1. Barton EE, Lawrence K, Deurloo F. {{Individualizing Interventions for Young Children with Autism in Preschool}}. {J Autism Dev Disord};2011 (Feb 19)
Increasing numbers of children with autism receive education services in settings with their typically developing peers. In response to this shift in the location of services, there is a growing body of research identifying evidence-based practices for young children with autism in inclusive early childhood classrooms. The purpose of this paper is to organize and translate this research for application by early childhood practitioners in inclusive settings.
2. Bosl W, Tierney A, Tager-Flusberg H, Nelson C. {{EEG complexity as a biomarker for autism spectrum disorder risk}}. {BMC Med};2011 (Feb 22);9(1):18.
ABSTRACT: BACKGROUND: Complex neurodevelopmental disorders may be characterized by subtle brain function signatures early in life before behavioral symptoms are apparent. Such endophenotypes may be measurable biomarkers for later cognitive impairments. The nonlinear complexity of electroencephalography (EEG) signals is believed to contain information about the architecture of the neural networks in the brain on many scales. Early detection of abnormalities in EEG signals may be an early biomarker for developmental cognitive disorders. The goal of this paper is to demonstrate that the modified multiscale entropy (mMSE) computed on the basis of resting state EEG data can be used as a biomarker of normal brain development and distinguish typically developing children from a group of infants at high risk for autism spectrum disorder (ASD), defined on the basis of an older sibling with ASD. METHODS: Using mMSE as a feature vector, a multiclass support vector machine algorithm was used to classify typically developing and high-risk groups. Classification was computed separately within each age group from 6 to 24 months. RESULTS: Multiscale entropy appears to go through a different developmental trajectory in infants at high risk for autism (HRA) than it does in typically developing controls. Differences appear to be greatest at ages 9 to 12 months. Using several machine learning algorithms with mMSE as a feature vector, infants were classified with over 80% accuracy into control and HRA groups at age 9 months. Classification accuracy for boys was close to 100% at age 9 months and remains high (70% to 90%) at ages 12 and 18 months. For girls, classification accuracy was highest at age 6 months, but declines thereafter. CONCLUSIONS: This proof-of-principle study suggests that mMSE computed from resting state EEG signals may be a useful biomarker for early detection of risk for ASD and abnormalities in cognitive development in infants. To our knowledge, this is the first demonstration of an information theoretic analysis of EEG data for biomarkers in infants at risk for a complex neurodevelopmental disorder.
3. Bradley EA, Ames CS, Bolton PF. {{Psychiatric conditions and behavioural problems in adolescents with intellectual disabilities: correlates with autism}}. {Can J Psychiatry};2011 (Feb);56(2):102-109.
Objective: To determine whether psychiatric and behavioural disorders occur more frequently in adolescents with autism and intellectual disabilities, compared with those without autism. Method: A population-based case-control study was undertaken and 36 adolescents with autism were pairwise matched for age and IQ to 36 adolescents without autism. Caregivers were interviewed with structured psychiatric interview and questionnaire measures of psychiatric and behavioural problems. Results: Compulsive behaviours and stereotypies were significantly more common in adolescents with autism. Conclusions: Adolescents with autism are prone to compulsive behaviours and stereotypies as well as specific manifestations of anxiety, fears, and phobias.
4. Chen KL, Chiang FM, Tseng MH, Fu CP, Hsieh CL. {{Responsiveness of the Psychoeducational Profile-third Edition for Children with Autism Spectrum Disorders}}. {J Autism Dev Disord};2011 (Feb 19)
The aim of this study was to examine the responsiveness of the Psychoeducational Profile-third edition (PEP-3) in children with Autism Spectrum Disorders (ASD). We investigated the responsiveness in terms of three types of scores (i.e., raw scores, developmental ages, and percentile ranks) of the subtests and composites of the PEP-3 and three methods of analysis were used: effect size, standardized response mean, and paired t test. The findings generally support the use of the PEP-3 as an outcome measure. We suggest using the raw scores and developmental ages of the PEP-3 when evaluating program effectiveness and developmental changes for children with ASD.
5. Chung SY, Yoon HJ. {{A framework for treatment of autism using affective computing}}. {Stud Health Technol Inform};2011;163:132-134.
It is known that as many as 1 in 91 children are diagnosed with autistic spectrum disorder. Since the children with autism usually do not express their own emotional status, it is needed to develop a novel technology to sense their emotional status and give proper psychological treatment. This article presents a framework of the treatment system for children with autism using affective computing technologies.
6. Ghanizadeh A. {{Gold implants and increased expression of Metallothionein-I/II as a novel hypothesized therapeutic approach for autism}}. {Toxicology};2011 (Feb 15)
7. Greene DJ, Colich N, Iacoboni M, Zaidel E, Bookheimer SY, Dapretto M. {{Atypical Neural Networks for Social Orienting in Autism Spectrum Disorders}}. {Neuroimage};2011 (Feb 17)
Greater activation for social vs. nonsocial orienting in typical development than ASD. No differences in behavioral performance in typical development and ASD. Group X cue condition interactions confirm group differences in brain activity.
8. Hampson DR, Adusei DC, Pacey LK. {{The Neurochemical Basis for the Treatment of Autism Spectrum Disorders and Fragile X Syndrome}}. {Biochem Pharmacol};2011 (Feb 16)
Autism spectrum disorders (ASD) and Fragile X Syndrome (FXS) are neurodevelopmental disorders that share overlapping behavioral characteristics. While FXS is known to result from a specific genetic mutation, the causes of the majority of cases of ASD are unknown. Animal models of FXS have revealed new insight into the cellular and biochemical changes that occur in the central nervous system in this disorder, while human genetic studies on individuals with autism have identified sets of genes that may increase susceptibility to the disorder. Together these discoveries suggest overlapping biochemical characteristics and reveal new directions for the potential development of pharmacological therapies that might prove useful in the treatment of both FXS and ASD. In particular, delayed synaptic maturation, abnormal synaptic structure and/or function and alterations in intracellular signaling pathways have been linked to the pathogenesis of FXS and ASD. Aberrations in GABA(A) receptor ion channels and the G-protein coupled metabotropic glutamate and GABA(B) transmitter systems are also linked to both disorders and these receptors are currently at the forefront of preclinical and clinical research into treatments for both autism and Fragile X Syndrome.
9. Lee AR, Hong SW, Kim JS, Ju SJ. {{[Life Transition of Mothers of Children with Autism.]}}. {J Korean Acad Nurs};2010 (Dec);40(6):808-819.
PURPOSE: While there are a number of studies on children with disabilities, there have been few studies on mothers of children with autism. The purpose of this study was to explore the process of life transition of mothers who have children with autism. METHODS: From June 2007 to May 2009, the researcher interviewed 15 mothers of children with autism living in Seoul City, Gyeonggi or Chonbuk Provinces, and then analyzed the data gathered using the constant comparative method of grounded theory. RESULTS: « Living together holding a string of fate » was a core category showing along the continuum of life. The basic social process of life transition encompassed 5 stages: stages of denying, wandering, devoting, mind controlling, and finally accepting. These five stages proceeded in phases, though returned back to the wandering stage occasionally. CONCLUSION: This study has opened the door to understanding how mothers of children with autism experienced life transition. The findings suggest that differentiated support and care at each stage should be given and there is the need to develop transition assessment tools for mothers of children with autism.
10. Peter Hobson R. {{Congenital Blindness and Autism}}. {J Autism Dev Disord};2011 (Feb 19)
11. Schnohr CW. {{[The gastrointestinal system’s association with autism.]}}. {Ugeskr Laeger};2011 (Feb 21);173(8):581-583.
Autism was first described by Leo Kanner in 1943. He described common features in 11 children, who were, among others, characterised by limited social interaction and lack of communicative skills. However, Kanner also described characteristics related to the gastrointestinal system. Subsequently, studies have related autism to chronic inflammation in the intestinal lining and to food allergies. If the severity of autism is affected, e.g. by a pathological gastrointestinal condition, there is a possibility that treatment of the secondary condition will lead to improvement in the primary ailment followed by increased well-being.
12. Shukla DK, Keehn B, Smylie DM, Muller RA. {{Microstructural abnormalities of short-distance white matter fiber tracts in autism spectrum disorder}}. {Neuropsychologia};2011 (Feb 16)
Recent functional connectivity magnetic resonance imaging and diffusion tensor imaging (DTI) studies have suggested atypical functional connectivity and reduced integrity of long-distance white matter fibers in autism spectrum disorder (ASD). However, evidence for short-distance white matter fibers is still limited, despite some speculation of potential sparing of local connectivity in ASD. Short-distance U-fibers are an important component of neural networks and are thought to play a crucial role in cognitive function. In the present study, we applied tract-based spatial statistics to derive short- and long-distance white matter fiber tracts in frontal, parietal, and temporal lobes in both hemispheres. DTI data were acquired from 26 children with ASD and 24 typically developing (TD) children. A mean fractional anisotropy (FA) image was created and thinned to represent centers of all common tracts. Evidence of compromised short-distance tracts for the ASD group was found in frontal lobe (reduced FA, increased mean diffusivity [MD] and radial diffusivity) as well as in temporal and parietal lobes (increased MD and radial diffusivity). Significant positive correlations between age and FA and negative correlations between age and MD and radial diffusivity were also found for short-distance tracts in each lobe in the TD, but not the ASD group. These results suggest white matter compromise in short-distance tracts in ASD. Absence of typical age-related correlations with DTI indices may reflect altered maturation of short-distance tracts in ASD. Our results are inconsistent with a notion of selective sparing of short-distance connectivity in ASD.
13. Steiner AM, Koegel LK, Koegel RL, Ence WA. {{Issues and Theoretical Constructs Regarding Parent Education for Autism Spectrum Disorders}}. {J Autism Dev Disord};2011 (Feb 20)
Participation of parents of children with autism is commonplace in most comprehensive intervention programs, yet, there is limited research relating to the best practices in this area. This article provides an overview of parent education programs for young children with autism and details data-driven procedures which are associated with improved parent and child outcomes. In addition, we provide a troubleshooting guide based on the literature for professionals regarding a variety of complex issues which may arise during parent education.
