scholarly journals Visuomotor brain network activation and functional connectivity among individuals with autism spectrum disorder

2021 ◽  
Author(s):  
Rebecca J. Lepping ◽  
Walker S. McKinney ◽  
Grant C. Magnon ◽  
Sarah K. Keedy ◽  
Zheng Wang ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Autism Spectrum ◽  
Brain Network ◽  
Spectrum Disorder ◽  
Network Activation

scholarly journals Alterations in Social Brain Network Topology at Rest in Children With Autism Spectrum Disorder

2022 ◽  
Author(s):  
Narae Yoon ◽  
Youngmin Huh ◽  
Hyekyoung Lee ◽  
Johanna Inhyang Kim ◽  
Jung Lee ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Network Topology ◽  
Default Mode Network ◽  
Autism Spectrum ◽  
Brain Network ◽  
Preschool Age ◽  
Spectrum Disorder ◽  
Typical Development ◽  
Default Mode

Abstract BackgroundUnderconnectivity in the resting brain is not consistent in autism spectrum disorder (ASD). However, it is known that the default mode network is mainly decreased in childhood ASD. This study investigated the brain network topology as the changes in the connection strength and network efficiency in childhood ASD, including the early developmental stages.MethodsIn this study, 31 ASD children aged 2–11 years were compared with 31 age and sex-matched children showing typical development. We explored the functional connectivity based on graph filtration by assessing the single linkage distance and global and nodal efficiencies using resting-state functional magnetic resonance imaging. The relationship between functional connectivity and clinical scores was also analyzed.ResultsUnderconnectivities within the posterior default mode network subregions and between the inferior parietal lobule and inferior frontal/superior temporal regions were observed in the ASD group. These areas significantly correlated with the clinical phenotypes. The global, local, and nodal network efficiencies were lower in children with ASD than in those with typical development. In the preschool-age children (2–6 years) with ASD, the anterior-posterior connectivity of the default mode network and cerebellar connectivity were reduced.ConclusionsThe observed topological reorganization, underconnectivity, and disrupted efficiency in the default mode network subregions and social function-related regions could be significant biomarkers of childhood ASD.

scholarly journals Locked-In Intact Functional Networks in Children with Autism Spectrum Disorder: A Case-Control Study

2021 ◽  
Vol 11 (9) ◽  
pp. 854
Author(s):  
Andrew R. Pines ◽  
Bethany Sussman ◽  
Sarah N. Wyckoff ◽  
Patrick J. McCarty ◽  
Raymond Bunch ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Autism Spectrum ◽  
Case Control ◽  
Brain Network ◽  
Cognitive Networks ◽  
Spectrum Disorder ◽  
Exact Test ◽  
Individual Level ◽  
Network Activation ◽  
Children With Asd

Resting-state functional magnetic resonance imaging (rs-fMRI) has the potential to investigate abnormalities in brain network structure and connectivity on an individual level in neurodevelopmental disorders, such as autism spectrum disorder (ASD), paving the way toward using this technology for a personalized, precision medicine approach to diagnosis and treatment. Using a case-control design, we compared five patients with severe regressive-type ASD to five patients with temporal lobe epilepsy (TLE) to examine the association between brain network characteristics and diagnosis. All children with ASD and TLE demonstrated intact motor, language, and frontoparietal (FP) networks. However, aberrant networks not usually seen in the typical brain were also found. These aberrant networks were located in the motor (40%), language (80%), and FP (100%) regions in children with ASD, while children with TLE only presented with aberrant networks in the motor (40%) and language (20%) regions, in addition to identified seizure onset zones. Fisher’s exact test indicated a significant relationship between aberrant FP networks and diagnosis (p = 0.008), with ASD and atypical FP networks co-occurring more frequently than expected by chance. Despite severe cognitive delays, children with regressive-type ASD may demonstrate intact typical cortical network activation despite an inability to use these cognitive facilities. The functions of these intact cognitive networks may not be fully expressed, potentially because aberrant networks interfere with their long-range signaling, thus creating a unique “locked-in network” syndrome.

scholarly journals Increased Functional Connectivity Between Subcortical and Cortical Resting-State Networks in Autism Spectrum Disorder

