Lateralization of Brain Networks and Clinical Severity in Toddlers with Autism Spectrum Disorder: A HARDI Diffusion MRI Study

2015 ◽  
Vol 9 (3) ◽  
pp. 382-392 ◽  
Author(s):  
Eugenia Conti ◽  
Sara Calderoni ◽  
Anna Gaglianese ◽  
Kerstin Pannek ◽  
Sara Mazzotti ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Diffusion Mri ◽  
Brain Networks ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Clinical Severity ◽  
Mri Study

scholarly journals Network over-connectivity differentiates autism spectrum disorder from other developmental disorders in toddlers: A diffusion MRI study

2017 ◽  
Vol 38 (5) ◽  
pp. 2333-2344 ◽  
Author(s):  
E. Conti ◽  
J. Mitra ◽  
S. Calderoni ◽  
K. Pannek ◽  
K. K. Shen ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Diffusion Mri ◽  
Developmental Disorders ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Mri Study

scholarly journals Measuring Robustness of Brain Networks in Autism Spectrum Disorder with Ricci Curvature

2019 ◽  
Author(s):  
Anish K. Simhal ◽  
Kimberly L.H. Carpenter ◽  
Saad Nadeem ◽  
Joanne Kurtzberg ◽  
Allen Song ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Ricci Curvature ◽  
Diffusion Mri ◽  
Brain Networks ◽  
Autism Spectrum ◽  
Brain Network ◽  
Spectrum Disorder ◽  
Global Changes ◽  
Before And After ◽  
The Brain

ABSTRACTRicci curvature is a method for measuring the robustness of networks. In this work, we use Ricci curvature to measure robustness of brain networks affected by autism spectrum disorder (ASD). Subjects with ASD are given a stem cell infusion and are imaged with diffusion MRI before and after the infusion. By using Ricci curvature to measure changes in robustness, we quantify both local and global changes in the brain networks correlated with the infusion. Our results find changes in regions associated with ASD that were not detected via traditional brain network analysis.

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.

scholarly journals Cortical Anatomy in Autism Spectrum Disorder: An In Vivo MRI Study on the Effect of Age

2009 ◽  
Vol 20 (6) ◽  
pp. 1332-1340 ◽  
Author(s):  
Armin Raznahan ◽  
Roberto Toro ◽  
Eileen Daly ◽  
Dene Robertson ◽  
Clodagh Murphy ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Mri Study ◽  
Effect Of Age

scholarly journals Multimodal Diffusion-MRI and MEG Assessment of Auditory and Language System Development in Autism Spectrum Disorder

2016 ◽  
Vol 10 ◽  
Author(s):  
Jeffrey I. Berman ◽  
James C. Edgar ◽  
Lisa Blaskey ◽  
Emily S. Kuschner ◽  
Susan E. Levy ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Diffusion Mri ◽  
System Development ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Language System

scholarly journals A Study of the Correlation between VEP and Clinical Severity in Children with Autism Spectrum Disorder

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Winai Sayorwan ◽  
Nutthida Phianchana ◽  
Kannika Permpoonputtana ◽  
Vorasith Siripornpanich
Keyword(s):  
Autism Spectrum Disorder ◽  
Electrical Response ◽  
Children With Autism ◽  
Visual Pathway ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Clinical Severity ◽  
Pattern Reversal ◽  
Vineland Adaptive Behavior Scales ◽  
Children With Asd

Visual evoked potential (VEP) is a technique used to assess the brain’s electrical response to visual stimuli. The aims of this study were to examine neural transmission within the visual pathway through VEP testing in preschool children with autism spectrum disorder (ASD) and compare it to age-matched controls, as well as search for a correlation between the VEP parameters and the symptoms of ASD. Participants were composed of ASD children (9 males) and typically developing children (8 males and 4 females), aged between 3 and 5 years. Checkerboards were chosen as the pattern-reversal VEP. The clinical severity of ASD was assessed using the Autism Treatment Evaluation Checklist (ATEC) and the Vineland Adaptive Behavior Scales 2nd edition (VABS-II). Our findings demonstrated that children with ASD had significantly longer N145 latency compared to the controls. A longer N145 latency correlated with a higher score of ATEC within the sensory/cognitive awareness subdomain. In addition, a slower N145 response was also associated with a lower VABS-II score within the socialization domain. The correlation between longer VEP latency and abnormal behaviors in children with ASD suggests a delayed neural communication within other neural circuits, apart from the visual pathway. These lines of evidence support the possibility of using VEP, along with clinical parameters, for the assessment of ASD severity.

scholarly journals Attention and Working Memory in Adolescents with Autism Spectrum Disorder: A Functional MRI Study

2015 ◽  
Vol 47 (3) ◽  
pp. 503-517 ◽  
Author(s):  
Jukka S. Rahko ◽  
Virve A. Vuontela ◽  
Synnöve Carlson ◽  
Juha Nikkinen ◽  
Tuula M. Hurtig ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Working Memory ◽  
Functional Mri ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Adolescents With Autism ◽  
Mri Study

scholarly journals Evaluating Functional Connectivity Alterations in Autism Spectrum Disorder Using Network-Based Statistics

Diagnostics ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. 51 ◽  
Author(s):  
Aitana Pascual-Belda ◽  
Antonio Díaz-Parra ◽  
David Moratal
Keyword(s):  
Autism Spectrum Disorder ◽  
Brain Connectivity ◽  
Brain Networks ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Typical Development ◽  
Functional Brain ◽  
Functional Brain Networks ◽  
Management Functions ◽  
The Brain

The study of resting-state functional brain networks is a powerful tool to understand the neurological bases of a variety of disorders such as Autism Spectrum Disorder (ASD). In this work, we have studied the differences in functional brain connectivity between a group of 74 ASD subjects and a group of 82 typical-development (TD) subjects using functional magnetic resonance imaging (fMRI). We have used a network approach whereby the brain is divided into discrete regions or nodes that interact with each other through connections or edges. Functional brain networks were estimated using the Pearson’s correlation coefficient and compared by means of the Network-Based Statistic (NBS) method. The obtained results reveal a combination of both overconnectivity and underconnectivity, with the presence of networks in which the connectivity levels differ significantly between ASD and TD groups. The alterations mainly affect the temporal and frontal lobe, as well as the limbic system, especially those regions related with social interaction and emotion management functions. These results are concordant with the clinical profile of the disorder and can contribute to the elucidation of its neurological basis, encouraging the development of new clinical approaches.

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