1. Berry RC, Novak P, Withrow N, Schmidt B, Rarback S, Feucht S, Criado KK, Sharp WG. {{Nutrition Management of Gastrointestinal Symptoms in Children with Autism Spectrum Disorder: Guideline from an Expert Panel}}. {J Acad Nutr Diet};2015 (Jul 9)
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2. Elwin M, Schroder A, Ek L, Kjellin L. {{Development and pilot validation of a sensory reactivity scale for adults with high functioning autism spectrum conditions: Sensory Reactivity in Autism Spectrum (SR-AS)}}. {Nord J Psychiatry};2015 (Jul 9):1-8.
BACKGROUND: Unusual reactions to sensory stimuli are experienced by 90-95% of people with an autism spectrum condition (ASC). Self-reported sensory reactivity in ASC has mainly been measured with generic questionnaires developed and validated on data from the general population. Interest in sensory reactivity in ASC increased after the inclusion of hyper- and hypo-reactivity together with unusual sensory interest as diagnostic markers of ASC in the DSM-5. AIMS: To develop and pilot validate a self-report questionnaire designed from first-hand descriptions of the target group of adults diagnosed with high functioning ASC. Psychometric properties of the questionnaire were evaluated on a sample of participants with ASC diagnoses (N = 71) and a random sample from the general population (N = 162). RESULTS: The Sensory Reactivity in Autism Spectrum (SR-AS is intended to be used as a screening tool in diagnostic processes with adults and for support in adapting compensating strategies and environmental adjustments. The internal consistency was high for both the SR-AS and its subscales. The total scale Cronbach’s alpha was 0.96 and the subscales alphas were >/= 0.80. Confirmatory factor analysis (CFA) showed best fit for a four-factor model of inter-correlated factors: hyper and hypo-reactivity, strong sensory interest and a sensory/motor factor. The questionnaire discriminated well between ASC-diagnosed participants and participants from the general population. CONCLUSIONS: The SR-AS displayed good internal consistency and discriminatory power and promising factorial validity.
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3. Gulati S, Dubey R. {{Adaptive Functioning and Feeding Behavior: Key Targets in Autism Management}}. {Indian J Pediatr};2015 (Jul 9)
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4. Kloth AD, Badura A, Li A, Cherskov A, Connolly SG, Giovannucci A, Bangash MA, Grasselli G, Penagarikano O, Piochon C, Tsai PT, Geschwind DH, Hansel C, Sahin M, Takumi T, Worley PF, Wang SS. {{Cerebellar associative sensory learning defects in five mouse autism models}}. {Elife};2015 (Jul 9);4
Sensory integration difficulties have been reported in autism, but their underlying brain-circuit mechanisms are underexplored. Using five autism-related mouse models, Shank3+/DeltaC, Mecp2R308/Y, Cntnap2-/-, L7-Tsc1 (L7/Pcp2Cre::Tsc1flox/+) and patDp(15q11-13)/+, we report specific perturbations in delay eyeblink conditioning, a form of associative sensory learning requiring cerebellar plasticity. By distinguishing perturbations in the probability and characteristics of learned responses, we found that probability was reduced in Cntnap2-/-, patDp(15q11-13)/+, and L7/Pcp2Cre::Tsc1flox/+, all associated with Purkinje-cell/deep-nuclear gene expression, along with Shank3+/DeltaC. Amplitudes were smaller in L7/Pcp2Cre::Tsc1flox/+ as well as Shank3+/DeltaC and Mecp2R308/Y, which are associated with granule-cell pathway expression. Shank3+/DeltaC and Mecp2R308/Y also showed aberrant response timing and reduced Purkinje-cell dendritic spine density. Overall, our observations are potentially accounted for by defects in instructed learning in the olivocerebellar loop and response representation in the granule cell pathway. Our findings indicate that defects in associative temporal binding of sensory events are widespread in autism mouse models.
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5. Orinstein A, Tyson KE, Suh J, Troyb E, Helt M, Rosenthal M, Barton ML, Eigsti IM, Kelley E, Naigles L, Schultz RT, Stevens MC, Fein DA. {{Psychiatric Symptoms in Youth with a History of Autism and Optimal Outcome}}. {J Autism Dev Disord};2015 (Jul 9)
Since autism spectrum disorder (ASD) is often comorbid with psychiatric disorders, children who no longer meet criteria for ASD (optimal outcome; OO) may still be at risk for psychiatric disorders. A parent interview for DSM-IV psychiatric disorders (K-SADS-PL) for 33 OO, 42 high-functioning autism (HFA) and 34 typically developing (TD) youth, ages 8-21, showed that OO and HFA groups had elevated current ADHD and specific phobias, with tics in HFA. In the past, the HFA group also had elevated depression and ODD, and the OO group had tics. The HFA group also showed subthreshold symptoms of specific and social phobias, and generalized anxiety. Psychopathology in the OO group abated over time as did their autism, and decreased more than in HFA.
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6. Richard AE, Lajiness-O’Neill R. {{Visual attention shifting in autism spectrum disorders}}. {J Clin Exp Neuropsychol};2015 (Jul 9):1-17.
INTRODUCTION: Abnormal visual attention has been frequently observed in autism spectrum disorders (ASD). Abnormal shifting of visual attention is related to abnormal development of social cognition and has been identified as a key neuropsychological finding in ASD. Better characterizing attention shifting in ASD and its relationship with social functioning may help to identify new targets for intervention and improving social communication in these disorders. Thus, the current study investigated deficits in attention shifting in ASD as well as relationships between attention shifting and social communication in ASD and neurotypicals (NT). METHOD: To investigate deficits in visual attention shifting in ASD, 20 ASD and 20 age- and gender-matched NT completed visual search (VS) and Navon tasks with attention-shifting demands as well as a set-shifting task. VS was a feature search task with targets defined in one of two dimensions; Navon required identification of a target letter presented at the global or local level. Psychomotor and processing speed were entered as covariates. Relationships between visual attention shifting, set shifting, and social functioning were also examined. RESULTS: ASD and NT showed comparable costs of shifting attention. However, psychomotor and processing speed were slower in ASD than in NT, and psychomotor and processing speed were positively correlated with attention-shifting costs on Navon and VS, respectively, for both groups. Attention shifting on VS and Navon were correlated among NT, while attention shifting on Navon was correlated with set shifting among ASD. Attention-shifting costs on Navon were positively correlated with restricted and repetitive behaviors among ASD. CONCLUSIONS: Relationships between attention shifting and psychomotor and processing speed, as well as relationships between measures of different aspects of visual attention shifting, suggest inefficient top-down influences over preattentive visual processing in ASD. Inefficient attention shifting may be related to restricted and repetitive behaviors in these disorders.
