Long non-coding RNAs (lncRNAs) play a key role in the human brain, and genetic variants regulate their expression. Herein, expression quantitative trait loci of lncRNAs encompassing 10 brain regions from 134 individuals were analyzed, and novel variants influencing lncRNA expression (eSNPs) and respective affected lncRNAs (elncRNAs) were identified. The eSNPs showed proximity to their corresponding elncRNAs, enriched in the non-coding genome, and have a high minor allele frequency. The elncRNAs exhibit a high-level and complex pattern of expression. The genetic regulation is more tissue specific for lncRNAs than for protein-coding genes, with notable differences between cerebrum and cerebellum. Nonetheless, it shows relatively similar patterns across cortex regions. Furthermore, we observed a significant enrichment of eSNPs among variants associated with neurological disorders, especially insomnia, and identified insomnia-related lncRNAs involved in immune response functions. Moreover, the present study offers an improved tool for lncRNA quantification, a novel approach for lncRNA function analysis, and a database of lncRNA expression regulation in human brain. These findings and resources will advance the research on non-coding gene expression regulation in neuroscience.

Embedded screen-camera communication techniques encode information in screen imagery that can be decoded with a camera receiver yet remains unobtrusive to the human observer. These techniques have applications in tagging content on screens similar to QR-code tagging for other objects. This paper characterizes the design space for flicker-free embedded screen-camera communication. In particular, we identify an orthogonal dimension to prior work: spatial content-adaptive encoding, and observe that it is essential to combine multiple dimensions to achieve both high capacity and minimal flicker. From these insights, we develop content-adaptive encoding techniques that exploit visual features such as edges and texture to unobtrusively communicate information. These can then be layered over existing techniques to further boost the capacity. Our experimental results show that there is potential to achieve an average goodput of about 22 kbps, significantly outperforming existing work while remaining flicker-free.