Quantifying the effects of temperature and noise on attention-level using EDA and EEG sensors

Most people with Autism Spectrum Disorder (ASD) experience atypical sensory modality and need help to self-regulate their sensory responses. Results of a pilot study are presented here where temperature, noise types and noise levels are used as independent variables. Attention-based tests (ABTs), Electrodermal Activity (EDA) and Electroencephalography (EEG) sensors are used as dependent variables to quantify the effects of temperature and noise. Based on the outcome of the analyses, it is feasible to use off-the-shelf sensors to recognize physiological changes, indicating a possibility to develop sensory management recommendation interventions to support people with ASD

Genome-wide identification of autosomal genes with allelic imbalance of chromatin state

In mammals, monoallelic gene expression can result from X-chromosome inactivation, genomic imprinting, and random monoallelic expression (RMAE). Epigenetic regulation of RMAE is not fully understood. Here we analyze allelic imbalance in chromatin state of autosomal genes using ChIP-seq in a clonal cell line. We identify approximately 3.7% of autosomal genes that show significant differences between chromatin states of two alleles. Allelic regulation is represented among several functional gene categories including histones, chromatin modifiers, and multiple early developmental regulators. Most cases of allelic skew are produced by quantitative differences between two allelic chromatic states that belong to the same gross type (active, silent, or bivalent). Combinations of allelic states of different types are possible but less frequent. When different chromatin marks are skewed on the same gene, their skew is coordinated as a result of quantitative relationships between these marks on each individual allele. Finally, combination of allele-specific densities of chromatin marks is a quantitative predictor of allelic skew in gene expression