1. De Leo G, Gonzales CH, Battagiri P, Leroy G. {{A Smart-Phone Application and a Companion Website for the Improvement of the Communication Skills of Children with Autism: Clinical Rationale, Technical Development and Preliminary Results}}. {J Med Syst} (Feb 2)
Autism is a complex neurobiological disorder that is part of a group of disorders known as autism spectrum disorders (ASD). Today, one in 150 individuals is diagnosed with autism. Lack of social interaction and problems with communication are the main characteristics displayed by children with ASD. The Picture Exchange Communication System (PECS) is a communication system where children exchange visual symbols as a form of communication. The visual symbols are laminated pictures stored in a binder. We have designed, developed and are currently testing a software application, called PixTalk which works on any Windows Mobile Smart-phone. Teachers and caregivers can access a web site and select from an online library the images to be downloaded on to the Smart-phone. Children can browse and select images to express their intentions, desires, and emotions using PixTalk. Case study results indicate that PixTalk can be used as part of ongoing therapy.
2. Ecker C, Marquand A, Mourao-Miranda J, Johnston P, Daly EM, Brammer MJ, Maltezos S, Murphy CM, Robertson D, Williams SC, Murphy DG. {{Describing the brain in autism in five dimensions–magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach}}. {J Neurosci} (Aug 11);30(32):10612-10623.
Autism spectrum disorder (ASD) is a neurodevelopmental condition with multiple causes, comorbid conditions, and a wide range in the type and severity of symptoms expressed by different individuals. This makes the neuroanatomy of autism inherently difficult to describe. Here, we demonstrate how a multiparameter classification approach can be used to characterize the complex and subtle structural pattern of gray matter anatomy implicated in adults with ASD, and to reveal spatially distributed patterns of discriminating regions for a variety of parameters describing brain anatomy. A set of five morphological parameters including volumetric and geometric features at each spatial location on the cortical surface was used to discriminate between people with ASD and controls using a support vector machine (SVM) analytic approach, and to find a spatially distributed pattern of regions with maximal classification weights. On the basis of these patterns, SVM was able to identify individuals with ASD at a sensitivity and specificity of up to 90% and 80%, respectively. However, the ability of individual cortical features to discriminate between groups was highly variable, and the discriminating patterns of regions varied across parameters. The classification was specific to ASD rather than neurodevelopmental conditions in general (e.g., attention deficit hyperactivity disorder). Our results confirm the hypothesis that the neuroanatomy of autism is truly multidimensional, and affects multiple and most likely independent cortical features. The spatial patterns detected using SVM may help further exploration of the specific genetic and neuropathological underpinnings of ASD, and provide new insights into the most likely multifactorial etiology of the condition.
3. El-Baz A, Elnakib A, Casanova MF, Gimel’farb G, Switala AE, Jordan D, Rainey S. {{Accurate Automated Detection of Autism Related Corpus Callosum Abnormalities}}. {J Med Syst} (May 6)
The importance of accurate early diagnostics of autism that severely affects personal behavior and communication skills cannot be overstated. Neuropathological studies have revealed an abnormal anatomy of the Corpus Callosum (CC) in autistic brains. We propose a new approach to quantitative analysis of three-dimensional (3D) magnetic resonance images (MRI) of the brain that ensures a more accurate quantification of anatomical differences between the CC of autistic and normal subjects. It consists of three main processing steps: (i) segmenting the CC from a given 3D MRI using the learned CC shape and visual appearance; (ii) extracting a centerline of the CC; and (iii) cylindrical mapping of the CC surface for its comparative analysis. Our experiments revealed significant differences (at the 95% confidence level) between 17 normal and 17 autistic subjects in four anatomical divisions, i.e. splenium, rostrum, genu and body of their CCs.
4. Ghanizadeh A. {{Novel Treatment for Lead Exposure in Children with Autism}}. {Biol Trace Elem Res} (Aug 13)
