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Digital archive of theses discussed at the University of Pisa


Thesis etd-04082011-233641

Thesis type
Tesi di dottorato di ricerca
Thesis title
Novel methodologies and technologies for the multiscale and multimodal study of Autism Spectrum Disorders (ASDs)
Academic discipline
Course of study
correlatore Dott. Pioggia, Giovanni
correlatore Dott. Tosetti, Michela
tutor Prof.ssa Ahluwalia, Arti Devi
  • arcuate fasciculus
  • biomarkers
  • brain activation
  • Engrailed2
  • metrical features
  • signals
  • tractography
Graduation session start date
The aim of this PhD thesis was the development of novel bioengineering tools and methodologies that provide a support in the study of ASDs.
ASDs are very heterogeneous disturbs and their abnormalities are present both at local and global level. For this reason a multimodal and multiscale approach was followed.
The analysis of microstructure was executed on single Purkinje neurons in culture and on organotypic slices extracted from cerebella of GFP wild-type mice and animal models of ASDs. A methodology for the non-invasive imaging of neurons during their growth was set up and a software called NEMO (NEuron MOrphological analysis tool) for the automatic analysis of morphology and connectivity was developed.
Microstructure properties can be inferred also in vivo through the quite recent technique of Diffusion Tensor Imaging (DTI). DTI studies in ASDs are based on the hypothesis that the disorder involves aberrant brain connectivity and disruption of white matter tracts between regions implicated in social functioning. In this study DTI was used to investigate structural abnormalities in the white matter structure of young children with ASDs. Moreover the neurostructural bases of echolalia were investigated.
The functionality of the brain was analyzed through Functional Magnetic Resonance Imaging (fMRI) using a novel task based on face processing of human, android and robotic faces. A case-control study was performed in order to study how the face processing network is altered in ASDs and how robots are differently processed in ASDs and control groups.
Measurements characterizing physiology and behavior of ASD children were also collected using an innovative platform called FACE-T (FACE-Therapy). FACE-T consists of a specially equipped room in which the child, wearing unobtrusive devices for recording physiological and behavioral data as well as gaze information, can interact with an android (FACE, Facial Automaton for Conveying Emotions) and a therapist.
The focus was on ECG, as from the analysis of power spectrum density of ECG it is possible to extract features related to the autonomic nervous system that is correlated with brain functionality.
These studies give new insights in the study of ASDs exploring aspects not yet addressed. Moreover the methodologies and tools developed could help in the objective characterization of ASD subjects and in the definition of a personalized therapeutic protocol for each child.