian H. GOTLIB, Auteur . - p.701-714.
Langues : Anglais (eng)
in Journal of Child Psychology and Psychiatry > 63-6 (June 2022) . - p.701-714
Mots-clés : Suicidal ideation adolescence graph theory internalizing and externalizing symptoms resting-state fMRI Index. décimale : PER Périodiques Résumé : BACKGROUND: Suicidal ideation (SI) typically emerges during adolescence but is challenging to predict. Given the potentially lethal consequences of SI, it is important to identify neurobiological and psychosocial variables explaining the severity of SI in adolescents. METHODS: In 106 participants (59 female) recruited from the community, we assessed psychosocial characteristics and obtained resting-state fMRI data in early adolescence (baseline: aged 9-13?years). Across 250 brain regions, we assessed local graph theory-based properties of interconnectedness: local efficiency, eigenvector centrality, nodal degree, within-module z-score, and participation coefficient. Four years later (follow-up: ages 13-19?years), participants self-reported their SI severity. We used least absolute shrinkage and selection operator (LASSO) regressions to identify a linear combination of psychosocial and brain-based variables that best explain the severity of SI symptoms at follow-up. Nested-cross-validation yielded model performance statistics for all LASSO models. RESULTS: A combination of psychosocial and brain-based variables explained subsequent severity of SI (R(2?) =?.55); the strongest was internalizing and externalizing symptom severity at follow-up. Follow-up LASSO regressions of psychosocial-only and brain-based-only variables indicated that psychosocial-only variables explained 55% of the variance in SI severity; in contrast, brain-based-only variables performed worse than the null model. CONCLUSIONS: A linear combination of baseline and follow-up psychosocial variables best explained the severity of SI. Follow-up analyses indicated that graph theory resting-state metrics did not increase the prediction of the severity of SI in adolescents. Attending to internalizing and externalizing symptoms is important in early adolescence; resting-state connectivity properties other than local graph theory metrics might yield a stronger prediction of the severity of SI. En ligne : http://dx.doi.org/10.1111/jcpp.13512 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=475 Hyperconnectivity of the Right Posterior Temporo-parietal Junction Predicts Social Difficulties in Boys with Autism Spectrum Disorder / Hsiang-Yun CHIEN in Autism Research, 8-4 (August 2015)
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PermalinkNetwork-specific sex differentiation of intrinsic brain function in males with autism / D. L. FLORIS in Molecular Autism, 9 (2018)
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PermalinkStructural and functional connectivity in the default mode network in 22q11.2 deletion syndrome / M. C. PADULA in Journal of Neurodevelopmental Disorders, 7-1 (December 2015)
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PermalinkAberrant functional connectivity of inhibitory control networks in children with autism spectrum disorder / W. VOORHIES in Autism Research, 11-11 (November 2018)
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PermalinkCharacterizing intrinsic functional connectivity in relation to impaired self-regulation in intellectually able male youth with autism spectrum disorder / Hsiang-Yuan LIN in Autism, 24-5 (July 2020)
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