Straight from the horse's mouth: Increasing self-report in mental health assessment in individuals with intellectual disability.

BACKGROUND: Mental health conditions are common among individuals with intellectual disability. Under recognition of mental health disorders leading to unmet treatment needs is common in this population. This article addresses one major contributing factor, the lack of cognitively accessible self-report measures for individuals with intellectual disability. METHOD: In this literature-informed overview of the state of the field, we discuss the need for, and complexities of, including individuals with intellectual disability in mental health assessments. RESULTS: With appropriate supports, many individuals with intellectual disability can respond to mental health questions. We discuss evidence-based strategies to make mental health assessments more accessible. CONCLUSION: We highlight the need to engage individuals with intellectual disability to provide first-hand information about their health and well-being. New instruments and research procedures should be developed in partnership with individuals with intellectual disability. Self-report may be essential to advancing the science of mental health research.

Low-temperature fabrication of spiking soma circuits using nanocrystalline-silicon TFTs.

Spiking neuron circuits consisting of ambipolar nanocrystalline-silicon (nc-Si) thin-film transistors (TFTs) have been fabricated using low temperature processing conditions (maximum of 250 °C) that allow the use of flexible substrates. These circuits display behaviors commonly observed in biological neurons such as millisecond spike duration, nonlinear frequency-current relationship, and spike frequency adaptation. The maximum drive capacity of a simple soma circuit was estimated to be approximately 9200 synapses. The effect of bias stress-induced threshold voltage degradation of component nc-Si TFTs on the spike frequency of soma circuits is explored. The measured power consumption of the circuit when spiking at 100 Hz was approximately 12 nW. Finally, the power consumption of the soma circuits at different spiking conditions and its implications on a large-scale system are discussed. The fabricated circuits can be employed as part of a compact multilayer learning network.

Neural learning circuits utilizing nano-crystalline silicon transistors and memristors.

Properties of neural circuits are demonstrated via SPICE simulations and their applications are discussed. The neuron and synapse subcircuits include ambipolar nano-crystalline silicon transistor and memristor device models based on measured data. Neuron circuit characteristics and the Hebbian synaptic learning rule are shown to be similar to biology. Changes in the average firing rate learning rule depending on various circuit parameters are also presented. The subcircuits are then connected into larger neural networks that demonstrate fundamental properties including associative learning and pulse coincidence detection. Learned extraction of a fundamental frequency component from noisy inputs is demonstrated. It is then shown that if the fundamental sinusoid of one neuron input is out of phase with the rest, its synaptic connection changes differently than the others. Such behavior indicates that the system can learn to detect which signals are important in the general population, and that there is a spike-timing-dependent component of the learning mechanism. Finally, future circuit design and considerations are discussed, including requirements for the memristive device.

One-step selective chemistry for silicon-on-insulator sensor geometries.

A one-step functionalization process has been developed for oxide-free channels of field effect transistor structures, enabling a self-selective grafting of receptor molecules on the device active area, while protecting the nonactive part from nonspecific attachment of target molecules. Characterization of the self-organized chemical process is performed on both Si(100) and SiO(2) surfaces by infrared and X-ray photoelectron spectroscopy, atomic force microscopy, and electrical measurements. This selective functionalization leads to structures with better chemical stability, reproducibility, and reliability than current SiO(2)-based devices using silane molecules.

Hypertrophic pyloric stenosis: predicting the resolution of biochemical abnormalities.

PURPOSE: Hypertrophic pyloric stenosis (HPS) is a common condition of infancy, often presenting with marked biochemical derangement, requiring correction. Previous studies have looked at the relationship between serum electrolytes and acid-base balance in HPS but not at the relationship between the degree of biochemical derangement and time taken to resolve the biochemical abnormality. METHODS: Retrospective analysis was performed on all 151 infants undergoing pyloromyotomy over a 3 year period. Of these, 105 met the inclusion criteria of: compliance with the unit HPS fluid protocol, and the documentation of at least three serial biochemical investigations. The rate of correction for each biochemical marker (sodium, potassium, chloride, urea, pCO2, hydrogen ion concentration, bicarbonate and the base excess) was plotted against the degree of disturbance and then against time. RESULTS: A significant relationship (P < 0.01) was found between the rate of correction of an abnormal chloride, urea or base excess and the degree of initial derangement. This enables the prediction of the time taken for the required correction of biochemical abnormalities prior to theatre. CONCLUSION: This method of analysis may be of value in comparing the effectiveness of different fluid regimes in use for the correction of biochemical abnormalities in infants with IHPS.