The Influence of Pitch-by-Pitch Feedback on Neural Activity and Pitch Perception in Baseball.

This study was designed to examine the influence of performance feedback on task performance and neural activity in expert and novice baseball players. Participants completed a video task to determine whether thrown pitches were balls or strikes while their neural activity was recorded. After each pitch, participants were given feedback on the accuracy of their choice. Results indicated that college players exhibited larger frontocentral positivity amplitudes compared with novices, regardless of feedback type. Furthermore, results showed that the feedback-related negativity was related to response accuracy following incorrect feedback for college players, with larger feedback-related negativity amplitude associated with greater response accuracy. This relationship is independent of any relations between overall task accuracy and either feedback-related negativity amplitude or response accuracy following incorrect feedback. These results indicate that the nature of neural activity during pitch feedback for college baseball players can inform and influence participants' subsequent pitch-location performance.

Impacting development in infants with tuberous sclerosis complex: Multidisciplinary research collaboration.

The Tuberous Sclerosis Complex Autism Center of Excellence Network (TACERN) is a 6-site collaborative conducting longitudinal research on infants with tuberous sclerosis complex (TSC), focused on identifying early biomarkers for autism spectrum disorder (ASD). A multidisciplinary research team that includes the specialties of psychology, neurology, pediatrics, medical genetics, and speech-language pathology, its members work together to conduct studies on neurological status, brain structure and function, neurodevelopmental phenotype, and behavioral challenges in this population. This article provides insights into the roles of the multidisciplinary multisite team and lessons learned from the collaboration, in terms of research as well as training of future researchers and clinicians. In addition, the authors detail the major findings to date, including those related to the identification and measurement of early symptoms of ASD, relationship between seizures and early development, and early biomarkers for epilepsy and developmental delay in infants and young children with TSC. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Improving Access to Diagnostic Assessments for Autism Spectrum Disorder Using an Arena Model.

OBJECTIVE: To improve access to diagnostic evaluations for children younger than 3 years with concerns for possible autism spectrum disorder. METHODS: A multidisciplinary "arena model" for children younger than 3 years was developed, tested, and implemented over an approximately 2-year period. Arena assessment teams comprised a developmental behavioral pediatrician (DBP), psychologist, and speech language pathologist (SLP). Quality improvement methods were used during the design phase, conducting Plan-Do-Study-Act (PDSA) cycles and collecting feedback from key stakeholders, and during implementation, plotting data on run charts to measure outcomes of the time to initial visit and time to diagnosis. RESULTS: Over the 9-month implementation period, 6 arena assessment teams were formed to provide 60 evaluation slots per month for children younger than 3 years. The time to first visit was reduced from a median of 122 days to 19 days, and the time to final diagnosis was reduced from 139 days to 14 days, maintaining these outcomes at <35 and <18 days, respectively, over a 2-year period. Total visits required decreased from 4 to 5 visits to just 2 visits, and the average assessment cost was reduced by $992 per patient. Feedback from both providers and families participating in this model was overwhelmingly positive. CONCLUSION: Access for young children referred for developmental assessments can be improved through an understanding of supply and demand and the development of creative and flexible care delivery models.

Utility of the Autism Observation Scale for Infants in Early Identification of Autism in Tuberous Sclerosis Complex.

BACKGROUND: Tuberous sclerosis complex (TSC) is a genetic disorder with high prevalence of associated autism spectrum disorder (ASD). Our primary objectives were to determine early predictors of autism risk to identify children with TSC in most need of early interventions. The Autism Observation Scale for Infants (AOSI) was evaluated as a measure of ASD-associated behaviors in infants with TSC at age 12 months and its ability to predict ASD at 24 months. METHODS: Children ages 0 to 36 months with TSC were enrolled in the TSC Autism Center of Excellence Research Network (TACERN), a multicenter, prospective observational study to identify biomarkers of ASD. The AOSI was administered at age 12 months and the Autism Diagnostic Observation Schedule-2 (ADOS-2) and Autism Diagnostic Interview-Revised (ADI-R) at 24 months. Developmental functioning was assessed using the Mullen Scales of Early Learning. Children were classified as ASD or non-ASD according to the ADOS-2. RESULTS: Analysis included 79 children who had been administered the AOSI at 12 months and ADOS-2 and ADI-R at 24 months. The ASD group had a mean AOSI total score at 12 months significantly higher than the non-ASD group (11.8 ± 7.4 vs 6.3 ± 4.7; P < 0.001). An AOSI total score cutoff of 13 provided a specificity of 0.89 to detect ASD with the ADOS-2. AOSI total score at 12 months was similarly associated with exceeding cutoff scores on the ADI-R. CONCLUSIONS: The AOSI is a useful clinical tool in determining which infants with TSC are at increased risk for developing ASD.

A Prospective Study of the Concordance of DSM-IV and DSM-5 Diagnostic Criteria for Autism Spectrum Disorder.

