Behavioral neuroscience faces two conflicting demands: long-duration recordings from large neural populations and unimpeded animal behavior. To meet this challenge, we developed ONIX, an open-source data acquisition system with high data throughput (2GB/sec) and low closed-loop latencies (<1ms) that uses a novel 0.3 mm thin tether to minimize behavioral impact. Head position and rotation are tracked in 3D and used to drive active commutation without torque measurements. ONIX can acquire from combinations of passive electrodes, Neuropixels probes, head-mounted microscopes, cameras, 3D-trackers, and other data sources. We used ONIX to perform uninterrupted, long (~7 hours) neural recordings in mice as they traversed complex 3-dimensional terrain. ONIX allowed exploration with similar mobility as non-implanted animals, in contrast to conventional tethered systems which restricted movement. By combining long recordings with full mobility, our technology will enable new progress on questions that require high-quality neural recordings during ethologically grounded behaviors.
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http://dx.doi.org/10.1101/2023.08.30.554672 | DOI Listing |
Sensors (Basel)
November 2024
Science of Learning in Education Centre, National Institute of Education, Nanyang Technological University, Singapore 637616, Singapore.
The Empatica EmbracePlus is a recent innovation in medical-grade wristband wearable sensors that enable unobtrusive continuous measurement of pulse rate, electrodermal activity, skin temperature, and various accelerometry-based actigraphy measures using a minimalistic smartwatch design. The advantage of this lightweight wearable is the potential for holistic longitudinal recording and monitoring of physiological processes that index a suite of autonomic functions, as well as to provide ecologically valid insights into human behaviour, health, physical activity, and psychophysiological processes. Given the longitudinal nature of wearable recordings, EmbracePlus data collection is managed by storing raw timeseries in short 'chunks' in avro file format organised by universal standard time.
View Article and Find Full Text PDFChem Sci
November 2024
School of Chemistry, CRANN and AMBER Research Centres, Trinity College Dublin, College Green Dublin 2 Ireland
Bioinformatics
November 2024
Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China.
Summary: This study introduces easySCF, a tool designed to enhance the interoperability of single-cell data between the two major bioinformatics platforms, R and Python. By supporting seamless data exchange, easySCF improves the efficiency and accuracy of single-cell data analysis.
Availability And Implementation: easySCF utilizes a unified data format (.
Brief Bioinform
November 2024
Department of Computer Science, The University of Hong Kong, Pok Fu Lam Road, Hong Kong, 999077, China.
Ensuring a unified variant representation aligning the sequencing data is critical for downstream analysis as variant representation may differ across platforms and sequencing conditions. Current approaches typically treat variant unification as a post-step following variant calling and are incapable of measuring the correct variant representation from the outset. Aligning variant representations with the alignment before variant calling has benefits like providing reliable training labels for deep learning-based variant caller model training and enabling direct assessment of alignment quality.
View Article and Find Full Text PDFSci Rep
November 2024
Department of Electrical & Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA, 22203, USA.
Bioinformatics software tools are essential to identify informative molecular features that define different phenotypic sample groups. Among the most fundamental and interrelated tasks are missing value imputation, signature gene detection, and differential pattern visualization. However, many commonly used analytics tools can be problematic when handling biologically diverse samples if either informative missingness possess high missing rates with mixed missing mechanisms, or multiple sample groups are compared and visualized in parallel.
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