Statistical Learning, Syllable Processing, and Speech Production in Healthy Hearing and Hearing-Impaired Preschool Children: A Mismatch Negativity Study

OBJECTIVES The objectives of the present study were to investigate temporal/spectral sound-feature processing in preschool children (4 to 7 years old) with peripheral hearing loss compared with age-matched controls. The results verified the presence of statistical learning, which was diminished in children with hearing impairments (HIs), and elucidated possible perceptual mediators of speech production. DESIGN Perception and production of the syllables /ba/, /da/, /ta/, and /na/ were recorded in 13 children with normal hearing and 13 children with HI. Perception was assessed physiologically through event-related potentials (ERPs) recorded by EEG in a multifeature mismatch negativity paradigm and behaviorally through a discrimination task. Temporal and spectral features of the ERPs during speech perception were analyzed, and speech production was quantitatively evaluated using speech motor maximum performance tasks. RESULTS Proximal to stimulus onset, children with HI displayed a difference in map topography, indicating diminished statistical learning. In later ERP components, children with HI exhibited reduced amplitudes in the N2 and early parts of the late disciminative negativity components specifically, which are associated with temporal and spectral control mechanisms. Abnormalities of speech perception were only subtly reflected in speech production, as the lone difference found in speech production studies was a mild delay in regulating speech intensity. CONCLUSIONS In addition to previously reported deficits of sound-feature discriminations, the present study results reflect diminished statistical learning in children with HI, which plays an early and important, but so far neglected, role in phonological processing. Furthermore, the lack of corresponding behavioral abnormalities in speech production implies that impaired perceptual capacities do not necessarily translate into productive deficits.

Management of children with autism spectrum disorder in the dental setting: concerns, behavioural approaches and recommendations

OBJECTIVES This article reviews the present literature on the issues encountered while coping with children with autistic spectrum disorder from the dental perspective. The autistic patient profile and external factors affecting the oral health status of this patient population are discussed upon the existing body of evidence. MATERIAL AND METHODS The MEDLINE database was searched using the terms 'Autistic Disorder', 'Behaviour Control/methods', 'Child', 'Dental care for disabled', 'Education', 'Oral Health', and 'Pediatric Dentistry' to locate related articles published up to January 2013. RESULTS Most of the relevant studies indicate poor oral hygiene whereas they are inconclusive regarding the caries incidence in autistic individuals. Undergraduate dental education appears to determine the competence of dental professionals to treat developmentally disabled children and account partly for compromised access to dental care. Dental management of an autistic child requires in-depth understanding of the background of the autism and available behavioural guidance theories. The dental professional should be flexible to modify the treatment approach according to the individual patient needs.

Soziales und moralisches Denken von Kindern über den Ein- und Ausschluss behinderter Kinder

Die Studie untersucht, wie 70 Kindergartenkinder im Vergleich zu 71 Fünft- und Sechstklässler über Situationen denken, in welchen sich ein Protagonist für die Wahl eines behinderten oder nicht behinderten Kindes in seine Gruppe entscheiden musste. Die Situationen wurden nach Behinderungsform des behinderten Kindes (geistig behindert, körperbehindert) und nach Gruppenaktivität (schulisch, sozial, sportlich) variiert. Die Kinder sollten die Wahl des Protagonisten vorhersagen und die Wahl begründen. Die älteren Kinder berücksichtigten in ihren Überlegungen stärker den situativen Kontext als die jüngeren Kinder. Allerdings erwarteten sie weniger häufig den Einschluss des geistig behinderten Kindes als den Einschluss des körperbehinderten Kindes. Die Ergebnisse der Studie werden vor dem Hintergrund von Forschung zur Entwicklung sozialen und moralischen Denkens über Ein- und Ausschluss diskutiert.

Neural network based glucose - insulin metabolism models for children with Type 1 diabetes

In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.

Personality factors in elementary school children: Contributions to academic performance over and above executive functions?

Unique contributions of Big Five personality factors to academic performance in young elementary school children were explored. Extraversion and Openness (labeled “Culture” in our study) uniquely contributed to academic performance, over and above the contribution of executive functions in first and second grade children (N = 446). Well established associations between Conscientiousness and academic performance, however, could only be replicated with regard to zero-order correlations. Executive functions (inhibition, updating, and shifting), for their part, proved to be powerful predictors of academic performance. Results were to some extent dependent on the criterion with which academic performance was measured: Both personality factors had stronger effects on grades than on standardized achievement tests, whereas the opposite was true for executive functions. Finally, analyses on gender differences revealed that Extraversion and Openness/Culture played a more dominant role in girls than in boys, but only regarding grades.

Personalized Tuning of a Reinforcement Learning Control Algorithm for Glucose Regulation

Artificial pancreas is in the forefront of research towards the automatic insulin infusion for patients with type 1 diabetes. Due to the high inter- and intra-variability of the diabetic population, the need for personalized approaches has been raised. This study presents an adaptive, patient-specific control strategy for glucose regulation based on reinforcement learning and more specifically on the Actor-Critic (AC) learning approach. The control algorithm provides daily updates of the basal rate and insulin-to-carbohydrate (IC) ratio in order to optimize glucose regulation. A method for the automatic and personalized initialization of the control algorithm is designed based on the estimation of the transfer entropy (TE) between insulin and glucose signals. The algorithm has been evaluated in silico in adults, adolescents and children for 10 days. Three scenarios of initialization to i) zero values, ii) random values and iii) TE-based values have been comparatively assessed. The results have shown that when the TE-based initialization is used, the algorithm achieves faster learning with 98%, 90% and 73% in the A+B zones of the Control Variability Grid Analysis for adults, adolescents and children respectively after five days compared to 95%, 78%, 41% for random initialization and 93%, 88%, 41% for zero initial values. Furthermore, in the case of children, the daily Low Blood Glucose Index reduces much faster when the TE-based tuning is applied. The results imply that automatic and personalized tuning based on TE reduces the learning period and improves the overall performance of the AC algorithm.