The transition from DSM-IV to DSM-5 criteria for autism spectrum disorder (ASD) sparked considerable concern about the potential implications of these changes. This study was designed to address limitations of prior studies by prospectively examining the concordance of DSM-IV and final DSM-5 criteria on a consecutive sample of 439 children referred for autism diagnostic evaluations. Concordance and discordance were assessed using a consistent diagnostic battery. DSM-5 criteria demonstrated excellent overall specificity and good sensitivity relative to DSM-IV criteria. Sensitivity and specificity were strongest for children meeting DSM-IV criteria for autistic disorder, but poor for those meeting criteria for Asperger's disorder and pervasive developmental disorder. Higher IQ, older age, female sex, and less pronounced ASD symptoms were associated with greater discordance.

Influence of seizures on early development in tuberous sclerosis complex.

OBJECTIVE: Epilepsy is commonly seen in Tuberous Sclerosis Complex (TSC). The relationship between seizures and developmental outcomes has been reported, but few studies have examined this relationship in a prospective, longitudinal manner. The objective of the study was to evaluate the relationship between seizures and early development in TSC. METHODS: Analysis of 130 patients ages 0-36months with TSC participating in the TSC Autism Center of Excellence Network, a large multicenter, prospective observational study evaluating biomarkers predictive of autism spectrum disorder (ASD), was performed. Infants were evaluated longitudinally with standardized evaluations, including cognitive, adaptive, and autism-specific measures. Seizure history was collected continuously throughout, including seizure type and frequency. RESULTS: Data were analyzed at 6, 12, 18, and 24months of age. Patients without a history of seizures performed better on all developmental assessments at all time points compared to patients with a history of seizures and exhibited normal development at 24months. Patients with a history of seizures not only performed worse, but developmental progress lagged behind the group without seizures. All patients with a history of infantile spasms performed worse on all developmental assessments at 12, 18, and 24months. Higher seizure frequency correlated with poorer outcomes on developmental testing at all time points, but particularly at 12months and beyond. Patients with higher seizure frequency during infancy continued to perform worse developmentally through 24months. A logistic model looking at the individual impact of infantile spasms, seizure frequency, and age of seizure onset as predictors of developmental delay revealed that age of seizure onset was the most important factor in determining developmental outcome. CONCLUSIONS: Results of this study further define the relationship between seizures and developmental outcomes in young children with TSC. Early seizure onset in infants with TSC negatively impacts very early neurodevelopment, which persists through 24months of age.

Electronic Health Record Based Algorithm to Identify Patients with Autism Spectrum Disorder.

OBJECTIVE: Cohort selection is challenging for large-scale electronic health record (EHR) analyses, as International Classification of Diseases 9th edition (ICD-9) diagnostic codes are notoriously unreliable disease predictors. Our objective was to develop, evaluate, and validate an automated algorithm for determining an Autism Spectrum Disorder (ASD) patient cohort from EHR. We demonstrate its utility via the largest investigation to date of the co-occurrence patterns of medical comorbidities in ASD. METHODS: We extracted ICD-9 codes and concepts derived from the clinical notes. A gold standard patient set was labeled by clinicians at Boston Children's Hospital (BCH) (N = 150) and Cincinnati Children's Hospital and Medical Center (CCHMC) (N = 152). Two algorithms were created: (1) rule-based implementing the ASD criteria from Diagnostic and Statistical Manual of Mental Diseases 4th edition, (2) predictive classifier. The positive predictive values (PPV) achieved by these algorithms were compared to an ICD-9 code baseline. We clustered the patients based on grouped ICD-9 codes and evaluated subgroups. RESULTS: The rule-based algorithm produced the best PPV: (a) BCH: 0.885 vs. 0.273 (baseline); (b) CCHMC: 0.840 vs. 0.645 (baseline); (c) combined: 0.864 vs. 0.460 (baseline). A validation at Children's Hospital of Philadelphia yielded 0.848 (PPV). Clustering analyses of comorbidities on the three-site large cohort (N = 20,658 ASD patients) identified psychiatric, developmental, and seizure disorder clusters. CONCLUSIONS: In a large cross-institutional cohort, co-occurrence patterns of comorbidities in ASDs provide further hypothetical evidence for distinct courses in ASD. The proposed automated algorithms for cohort selection open avenues for other large-scale EHR studies and individualized treatment of ASD.

Autism spectrum disorders.

Autism spectrum disorders are being diagnosed with increasing frequency. The likelihood that a primary care provider will see a patient with autism spectrum disorder in their clinic is high. In this article, current diagnostic criteria and expected changes in DSM criteria, as well as prevalence rates and epidemiologic studies are reviewed. Recommendations for screening, including early warning signs, and best practices for diagnosis are discussed. Comprehensive evidence based intervention for ASD as well as the findings of the National Standards Project are reviewed. Medication management is also described, as are the roles of other treating professionals.

Food variety as a predictor of nutritional status among children with autism.

The frequency of selective eating and nutritional deficiency was studied among 22 children with autism and an age matched typically developing control group. Children with autism ate fewer foods on average than typically developing children. (33.5 vs. 54.5 foods, P < .001) As compared to typical controls, children with autism had a higher average intake of magnesium, and lower average intake of protein, calcium, vitamin B12, and vitamin D. Selective eaters were significantly more likely than typical controls to be at risk for at least one serious nutrient deficiency (P < .001).