alexa An Abnormal Cerebellar Network in Children with Autistic Spectrum Disorder: A Morphometric Study
ISSN: 2165-7890

Autism-Open Access
Open Access

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Research Article

An Abnormal Cerebellar Network in Children with Autistic Spectrum Disorder: A Morphometric Study

Alessandro Grecucci1*, Edoardo Pappaianni1 and Roma Siugzdaite2

1Department of Psychology and Cognitive Sciences, University of Trento, Trento, Italy

2Department of Experimental Psychology, University of Ghent, Ghent, Belgium

*Corresponding Author:
Grecucci A
Department of Psychology and Cognitive Sciences
University of Trento, Trento, Italy
Tel: +39-3475956454
E-mail: [email protected]

Received date: 04 May 2016; Accepted date: 30 May 2016; Published date: 06 June, 2016

Citation: Grecucci A, Pappaianni E, Siugzdaite R (2016) An Abnormal Cerebellar Network in Children with Autistic Spectrum Disorder: A Morphometric Study. Autism Open Access 6:178. doi:10.4172/2165-7890.1000178

Copyright: © 2016 Grecucci A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



Autism is a neurodevelopmental disorder characterized by poor social abilities, communication deficiency and restricted behavioural patterns. Recently, scholars started to consider the possibility of detecting biological markers for better and faster diagnosing autism. This problem has been approached from different perspectives considering biochemical, neurophysiological, and neuroanatomical markers. Following this perspective, our intent was to investigate whether a structural brain signature of autism can be detected in children by using a whole brain morphological analysis. To this aim, we selected 43 male children with autistic spectrum disorder and 46 male controls, matched for age. Structural brain images (T1 image), intelligence scores (Full IQ, Verbal IQ, Performance IQ), and Autism Diagnostic Observation Schedule (ADOS) scores were considered for analyses. Source-Based Morphometry, a multivariate method based on Independent Component Analysis to detect maximally independent cortical networks of gray matter differences was applied to autistic and control brains. Results showed a statistically different network between ASD children and controls, including several cerebellar regions (Inferior Semi-lunar lobule, Tuble, Uvula, Pyramis, Declive, Cerebellar Tonsil) and the Fusiform Gyrus, confirming, but, also expanding previous results. In addition, separate temporal, frontal, and parietal networks were found to be significantly correlated with the Stereotyped Behaviour ADOS scores. These morphologic differences may be particularly useful in paving the way for future objective methods to diagnose autism.


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