2015 ◽  
Vol 72 (8) ◽  
pp. 767 ◽  
Author(s):  
Leonardo Cerliani ◽  
Maarten Mennes ◽  
Rajat M. Thomas ◽  
Adriana Di Martino ◽  
Marc Thioux ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Resting State ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Resting State Networks

Somatosensory Regions Show Limited Functional Connectivity Differences in Youth with Autism Spectrum Disorder

2018 ◽  
Vol 8 (9) ◽  
pp. 558-566 ◽  
Author(s):  
Brian Cechmanek ◽  
Harriet Johnston ◽  
Sherene Vazhappilly ◽  
Catherine Lebel ◽  
Signe Bray
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Autism Spectrum ◽  
Spectrum Disorder

scholarly journals Multisite Autism Spectrum Disorder Classification Using Convolutional Neural Network Classifier and Individual Morphological Brain Networks

2021 ◽  
Vol 14 ◽  
Author(s):  
Jingjing Gao ◽  
Mingren Chen ◽  
Yuanyuan Li ◽  
Yachun Gao ◽  
Yanling Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Autism Spectrum Disorder ◽  
Convolutional Neural Network ◽  
Structural Mri ◽  
Autism Spectrum ◽  
Brain Network ◽  
Spectrum Disorder ◽  
Structural Covariance ◽  
Almost All ◽  
New Framework

Autism spectrum disorder (ASD) is a range of neurodevelopmental disorders with behavioral and cognitive impairment and brings huge burdens to the patients’ families and the society. To accurately identify patients with ASD from typical controls is important for early detection and early intervention. However, almost all the current existing classification methods for ASD based on structural MRI (sMRI) mainly utilize the independent local morphological features and do not consider the covariance patterns of these features between regions. In this study, by combining the convolutional neural network (CNN) and individual structural covariance network, we proposed a new framework to classify ASD patients with sMRI data from the ABIDE consortium. Moreover, gradient-weighted class activation mapping (Grad-CAM) was applied to characterize the weight of features contributing to the classification. The experimental results showed that our proposed method outperforms the currently used methods for classifying ASD patients with the ABIDE data and achieves a high classification accuracy of 71.8% across different sites. Furthermore, the discriminative features were found to be mainly located in the prefrontal cortex and cerebellum, which may be the early biomarkers for the diagnosis of ASD. Our study demonstrated that CNN is an effective tool to build the framework for the diagnosis of ASD with individual structural covariance brain network.

scholarly journals Decreased homotopic interhemispheric functional connectivity in children with autism spectrum disorder

2020 ◽  
Author(s):  
Shuxia Yao ◽  
Menghan Zhou ◽  
Yuan Zhang ◽  
Feng Zhou ◽  
Qianqian Zhang ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Symptom Severity ◽  
Visual Processing ◽  
Brain Networks ◽  
Cingulate Cortex ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Volume Changes ◽  
Processing Network

AbstractWhile a number of functional and structural changes occur in large-scale brain networks in autism spectrum disorder (ASD), reduced interhemispheric resting state functional connectivity (rsFC) between homotopic regions may be of particular importance as a biomarker. ASD is an early-onset developmental disorder and neural alterations are often age-dependent, reflecting dysregulated developmental trajectories, although no studies have investigated whether homotopic interhemispheric rsFC alterations occur in ASD children. The present study conducted a voxel-based homotopic interhemispheric rsFC analysis in 146 SD and 175 typically developing children under age 10 and examined associations with symptom severity in the Autism Brain Imaging Data Exchange datasets. Given the role of corpus callosum (CC) in interhemispheric connectivity and reported CC volume changes in ASD we additionally examined whether there were parallel volumetric changes in ASD children. Results demonstrated decreased homotopic rsFC in ASD children in the medial prefrontal cortex, precuneus and posterior cingulate cortex of the default mode network (DMN), the dorsal anterior cingulate cortex of the salience network, the precentral gyrus and inferior parietal lobule of the mirror neuron system, the lingual, fusiform and inferior occipital gyri of the visual processing network and thalamus. Symptom severity was associated with homotopic rsFC in regions in the DMN and visual processing network. There were no significant CC volume changes in ASD children. The present study shows that reduced homotopic interhemispheric rsFC in brain networks in ASD adults/adolescents is already present in children of 5-10 years old and further supports their potential use as a general ASD biomarker.

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