Tsai, A. C. | Search bioRxiv

bioRxiv2023

OICNet: A Neural Network for Online EEG Source Separation using Independent Component Analysis

Online source separation of EEG signals plays a crucial role in understanding and interpreting brain dynamics in real-time applications such as brain-computer interfaces (BCIs). In this paper, we propose OICNet, a novel neural network designed specifically for online EEG source separation using independent component analysis, aiming to address the challenges of real-time computational efficiency and reliable extraction of independent components from EEG data streams. The OICNet is trained on a loss function that integrates non-Gaussianity measurement and an orthogonality constraint to achieve effective decomposition of multi-channel EEG signals. We conducted comprehensive evaluation of OICNet on both task-related and task-free EEG datasets with comparison against conventional and network-based ICA counterparts. The results demonstrate that OICNet outperforms existing methods in terms of accuracy and computational efficiency. Overall, OICNet provides high-efficiency real-time EEG source separation capabilities and paves the way for advancements in deep-learning EEG processing in real-world BCI applications.

bioinformatics↗

bioRxiv2020

Gut carriage of antimicrobial resistance genes in women exposed to small-scale poultry farms in rural Uganda: a feasibility study

BackgroundAntibiotic use as growth promoters for livestock is presumed to be a major contributor to the acquisition of antimicrobial resistance (AMR) genes in humans, yet data evaluating AMR patterns in the setting of animal exposure are limited to observational studies that do not capture data from prior to livestock introduction. MethodsWe performed a feasibility study by recruiting a subset of women in a delayed-start randomized controlled trial of small-scale chicken farming in order to examine the prevalence of clinically-relevant AMR genes. Stool samples were obtained at baseline and one year from five intervention women who received chickens at the start of the study, six control women who did not receive chickens until the end of the study, and from chickens provided to the control group at the end of the study. Stool was screened for 87 clinically significant AMR genes using a commercially available qPCR array (Qiagen). ResultsChickens harbored 23 AMR genes from classes also found in humans as well as vancomycin and additional {beta}-lactamase resistance genes. After one year of exposure to chickens, six new AMR genes were detected in controls and seven new AMR genes were detected in the intervention group. Women who had direct contact with the chickens sampled in the study had greater similarities in AMR resistance gene patterns to chickens than those who did not have direct contact with chickens sampled (p = 0.006). There was a trend towards increased similarity in AMR gene patterns with chickens at one year (p = 0.12). ConclusionsChickens and humans in this study harbored AMR genes from many antimicrobial classes at both baseline and follow up timepoints. Studies designed to evaluate human AMR genes in the setting of animal exposure should account for high baseline AMR rates, and consider collecting concomitant animal samples, human samples, and environmental samples over time to determine the directionality and source of AMR genes. Trial registration: ClinicalTrials.gov Identifier: NCT02619227

microbiology↗