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Advanced Neuroimaging Methods for Studying Autism Disorder

Contributor(s): Material type: TextTextPublication details: Frontiers Media SA 2017Description: 1 electronic resource (141 p.)ISBN:
  • 978-2-88945-316-0
Subject(s): Online resources: Summary: In the last twenty years, many attempts have been made to provide neurobiological models of autism. Functional, structural and connectivity analyses have highlighted reduced responses in key social areas, such as amygdala, medial prefrontal cortex, cingulate cortex, and superior temporal sulcus. However, these studies present discrepant results and some of them have been questioned for methodological limitations. The aim of this research topic is to present advanced neuroimaging methods able to capture the complexity of the neural deficits displayed in autism. This special issue presents new studies using structural and functional MRI, as well as magnetoencephalography, and novel protocols to analyze data (Analysis of Cluster Variability, Noise Reduction Strategies, Source-based Morphometry, Functional Connectivity Density, Restriction Spectrum Imaging and the others). We believe it is time to integrate data provided by different techniques and methodologies in order to have a better understanding of autism.
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In the last twenty years, many attempts have been made to provide neurobiological models of autism. Functional, structural and connectivity analyses have highlighted reduced responses in key social areas, such as amygdala, medial prefrontal cortex, cingulate cortex, and superior temporal sulcus. However, these studies present discrepant results and some of them have been questioned for methodological limitations. The aim of this research topic is to present advanced neuroimaging methods able to capture the complexity of the neural deficits displayed in autism. This special issue presents new studies using structural and functional MRI, as well as magnetoencephalography, and novel protocols to analyze data (Analysis of Cluster Variability, Noise Reduction Strategies, Source-based Morphometry, Functional Connectivity Density, Restriction Spectrum Imaging and the others). We believe it is time to integrate data provided by different techniques and methodologies in order to have a better understanding of autism.

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