Sheikh Hassani, M. | bioRxiv Science

bioRxiv2018

A Novel Dual And Triple RSVP Paradigm For P300 Speller

ObjectiveA speller system enables disabled people, specifically those with spinal cord injuries, to visually select and spell characters. A problem of primary speller systems is that they are gaze shift dependent. To overcome this problem, a single RSVP paradigm was introduced in which characters are displayed one by one at the center of a screen. In this paper, two new protocols named Dual and Triple RSVP paradigms are introduced and their results are compared against the single paradigm.\n\nMethodsIn the Dual and Triple paradigms, two and three characters are displayed at the center of the screen simultaneously, therefore holding the advantage of displaying the target character twice and three times respectively, compared to the one-time appearance in the single paradigm. Subsequently, by reducing the number of repetitions in the Dual and Triple paradigms, it is expected that ITR decreases. To compare the results of these three paradigms, three subjects participated in experiments using all three paradigms.\n\nResultsThe offline results demonstrate an average character detection accuracy of 97% for the single and double protocols, and 80% for the Triple paradigm. In addition, average ITR is calculated to be 5.45, 7.62 and 7.90 bit/min for the single, Dual and Triple paradigms respectively. Results demonstrate an equally good character detection accuracy for the single and Dual paradigms, and a significant increase in ITR in the Dual paradigm compared to the single. The Triple RSVP paradigm demonstrates an almost equal ITR to that of the Dual paradigm, while decreasing character detection accuracy significantly.\n\nConclusionsResults demonstrate that the Dual RSVP paradigm can be recognized as the most suitable approach, by providing the best balance between ITR and character detection accuracy.\n\nSignificanceThis research demonstrates the improved performance of a newly proposed speller system (the Dual RSVP paradigm). By replacing existing methods with this new approach, the performance of speller matrices will be enhanced, and in addition the gaze dependency issue that caused limitations for users suffering from unimpaired oculomotor control will be overcome.

neuroscience↗

bioRxiv2018

miPIE: NGS-based Prediction of miRNA Using Integrated Evidence

Methods for the de novo identification of microRNA (miRNA) have been developed using a range of sequence-based features. With the increasing availability of next generation sequencing (NGS) transcriptome data, there is a need for miRNA identification that integrates both NGS transcript expression-based patterns as well as advanced genomic sequence-based methods. While miRDeep2 does examine the predicted secondary structure of putative miRNA sequences, it does not leverage many of the sequence-based features used in state-of-the-art de novo methods. Meanwhile, other NGS-based methods, such as miRanalyzer, place an emphasis on sequence-based features without leveraging advanced expression-based features reflecting miRNA biosynthesis. This represents an opportunity to combine the strengths of NGS-based analysis with recent advances in de novo sequence-based miRNA prediction. We here develop a method, microRNA Prediction using Integrated Evidence (miPIE), which integrates both expression-based and sequence-based features to achieve significantly improved miRNA prediction performance. Feature selection identifies the 20 most discriminative features, 3 of which reflect strictly expression-based information. Evaluation using precision-recall curves, for six NGS data sets representing six diverse species, demonstrates substantial improvements in prediction performance compared to miRDeep2 and miRanalyzer. The individual contributions of expression-based and sequence-based features are also examined and we demonstrate that their combination is more effective than either alone.

bioinformatics↗