
Three shades of grey : detecting brain abnormalities in children with autism by using source-, voxel- and surface-based morphometry
- Author
- Edoardo Pappaiani, Roma Siugzdaite (UGent) , Sofie Vettori, Paola Venuti, Remo Job and Alessandro Grecucci
- Organization
- Abstract
- Autistic spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interactions, communication and stereotyped behavior. Recent evidence from neuroimaging supports the hypothesis that ASD deficits in adults may be related to abnormalities in a specific frontal - temporal network (Autism-specific Structural Network, ASN). To see whether these results extend to younger children and to better characterize these abnormalities, we applied three morphometric methods on brain grey matter of children with and without ASD. We selected 39 sMRI images of male children with ASD and 42 typically developing (TD) from the ABIDE database. We used Source -Based Morphometry (SoBM), a whole-brain multivariate approach to identify grey matter networks, Voxel-Based Morphometry (VBM), a voxel-wise comparison of the local grey matter concentration, and Surface-Based Morphometry (SuBM) for the estimation of the cortical parameters. SoBM showed a bilateral frontal - parietal - temporal network different between groups, including the inferior - middle temporal gyrus, the inferior parietal lobule and the postcentral gyrus; VBM returned differences only in the right temporal lobe; SuBM returned a thinning in the right inferior temporal lobe thinner in ASD, a higher gyrification in the right superior parietal lobule in TD and in the middle frontal gyrus in ASD.
- Keywords
- Autism, MRI, VBM, Source based morphometry, Surface based morphometry
Downloads
-
ejn13704.pdf
- full text
- |
- open access
- |
- x-unknown/octet-stream
- |
- 1.21 MB
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8532274
- MLA
- Pappaiani, Edoardo, et al. “Three Shades of Grey : Detecting Brain Abnormalities in Children with Autism by Using Source-, Voxel- and Surface-Based Morphometry.” EUROPEAN JOURNAL OF NEUROSCIENCE, vol. 47, no. 6, 2018, pp. 690–700.
- APA
- Pappaiani, E., Siugzdaite, R., Vettori, S., Venuti, P., Job, R., & Grecucci, A. (2018). Three shades of grey : detecting brain abnormalities in children with autism by using source-, voxel- and surface-based morphometry. EUROPEAN JOURNAL OF NEUROSCIENCE, 47(6), 690–700.
- Chicago author-date
- Pappaiani, Edoardo, Roma Siugzdaite, Sofie Vettori, Paola Venuti, Remo Job, and Alessandro Grecucci. 2018. “Three Shades of Grey : Detecting Brain Abnormalities in Children with Autism by Using Source-, Voxel- and Surface-Based Morphometry.” EUROPEAN JOURNAL OF NEUROSCIENCE 47 (6): 690–700.
- Chicago author-date (all authors)
- Pappaiani, Edoardo, Roma Siugzdaite, Sofie Vettori, Paola Venuti, Remo Job, and Alessandro Grecucci. 2018. “Three Shades of Grey : Detecting Brain Abnormalities in Children with Autism by Using Source-, Voxel- and Surface-Based Morphometry.” EUROPEAN JOURNAL OF NEUROSCIENCE 47 (6): 690–700.
- Vancouver
- 1.Pappaiani E, Siugzdaite R, Vettori S, Venuti P, Job R, Grecucci A. Three shades of grey : detecting brain abnormalities in children with autism by using source-, voxel- and surface-based morphometry. EUROPEAN JOURNAL OF NEUROSCIENCE. 2018;47(6):690–700.
- IEEE
- [1]E. Pappaiani, R. Siugzdaite, S. Vettori, P. Venuti, R. Job, and A. Grecucci, “Three shades of grey : detecting brain abnormalities in children with autism by using source-, voxel- and surface-based morphometry,” EUROPEAN JOURNAL OF NEUROSCIENCE, vol. 47, no. 6, pp. 690–700, 2018.
@article{8532274, abstract = {Autistic spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interactions, communication and stereotyped behavior. Recent evidence from neuroimaging supports the hypothesis that ASD deficits in adults may be related to abnormalities in a specific frontal - temporal network (Autism-specific Structural Network, ASN). To see whether these results extend to younger children and to better characterize these abnormalities, we applied three morphometric methods on brain grey matter of children with and without ASD. We selected 39 sMRI images of male children with ASD and 42 typically developing (TD) from the ABIDE database. We used Source -Based Morphometry (SoBM), a whole-brain multivariate approach to identify grey matter networks, Voxel-Based Morphometry (VBM), a voxel-wise comparison of the local grey matter concentration, and Surface-Based Morphometry (SuBM) for the estimation of the cortical parameters. SoBM showed a bilateral frontal - parietal - temporal network different between groups, including the inferior - middle temporal gyrus, the inferior parietal lobule and the postcentral gyrus; VBM returned differences only in the right temporal lobe; SuBM returned a thinning in the right inferior temporal lobe thinner in ASD, a higher gyrification in the right superior parietal lobule in TD and in the middle frontal gyrus in ASD.}, author = {Pappaiani, Edoardo and Siugzdaite, Roma and Vettori, Sofie and Venuti, Paola and Job, Remo and Grecucci, Alessandro}, issn = {0953-816X}, journal = {EUROPEAN JOURNAL OF NEUROSCIENCE}, keywords = {Autism,MRI,VBM,Source based morphometry,Surface based morphometry}, language = {eng}, number = {6}, pages = {690--700}, title = {Three shades of grey : detecting brain abnormalities in children with autism by using source-, voxel- and surface-based morphometry}, url = {http://dx.doi.org/10.1111/ejn.13704}, volume = {47}, year = {2018}, }
- Altmetric
- View in Altmetric
- Web of Science
- Times cited: