1. Bara BG, Ciaramidaro A, Walter H, Adenzato M. {{Intentional Minds: A Philosophical Analysis of Intention Tested through fMRI Experiments Involving People with Schizophrenia, People with Autism, and Healthy Individuals}}. {Front Hum Neurosci};2011;5:7.
IN THIS PAPER WE SHOW HOW WE EMPIRICALLY TESTED ONE OF THE MOST RELEVANT TOPICS IN PHILOSOPHY OF MIND THROUGH A SERIES OF FMRI EXPERIMENTS: the classification of different types of intention. To this aim, firstly we trace a theoretical distinction among private, prospective, and communicative intentions. Second, we propose a set of predictions concerning the recognition of these three types of intention in healthy individuals, and we report the experimental results corroborating our theoretical model of intention. Third, we derive from our model predictions relevant for the domain of psychopathological functioning. In particular, we treat the cases of both hyper-intentionality (as in paranoid schizophrenia) and hypo-intentionality (as in autistic spectrum disorders). Our conclusion is that the theoretical model of intention we propose contributes to enlarge our knowledge on the neurobiological bases of intention processing, in both healthy people and in people with impairments to the neurocognitive system that underlies intention recognition.
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. Ghanizadeh A. {{May GABA transaminase inhibitors improve stereotyped behaviors in Rett syndrome?}}. {Amino Acids};2011 (Feb 23)
4. Hall HR, Graff JC. {{The relationships among adaptive behaviors of children with autism, family support, parenting stress, and coping}}. {Issues Compr Pediatr Nurs};2011;34(1):4-25.
Background: As the number of children diagnosed with autism continues to rise, resources must be available to support parents of children with autism and their families. Parents need help as they assess their unique situations, reach out for help in their communities, and work to decrease their stress levels by using appropriate coping strategies that will benefit their entire family. Methods: A descriptive, correlational, cross-sectional study was conducted with 75 parents/primary caregivers of children with autism. Using the McCubbin and Patterson model of family behavior, adaptive behaviors of children with autism, family support networks, parenting stress, and parent coping were measured. Findings and Conclusions: An association between low adaptive functioning in children with autism and increased parenting stress creates a need for additional family support as parents search for different coping strategies to assist the family with ongoing and new challenges. Professionals should have up-to-date knowledge of the supports available to families and refer families to appropriate resources to avoid overwhelming them with unnecessary and inappropriate referrals.
5. Patil RR. {{MMR vaccination and autism: Learnings and implications}}. {Hum Vaccin};2011 (Feb 1);7(2)
The Lancet has indeed taken an unprecedented action by retracting a research paper published by Dr. Wakefield citing misconduct and ethical fraud [1]. The paper published in 1998 indicated possible linkage between MMR vaccine and autism [2]. With this, The Lancet has done great service to the cause of public health, especially to developing world where the immunization is the only credible health insurance that could be offered to their citizens. With developing countries already struggling to provide measles vaccine coverage beyond 50% to children, the majority of whom are undernourished caught in the unending vicious cycle of infection, malnutrition and early child mortality.
6. Persico AM. {{Polyomaviruses and autism: more than simple association?}}. {J Neurovirol};2010 (Jul);16(4):332-333.
7. Wallace GL, Case LK, Harms MB, Silvers JA, Kenworthy L, Martin A. {{Diminished Sensitivity to Sad Facial Expressions in High Functioning Autism Spectrum Disorders is Associated with Symptomatology and Adaptive Functioning}}. {J Autism Dev Disord};2011 (Feb 24)
Prior studies implicate facial emotion recognition (FER) difficulties among individuals with autism spectrum disorders (ASD); however, many investigations focus on FER accuracy alone and few examine ecological validity through links with everyday functioning. We compared FER accuracy and perceptual sensitivity (from neutral to full expression) between 42 adolescents with high functioning (IQ > 80) ASD and 31 typically developing adolescents (matched on age, IQ, sex ratio) across six basic emotions and examined links between FER and symptomatology/adaptive functioning within the ASD group. Adolescents with ASD required more intense facial expressions for accurate emotion identification. Controlling for this overall group difference revealed particularly diminished sensitivity to sad facial expressions in ASD, which was uniquely correlated with ratings of autism-related behavior and adaptive functioning.
