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Three shades of grey : detecting brain abnormalities in children with autism by using Source-, Voxel- and Surface-based Morphometry

Edoardo Pappaiani, Roma Siugzdaite UGent, Sofie Vettori, Paola Venuti, Remo Job and Alessandro Grecucci (2017) EUROPEAN JOURNAL OF NEUROSCIENCE.
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.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
in press
subject
keyword
Autism, MRI, VBM, Source based morphometry, Surface based morphometry
journal title
EUROPEAN JOURNAL OF NEUROSCIENCE
ISSN
0953-816X
DOI
10.1111/ejn.13704
language
English
UGent publication?
yes
classification
A1
copyright statement
I don't know the status of the copyright for this publication
id
8532274
handle
http://hdl.handle.net/1854/LU-8532274
alternative location
http://onlinelibrary.wiley.com/doi/10.1111/ejn.13704/full
date created
2017-09-26 07:59:02
date last changed
2017-09-28 12:41:40
@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},
  keyword      = {Autism,MRI,VBM,Source based morphometry,Surface based morphometry},
  language     = {eng},
  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},
  year         = {2017},
}

Chicago
Pappaiani, Edoardo, Roma Siugzdaite, Sofie Vettori, Paola Venuti, Remo Job, and Alessandro Grecucci. 2017. “Three Shades of Grey : Detecting Brain Abnormalities in Children with Autism by Using Source-, Voxel- and Surface-based Morphometry.” European Journal of Neuroscience.
APA
Pappaiani, E., Siugzdaite, R., Vettori, S., Venuti, P., Job, R., & Grecucci, A. (2017). Three shades of grey : detecting brain abnormalities in children with autism by using Source-, Voxel- and Surface-based Morphometry. EUROPEAN JOURNAL OF NEUROSCIENCE.
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. 2017;
MLA
Pappaiani, Edoardo, Roma Siugzdaite, Sofie Vettori, 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 (2017): n. pag. Print.